research on food color

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New report shows artificial food coloring causes hyperactivity in some kids

• 2 min. read ▪ Published May 24, 2021
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A report released in April 2021 by the state of California—with contributors from UC Berkeley and UC Davis—confirmed the long-suspected belief that the consumption of synthetic food dyes can cause hyperactivity and other neurobehavioral issues for some children.

The report also found that federal rules for safe amounts of consumption of synthetic food dyes do not reflect the most current research and may not be protecting children’s behavioral health.

Over the past 20 years, the percentage of American children and adolescents diagnosed with Attention Deficit/Hyperactivity Disorder (ADHD) has increased from an estimated 6.1% to 10.2%. Concerns over ADHD and other behavioral disorders led the California Legislature to ask the California Environmental Protection Agency’s Office of Environmental Health Hazard Assessment (OEHHA) to conduct the report, which is based on two years of extensive evaluation of existing studies on the seven synthetic food dyes currently approved by the FDA.

“Evidence shows that synthetic food dyes are associated with adverse neurobehavioral outcomes in some children,” said OEHHA Director Lauren Zeise. “With increasing numbers of U.S. children diagnosed with behavioral disorders, this assessment can inform efforts to protect children from exposures that may exacerbate behavioral problems.”

Researchers found that all of the FDA’s Acceptable Daily Intake levels (ADIs) for synthetic food dyes are based on 35- to 70-year-old studies that were not designed to detect the types of behavioral effects that have been observed in children. Comparisons with newer studies indicate that the current ADIs may not adequately protect children from behavioral effects.

“This is the most comprehensive study examining dietary exposure to artificial food coloring in vulnerable populations such as young children and pregnant women. We found that children tended to have higher exposures than adults, and some exposures might exceed regulatory guidelines,” said UC Berkeley Environmental Health Sciences Professor Asa Bradman, who contributed to the report. “We also observed higher exposures in lower-income populations, pointing to the need to improve consumption of, and access to, healthier food.”

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• Reporting from KQED

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• Open access
• Published: 22 April 2015

On the psychological impact of food colour

• Charles Spence 1  

Flavour volume  4 , Article number:  21 ( 2015 ) Cite this article

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Colour is the single most important product-intrinsic sensory cue when it comes to setting people’s expectations regarding the likely taste and flavour of food and drink. To date, a large body of laboratory research has demonstrated that changing the hue or intensity/saturation of the colour of food and beverage items can exert a sometimes dramatic impact on the expectations, and hence on the subsequent experiences, of consumers (or participants in the lab). However, should the colour not match the taste, then the result may well be a negatively valenced disconfirmation of expectation. Food colours can have rather different meanings and hence give rise to differing expectations, in different age groups, not to mention in different cultures. Genetic differences, such as in a person’s taster status, can also modulate the psychological impact of food colour on flavour perception. By gaining a better understanding of the sensory and hedonic expectations elicited by food colour in different groups of individuals, researchers are coming to understand more about why it is that what we see modulates the multisensory perception of flavour, as well as our appetitive and avoidance-related food behaviours.

Under most everyday conditions (excepting perhaps the dine-in-the-dark restaurant; see [ 1 ]), consumers have the opportunity to inspect food and drink visually before deciding on whether or not to buy or taste it [ 2 ]. Indeed, it has long been recognized that colour constitutes one of the most salient of visual cues concerning the likely sensory properties (for example, taste/flavour) of that which we are about to eat or drink (for example, [ 3 - 10 ]). There is a very long history of colouring being added to food and drink [ 11 - 13 ]. Furthermore, although little studied, those colours that we take to suggest that a food may have gone off can exert a particularly powerful effect on our food avoidance behaviours [ 14 , 15 ]. As such, food colour can be considered as perhaps the single most important product-intrinsic sensory cue governing the sensory and hedonic expectations that the consumer holds concerning the foods and drinks that they search for, purchase, and which they may subsequently consume. a

At the outset, though, it is important to distinguish clearly between taste and flavour, two terms that are used more or less interchangeably in everyday language [ 16 , 17 ]. The reason being that colour cues appear to have a somewhat different effect on taste versus flavour perception (see [ 18 ], for a review). Strictly speaking, ‘taste’ refers to the perception of sweet, sour, bitter, salty, and the other basic tastes, which are detected by the gustatory receptors found primarily in the oral cavity. By contrast, ‘flavour’ refers to those experiences that also involve a retronasal olfactory component, such as meaty, burnt, floral, fruity, citrusy, and so on (see [ 17 ]). However, confusing matters somewhat, in everyday language, people typically use the term taste to describe their overall experience of food and drink. Here, the terms are used with their more precise scientific meaning.

A growing body of scientific research now suggests that our experience of taste and flavour is determined to a large degree by the expectations that we generate (often automatically) prior to tasting [ 19 - 21 ]. Such expectations can result from branding, labelling, packaging, and other contextual effects (that is, from a host of product-extrinsic cues) but also from a variety of product-intrinsic cues as well. The smell and aroma of food and drink are clearly important here, as are, on occasion, the sounds of food preparation (see [ 22 ], for a review). That said, olfactory cues can often be obscured by product packaging, and the products on the supermarket shelf rarely make any sound when inspected visually. Hence, it is vision, and most often colour, that is the cue used by the brain in order to help identify sources of food and make predictions about their likely taste and flavour [ 20 , 23 ]. Or, as the spokesperson for the Institute of Food Technologists put it a few years ago: ‘Color creates a psychological expectation for a certain flavor that is often impossible to dislodge.’ [ 24 ].

The focus in this article is on the psychological effect, or better said, effects, that food colour exerts over the mind and behaviour of the consumer. The review starts by looking at the effect of food colouring on sensory expectations and hence on people’s judgments of taste/flavour intensity and flavour identity (see [ 18 ], for a review). The literature on off-colours in foods and drinks is reviewed briefly, and popular concerns regarding artificial food colouring highlighted. Attention will be drawn to research showing the important individual differences in terms of the meaning, and hence psychological influence, of colour in food. Along the way, some of the problems associated with the interpretation of much of the laboratory research that has been conducted to date will be highlighted.

Although falling beyond the scope of the present review, it is worth noting that colour is but one aspect of vision’s influence over taste and flavour perception. Researchers have, for instance, reported that people tend to judge the freshness of fish, in part, based on the luminance distribution (that is, the glossiness) of fish eyes [ 25 ]. The luminance distribution also appears to be an important cue for judging the freshness of certain fruit and vegetables as well [ 26 ]. The influence of visual food texture on people’s sensory perception and consumption behaviour has also been studied by researchers [ 27 - 29 ]. However, given space constraints, the focus here will be squarely on colour and its psychological impact on the perception/behaviour of the consumer.

Psychological effects of food colour: setting sensory expectations

Taste/flavour intensity.

It would seem reasonable to assume that wherever in the world one finds oneself, more intensely coloured foods are likely to be more intensely flavoured. What also seems likely is that consumers will have picked up on this statistical regularity in the environment and hence will tend to expect that more intensely coloured foods and beverages (not to mention the packaging in which such products come) will have a more intense taste/flavour. Should those expectations not be met, then a negatively valenced disconfirmation of expectation response may well ensue (for example, [ 30 - 32 ]). b Over the last 50 years or so, a large body of laboratory research has demonstrated that adding more colouring to a food, or more often, to a beverage (see [ 33 ], for a review), can lead the participants in laboratory research to rate the taste and/or flavour as more intense (for example, [ 18 , 34 - 38 ]).

The addition of food colouring influences sensory thresholds for certain of the basic tastes. In one classic study, Maga [ 39 ] demonstrated that adding food colouring (red, green, or yellow) to an otherwise clear solution exerted a significant effect on thresholds for the detection of certain of the basic tastes when presented in solution. Adding green food colouring decreased people’s detection threshold for sourness, while at the same time increasing the threshold for the detection of sweetness. The addition of yellow colouring reduced the detection threshold for both sourness and sweetness, while the addition of red colouring reduced the threshold for the detection of bitterness. c Intriguingly, the threshold for the detection of salt was unaffected by the addition of food colouring. Maga’s [ 39 ] suggestion at the time was that this null effect resulted from the fact that salty foods are associated with foods of many different colours and hence that salt is not associated with a particular colour. As Maga himself put it: ‘numerous foods of varying color can be characterized as tasting salty, examples would be pretzels (brown), potato chips (yellow), popcorn (white), olives (green, black), and pickles (green).’ ([ 39 ], p. 118). That said, more recent research has clearly demonstrated that most people do tend to associate salt with the colour white (see [ 40 ]). Perhaps, then, had Maga tested a different range of colours, he might have come to a somewhat different conclusion.

Perhaps the most convincing evidence published to date concerning the influence of food colouring on ratings of taste intensity comes from research published by Clydesdale et al . [ 41 ]. These researchers conducted a number of psychophysical studies showing that the addition of food colouring can deliver as much as 10% perceived sweetness. Indeed, such results have led some to wonder whether food colouring could be used as an effective means of reducing the sugar content of foods. While this is certainly a theoretical possibility, it is worth bearing in mind that the majority of the studies that have been published to date have involved fairly short-term exposure to particular combinations of colour-taste/flavour. While demonstrating that food colouring has an impact on sweetness perception in the short term is one thing, it is quite another to convincingly demonstrate that it will necessarily have psychological effects that last over the long term (cf. [ 42 ]). Hence, longer-term follow-ups are most definitely in order. What is more, as the studies discussed below make only too clear, psychological effects of food colouring on the perception of taste and flavour intensity have not always been demonstrated.

One null result in this area was reported by Norton and Johnson [ 38 ]. These researchers manipulated the intensity of four typical drink colours. They were unable to find any meaningful relationship between the intensity of the colour and flavour ratings on either a sweet-sour scale or on a distinct-indistinct flavour scale in the 18 participants whom they tested. Meanwhile, Lavin and Lawless [ 43 ] investigated the influence of varying the intensity of food colouring on ratings of sweetness intensity. The participants were given two pairs of strawberry-flavoured drinks to compare and to rate in terms of their sweetness, using nine-point scales. One pair of drinks was light and dark red, whereas the other pair was light and dark green. The drinks were equally physically sweet, varying only in terms of their appearance properties (that is, colour). Those adults who took part in this study rated the dark-red and light-green drinks as tasting sweeter than the light-red and dark-green samples, respectively. By contrast, colour intensity had no effect on the responses of 5- and 14-year-old children. Elsewhere, Alley and Alley [ 44 ] similarly failed to demonstrate any effect of the addition of colour (red, blue, yellow, or green) to an otherwise colourless base (either liquid or solid) on the perceived sweetness of sugar solutions in a group of 11 to 13 year olds.

In a study by Philipsen et al . [ 45 ], a group of young adults (aged 18 to 22 years) and a group of older participants (aged 60 to 75 years) rated a number of attributes (for example, sweetness, flavour intensity, flavour quality, flavour identification, and so on) of 15 samples of an artificially flavoured cherry drink that varied in terms of its sucrose content, flavour, and colour. Interestingly, variations in colour intensity had no effect on sweetness ratings in either age group but did impact on flavour intensity ratings in the older participants.

In another study, Chan and Kane-Martinelli [ 46 ] examined the effect of food colouring on perceived flavour intensity and acceptability ratings in samples of chicken bouillon and chocolate pudding. These foods were presented with no colour added, with the normal (that is, commercial) level of food colouring, or with twice the normal level of colour added. The participants tasted and evaluated the three samples of either food, using visual analogue scales. Younger adults (20 to 35 years of age) were found to be more affected by the presence of food colouring than were the older adults (60 to 90 years of age). Interestingly, the younger group’s judgment of the overall flavour intensity of the chicken bouillon was influenced by the amount of colouring that had been added to the sample.

Zampini et al . [ 47 ] conducted a study in which a group of adults had to try and identify the flavour of a variety of drinks and rate perceived flavour intensity using a labelled magnitude scale. The drinks were flavourless, or else had an orange, lime, or strawberry flavour, and could be presented as colourless solutions, or else artificially coloured red, green, or orange. The food colouring was added at either a standard or double concentration. However, variations in the intensity of the food colouring (no matter whether that colour was appropriate or inappropriate to the flavour of the drink) had no effect on the perceived flavour intensity. That said, the addition of inappropriate food colouring significantly impaired the accuracy of participants’ flavour identification responses (see Figure  1 ), thus suggesting that the participants were unable to ignore the colour of the drinks completely, as they had been encouraged to do by the experimenter.

Mean percentage of correct flavour discrimination responses for the lime (a), orange (b), strawberry (c), and flavourless (d) solutions presented in Zampini et al . ( [ 47 ] ; experiment 2). The error bars represent the between-participants standard errors of the means. These results clearly show the deleterious effect of adding the inappropriate food colour on participants’ flavour identification responses, at least for the lime- and orange-flavoured drinks. (Somewhat surprisingly, the addition of food colouring had little effect on the accuracy of participants’ flavour discrimination responses for the strawberry flavoured solution). Critical to the present discussion, increasing the intensity of food colouring had no effect on flavour identification, nor on judgments of flavour intensity. (Figure reprinted with permission from [ 47 ]).

To date, the majority of the research on the psychological influence of colour on judgments of taste/flavour intensity (not to mention flavour identity, see below) has been conducted with beverages. This is presumably because it is easier to manipulate the level of colour in solutions [ 33 ]. That said, intriguing research by Shermer and Levitan [ 48 ] has recently demonstrated that people also expect more intensely red-coloured salsas to be spicier (that is, more piquant). In fact, over the last 80 years or so, researchers have looked at the psychological impact of food colour on everything from noodles [ 49 ] through vegetables [ 50 ] and from cheese [ 51 ] through to yoghurt [ 34 , 52 ], not to mention cake [ 53 ], jams, jellies, chocolates, and sherbets [ 7 , 54 , 55 ].

One final point to note here is that it may be important to pay careful attention to the methodological details from the various studies of the psychological effect of colour on flavour intensity. The reason being that one study has obtained differing effects of food colour on orthonasal and retronasal judgments of a commercial fruit-flavoured water drink [ 56 ]. In particular, colouring a tangerine-pineapple-guava-flavoured solution red led to odour enhancement in those participants who sniffed the odour orthonasally, while giving rise to a reduction in perceived odour intensity when the same olfactory stimulus was presented retronasally instead.

Koza et al . [ 56 ] attempted to account for this surprising pattern of results by suggesting that it may be more important for us to correctly evaluate foods once they have entered our mouths, since that is when they pose a greater risk of poisoning us. By contrast, the threat of poisoning from foodstuffs located outside the mouth is obviously going to be less severe. Whatever the explanation for Koza et al .’s results turns out to be, the main point that these results highlight is that one cannot simply assume that colour’s effect on orthonasal olfactory judgments of a food or drink’s flavour will necessarily be the same when people come to actually taste it.

Interim summary

As the results reviewed in this section have made only too clear, the psychological effects of either adding or changing the intensity of food colouring on the intensity of taste/flavour perception are not altogether clear. Null results have been obtained by some researchers (for example, [ 44 , 57 ]). And even those who have obtained significant effects of colour on taste/flavour intensity ratings/perception have tended to do so only under a subset of experimental conditions or else in a subset of those individuals whom they have tested (for example, see [ 39 , 43 , 45 - 47 , 53 , 58 - 66 ]). As such, it is difficult to draw any overarching conclusions from the range of results that have been published to date as to when exactly the addition of food colouring will influence ratings of taste/flavour intensity. Clearly, the addition of food colouring can influence thresholds and ratings of stimulus intensity. However, when exactly such crossmodal effects will be observed is harder to predict with any confidence. d Indeed, one question left unresolved by much of the research that has been published to date in this area concerns why it is that these seemingly inconsistent results might have been obtained in the first place. According to Koza et al .’s [ 56 ] findings, part of the answer might relate to methodological details concerning whether olfactory stimuli are presented orthonasally or retronasally.

However, perhaps, one also needs to take a step back and consider what happens if the sensory expectations set by the intensity of food colouring fail to match up with the experience when a food or beverage item is actually tasted by the participant or consumer. In the real world, this might be expected to give rise to a negatively valenced disconfirmation of expectation response [ 21 , 31 , 32 ]. However, in much of the laboratory research published to date, there is a question as to whether the participants actually believed that the colours of the foods or drinks that they were tasting had any meaning - that is, to what extent did they really believe that the food colouring they saw was linked to the actual taste/flavour of the drinks that they were tasting? (One might also be tempted to wonder whether or not participants noticed any discrepancy between what they saw and what they tasted [ 67 ]). While such an assumption is presumably likely out there in the real world, it is not so clearly the case for those participants taking part in laboratory research where they may have been exposed to a whole series of inappropriately coloured samples to taste and evaluate over the course of their experimental session. What is more, the research varies between those studies in which the researchers have been very explicit about the fact that the colour cues were designed to be misleading [ 47 , 68 ], through to those who have done their utmost to hide the purpose of their study (and the potentially misleading nature of the colours) from their participants [ 69 ].

Flavour identity

Perhaps the most robustly demonstrated effect of adding (or changing) food colouring has been on people’s identification of the flavour of food or, more commonly, drink (see [ 33 ], for a review). Classic research by DuBose and his colleagues [ 53 ] demonstrated that the addition of food colouring (green, red, or orange) biased participants’ judgments concerning the identity of the flavour of a cherry-flavoured solution. So, for instance, nearly 20% of the participants in this study reported that the drink tasted of orange when the cherry-flavoured solution was coloured orange as compared to no such responses when the same drink was coloured red, green, or remained colourless. Meanwhile, colouring the same drink green led to 26% lime-flavoured responses as compared to no such responses when the drink was coloured red or orange (see also [ 10 , 70 , 71 ], for similar results).

Oram et al . [ 67 ] gave over 300 people (of various ages) four drinks to taste. Four possible drink flavours (chocolate, orange, pineapple, and strawberry) were presented in four different colours (brown, orange, yellow, and red), thus giving rise to a total of 16 possible drinks. The participants had to try and discriminate the flavour of the drinks. The results highlighted a clear developmental trend toward an increased ability to correctly report the flavour of the drinks, regardless of the colour in which the drink was presented (see Figure  2 ). That is, the crossmodal modulation of flavour perception by vision apparently decreased with age (from 2 years of age up).

Graph highlighting the percentage of trials in which the participants’ flavour discrimination response matched the colour of the drink, the actual flavour of the drink, or matched neither the colour or flavour of the drink as a function of the age of the participants in a developmental study of the psychological impact of colour on people’s flavour discrimination responses reported by Oram et al . [ 67 ] . [Reprinted from [ 67 ], with permission].

Importantly, in this and the majority of the other studies that have been reported so far, the participants were given no information about the possibility that the colour of the solutions might have been misleading (a point to which we will return later). Research by Zampini et al . [ 47 , 68 ] has shown that adults can easily be confused by the addition of inappropriate colour to a range of fruit-flavoured soft drinks (see Figure  3 ). Importantly, the crossmodal effects of beverage colour on flavour identification demonstrated by Zampini et al . were obtained under those conditions where the participants had been told to ignore the potentially misleading colouring of the beverages that they had been presented with. Such results therefore hint at the automaticity of such crossmodal effects.

Summary of the results of Zampini et al .’s [ 68 ] study highlighting the influence of colour on people’s ability to correctly identify orange- and blackcurrant-flavoured solutions. [Figure reprinted with permission from [ 18 ].

The majority of the research that has been published to date has convincingly demonstrated that food colour affects the ability of people to correctly identify the flavour of food and drink (see Spence et al . [ 18 ], for a comprehensive review of the literature on this question). Although beyond the scope of this review, it is perhaps also worth noting that food colouring can influence the perceived thirst-quenching (or refreshing) properties of drinks as well [ 41 , 72 - 74 ]. That said, I would argue that there is a danger that one can get a biased impression of just how important colour is to the consumer’s perception of, and response to, food and drink. This is because in the majority of laboratory studies, the colour of the foodstuff was pretty much the only cue, sensory or otherwise, that the participants had to go on when making their decisions as to the taste/flavour of that which they were tasting. In the real world (see below), the consumer normally has a number of other cues to utilize when trying to judge the likely sensory and hedonic qualities of food and drink. What is more, there is always a danger that being confronted with a whole range of drinks, say, similar in flavour and differing most noticeably in terms of their colouring may have drawn, or focused, the participants’ attention on colour as the most salient dimension (that is, in a way that may not be representative of everyday life).

One other thing to note here is that food colours are not necessarily associated with just one taste/flavour. As shown by Zampini et al . [ 47 ], for example, a red-coloured drink may be most strongly associated with the flavour of strawberry, but also, to a lesser degree with the flavour of raspberry and cherry. Hence, if one really wants to understand/predict its effect on multisensory flavour perception, it is important to bear in mind that a given beverage colour may actually prime a number of different possible flavours [ 75 - 78 ]. What is more, similar food colours may give rise to qualitatively different flavour expectations depending on the category of product under consideration (for example, soft drinks, cake, noodles, curry, and so on) and possibly also the brand (cf. [ 79 ]). As such, there is clearly a need for more research addressing the influence of food colour across different kinds of food product (and as a function of branding) in order to get a more complete, not to mention market-relevant, understanding of the psychological effect of food colour.

Names, brands, and colours

Given the ambiguity in the meaning of colour in foods and beverages, it can sometimes be important that the name and description of a food or beverage set the right sensory or hedonic expectations or else help to disambiguate between the different possible meanings that may be associated with a given colour. The classic example here comes from the work of Yeomans and colleagues [ 80 ]. These researchers demonstrated that when the meaning of food colouring is misinterpreted (that is, when it sets the wrong sensory expectations), then this can have an adverse effect on people’s subsequent taste ratings. The participants in this study were given a bright pink ice cream to taste. One group of participants was given no information about the dish, another group was informed that the food was called ‘Food 386’, and a third group was told that what they were about to eat was a frozen savoury mousse. Those participants who had not been given any information about the dish and hence who were led by their eyes into expecting that they would taste a strawberry-flavoured ice cream (which has the same pinkish-red colour) did not like the dish when they tried it. Specifically, they rated the frozen savoury smoked salmon ice cream as tasting too salty. By contrast, those participants in the other two groups rated the seasoning of the dish as being just right, and, what is more, liked the savoury ice far more as well (see [ 81 - 83 ], for related research). These results therefore demonstrate that the meaning of colour in food and drink can be altered simply by the description that is given to a product or dish [ 1 ]. Generally speaking (that is, in all environments excepting perhaps the modernist restaurant), it is important to avoid disconfirmed expectation [ 1 , 84 ].

Indeed, the typical laboratory situation can be contrasted that with that of everyday consumption episodes where a food or drink will most likely be encountered in the context of branding/packaging information, or may well have been described by whoever has prepared, or is serving the food or drink. In other words, it can be argued that the situation that is typically studied in the laboratory setting is quite unlike that of everyday life (see also [ 85 - 87 ]). Hence, one concern here is that the results of much of the research that has been conducted in the laboratory may actually end up giving a biased view of the importance of colour in multisensory flavour perception. Note that in the laboratory situation, colour is often the only cue that participants have to go on when making their judgments of expected flavour. By contrast, in the majority of real-world consumption situations, colour is but one of many cues (including branding, pricing, labelling, and so on) that the consumer can use.

One other product-extrinsic cue that can modulate the meaning of colour in beverages is the nature of the glass or receptacle in which that drink happens to be presented [ 88 , 89 ]. The same colour drink may have a very different meaning if shown in a plastic bathroom cup than in a cocktail glass, say. In the former case, a blue-coloured drink is likely to be interpreted as connoting mouthwash and hence associated with a mint flavour, whereas when exactly the same colour is seen in a cocktail glass, it may be interpreted as signifying the orange flavour of blue curaçao instead [ 90 ].

Psychological effects of food colour on behaviour

It is important to realize that the psychological effects of food colouring are not restricted to the sensory-discriminative domain. It has often been suggested that food colouring can modulate certain of our food-related behaviours as well [ 91 , 92 ]. Certainly, getting the colour right can play an important role in food acceptance, liking, and hence, ultimately, food intake [ 24 , 93 - 97 ]. Though, as pointed out by Garber et al . [ 85 ], while it is often claimed that colour influences food preferences, good, marketing-relevant insights tend to be a little harder to come by in this area.

Colour can play an important role in modulating a consumer’s affective expectations [ 32 , 98 ]. And just as there can be a sensory disconfirmation of expectation (as outlined above), there can also be a hedonic disconfirmation of expectation - that is, when a consumer realizes that they do not like a food or beverage as much as they were expecting that they would.

In other research, it has been shown that people will consume more candy if it comes in a variety of colours than if presented in just a single colour [ 99 ], even if that colour happens to be the consumer’s favourite one. Whether sensory-specific satiety or boredom is the most appropriate explanation for such results is still being deliberated by researchers (see [ 92 ], for a review). Interestingly, while the use of colour (specifically increasing colour variety) is usually portrayed as a means by which the big food companies can get their consumers to consume more (think only of the multicoloured packs of Smarties, M&Ms, or Jelly Beans), there is some evidence to suggest that colour cues can also be used to modulate intake downward, by providing an effective cue to portion control ([ 100 ] see also [ 101 , 102 ]). So, for example, Geier et al . [ 100 ] reported that people ended up eating fewer potato chips if every seventh chip in a tube happened to be coloured red.

Off-colouring in food

Researchers have been interested in the response of consumers to food colouring that they associate with products that have been in some way spoiled. That such off-colours can have a profound effect on people’s food behaviours was suggested by the response of consumers to a batch of Tropicana grapefruit juice that was donated to a food bank some decades ago. According to Crumpacker ([ 14 ], p. 6), nobody wanted to drink the juice because of its abnormal brown colour. This despite the fact that those who tried it reported it to taste perfectly acceptable; see also [ 59 , 81 , 103 ], on the preferred colour of this staple of the breakfast table.

Meanwhile, the dinner party guests in Wheatley’s [ 15 ] classic study were invited to dine on a meal of steak, chips, and peas. The only thing that may have struck any of the diners as odd was how dim the lighting was. However, this aspect of the atmosphere was actually designed to help hide the food’s true colour. Part-way through the meal, the lighting was returned to normal, revealing that the steak had been artificially coloured blue, the chips looked green, and the peas had been coloured red. A number of Wheatley’s guests suddenly felt ill when the lighting was turned to normal levels, with several of them apparently heading straight for the bathroom (cf. [ 54 ]). e

It is noticeable how the majority of the research on the psychological impact of off-colour in food is rather anecdotal in nature (presumably because it can be difficult to get ethical approval to present food to participants and have them believe that the colour indicates that it has gone off). Nevertheless, the evidence that has been published to date does seem to highlight the strong avoidance responses that such food colouring can induce, especially in the case of meats and fish that look off. f

Artificial/natural

Over the years, there has been ongoing concerns expressed about the negative health and well-being consequences that are apparently associated with the consumption of certain artificial food colourings, this despite their being rated as being safe and tasteless [ 24 , 104 - 116 ]. This had led some consumers to search out those foods that are free from all colouring. However, such products generally do not taste that good. As Harris pointed out in an article that appeared in The New York Times [ 24 ], many commercial foods are disappointingly lacking in taste/flavour if served in a colourless (that is, clear or white) format.

A less extreme reaction to concerns over artificial food colourings has been to search out natural colourings that better match the sensory properties desired by the food producers: This includes everything from trying to deliver a wide enough range of natural colours [ 117 ], through to improving the stability of natural colourings, at least for those products that are likely to have a long shelf life [ 118 - 120 ]. Of course, that food colouring is natural does not in-and-of-itself necessarily make it appealing to the consumer. Here, one only needs to think of the red colouring of, for example, Smarties (the candy-covered chocolate; http://www.nestle.co.uk/brands/chocolate_and_confectionery/chocolate/smarties ) that used to be made from carminic acid extracted from scaly insects. Unappealing to most consumers, one imagines. Nowadays, though, the red colouring comes from red cabbage instead [ 116 ].

And what, exactly, constitutes natural is not obvious. The vibrant orange-coloured carrots that we are all familiar with nowadays, for example, are actually the result of extensive breeding. Once upon a time, the majority of carrots were naturally purple. According to some, the selective breeding was designed to deliver the orange colour of the Dutch royal family in the seventeenth century [ 121 - 123 ]. Although another, perhaps more plausible, explanation for why the orange variety may have been preferred over the original purple variety was because the latter would colour the soups, stews, and so on into which they were placed.

A number of the modernist chefs we have been fortunate enough to work with here at the Crossmodal Research Laboratory at Oxford University over the years have been particularly interested in surprising their diners by presenting foods that have one colour (and hence set a particular taste/flavour expectation) while actually delivering another unexpected flavour instead. g However, the chefs typically do not want to achieve such results by means of artificial food colourings for fear of their diners’ reaction.

One elegant example of the use of natural colouring to create surprise and delight in the mind of the diner comes from the beetroot and orange jelly dish that used to be served as one of the opening courses on the menu at The Fat Duck restaurant in Bray ( http://www.thefatduck.co.uk/ ). This dish would be presented as two blocks of jelly, one bright orange, the other a dark purple, placed side-by-side on the plate. And where the modernist chefs lead, the market sometimes follows. Pine berries, for example, which look for all-the-world like white strawberries provide an intriguing example of an otherworldly, at least to Western eyes, but entirely naturally coloured food. h Such unusually coloured food products have apparently been selling well in the supermarkets in recent years (see also [ 123 ]). More generally, there would appear to be renewed interest in surprisingly coloured foods in the mass market as well. For example, a few years ago, one well-known burger chain launched a pitch black bamboo and squid ink burger in Japan, that was seasoned with black squid ink ketchup, and served in a black bun [ 124 ]. As a group, children seem to be particularly fond of such miscoloured foods (think confused Skittles; http://www.wrigley.com/uk/brands/skittles.aspx ) and beverages [ 125 - 128 ].

Marketing colour

Adding colour to food or else changing the colour of a food or beverage (or its packaging) has long been used as a marketing tool (for example, [ 129 - 133 ]; see also http://www.ddwcolor.com/hue/why-color/ ). In fact, according to an informal store audit reported by Garber et al . [ 85 ], 97% of all food brands displayed (in all categories) used food colour to indicate flavour. Food colour is used in marketing for a number of reasons: Everything from increasing shelf stand-out through to blurring the distinction between different products. Indeed, going back three quarters of a century now, there was quite a fight by the butter lobby in order to try and prevent the makers of margarine from adding a golden yellow hue to their product in order to give it the appearance of its better established rival (for example, see [ 134 ]).

More recently, the potential role of adding food colouring in marketing was amply demonstrated by the dramatic rise in sales of tomato ketchup when Heinz decided to add a tiny amount of food colouring and turn this staple of the dining table green [ 135 ]. Other large drink brands that have, in recent years, launched drinks in unusual colours include an amber-coloured cola, called Pepsi Gold, in India [ 133 ]. However, not every attempt by marketers to use colour to boost sales has been successful. Clear cola drinks, for example, have generally failed in the marketplace [ 136 ]. And while there are a number of theories out there in the marketing literature about what went wrong in such cases, one suggestion is that when such drinks were tasted away from their packaging then the likely disconfirmation of expectation that results from experiencing a cola flavour when the sight of the drink led the consumer to expect lemonade or soda water may have been especially problematic. i

Individual differences in the psychological effects of colour

One thing that is noticeable about much of the early research on the psychological effects of food colouring is how little attention was paid by researchers to the profiles of the participants themselves. This turns out to be an important caveat since the latest research now shows that exactly the same food colour can elicit qualitatively different expectations concerning the likely taste/flavour of food and drink in different groups of consumers.

Cross-cultural differences

Exactly the same colour (for example, in a beverage) has been shown to set up qualitatively different expectations in the minds of different (groups of) consumers. Just take the two drinks shown in Figure  4 : When they were shown to young adults in Taiwan and the UK, the former expected them to taste of cranberry and mint (mouthwash?), respectively, whereas the latter expected cherry/strawberry and raspberry, instead [ 75 ]. Wan et al . [ 88 , 89 ] have recently been conducting a number of internet-based studies designed to assess which food colours have a similar meaning in terms of expected flavour across culture and which differ markedly in terms of the expectations that they set. Food marketers working in the global marketplace obviously need to be aware of any cultural differences in the meaning of food colour [ 133 ]. Here, though, one potential limitation with the internet-based testing of consumers’ colour expectations ought to be noted: Namely, it is difficult to precisely control the appearance properties of the visual stimuli on an individual participant’s monitor. By contrast, in Shankar et al .’s [ 75 ] study, the participants actually viewed the drinks.

Two of the six coloured drinks shown to the participants from the UK and Taiwan in a study by Shankar et al . [ 75 ]. The results of this cross-cultural study demonstrated that exactly the physically same food colour can elicit qualitatively sensory different expectations as far as the likely flavour of a drink might be in consumers from different countries. The most frequently expected flavours for drinks of these colours are shown at the bottom.

Developmental differences

Developmental differences in the meaning, and influence, of food colour have been reported by researchers. As noted earlier, young children seem to be more drawn to brightly (some would say artificially) coloured foods than are adults (though see [ 90 ]). In terms of changes in the psychological influence of food colouring across the lifespan, on the basis of the evidence that has been published to date [ 45 , 67 , 137 ], it would appear that, if anything, visual cues exert a somewhat greater influence on flavour identification early in development (see Figure  2 ), and in old age, than in adulthood (see [ 138 ], for a review). One reason as to why children might show more visual dominance (that is, simply relying on what they see) is because they have not yet learned to integrate their senses in an adult-like manner (cf. [ 139 ]). Thus far, published studies have assessed the responses of children from 2 years of age upward.

At the other end of the spectrum, the well-documented decline of taste and smell sensitivity in old age may mean that the residual senses (especially those where prostheses, such as glasses or hearing aids, are available) take on a more important role in terms of determining the final taste/flavour experience [ 3 , 137 ]. However, it has to be said that the evidence that has been published on this topic to date is rather mixed (see [ 138 ], for a review). While some researchers have been able to demonstrate more pronounced psychological effects of food colouring in, say, older adults [ 45 , 103 ], such differences have certainly not always been found.

Here, it is perhaps also worth bearing in mind that there may be changes in the meaning and acceptability of colour over time. One only needs to remember, for example, that blue foods were traditionally considered unacceptable to a majority of consumers [ 140 , 141 ]. Nowadays, many foods are blue [ 133 ], although in this case, note that they are primarily marketed at the younger consumer [ 85 ]. Over a much longer timescale, one could even think of how the flavour of carrots may have switched its colour association from purple to orange (see above).

Expertise and the psychological effects of food colouring

Expertise has been shown to modulate the psychological impact of food colouring on flavour perception. Some of the most impressive studies have come from the world of wine (see [ 142 ], for early research; and [ 143 ], for a review). In one oft-cited experiment, Morrot and his colleagues [ 144 ] reported that a group of students on a university wine course in Bordeaux, France, had been fooled into choosing red wine aroma descriptors when given a white wine to evaluate that had been artificially coloured red with odourless food dye. Meanwhile, Parr et al . [ 145 ] conducted a follow-up in New Zealand in which they tested both experts (including professional wine taster and wine makers) and ‘social’ drinkers. The descriptions of the aroma of a Chardonnay wine given by the experts when it had been artificially coloured red were more accurate when the wine was served in an opaque glass than when served in a clear glass. Interestingly, this colour-induced biasing of flavour judgments occurred despite the fact that the experts had been explicitly instructed to rate each of the wines that they had been given to taste while ignoring any colour cues. Such results therefore suggest that the crossmodal effect of vision is not under cognitive control. Ironically, the social drinkers in Parr et al .’s study turned out to be so bad at reliably identifying the aromas present in the wine that it was difficult to discern any pattern in the data when an inappropriate wine colour was added.

Taken together, therefore, the evidence that has been published to date is consistent with the view that expert wine tasters differ from social drinkers (that is, non-experts) in the degree to which visual (colour) cues influence their orthonasal perception of flavour [ 145 ] and their perception of the taste of sweetness ([ 142 ]; see also [ 84 ]). That said, it is worth noting that not all food/flavour experts necessarily exhibit the same increased responsiveness to colour cues when evaluating the taste and flavour of food and drink. Shankar et al . [ 78 ], for example, reported that the flavour experts working on a descriptive panel at an international flavour house (who all had more than 3 years of experience flavour profiling food and drink products) exhibited just as much visual capture (or assimilation) of their orthonasal olfactory flavour judgments as did non-experts. Thus, based on the research that has been published to date, the most appropriate conclusion regarding flavour experts would appear to be that while some (specifically those with an expertise in wine) show an enhanced susceptibility to the crossmodal influence of colour on judgments within their area of expertise [ 142 , 145 ], this pattern of results does not necessarily extend to other groups of flavour experts [ 78 ].

Genetic differences in the effect of colour

Although surprisingly little studied to date, various genetic differences might also modulate the psychological effect of food colouring. Here, for example, one might think both of those individuals who are born colour blind (primarily males and constituting approximately 6% of the population; [ 146 ]). Presumably such differences in colour perception ought to have some impact of the psychological effect of food colour, though it is hard to find any published research on the topic (see http://www.colourblindawareness.org/colour-blindness/living-with-colour-vision-deficiency/food/ ). Here, it is also worth noting that there are several discrete kinds of colour blindness, each likely affecting the perception of food and beverage colour in a slightly different way.

However, just as important as any deficits in colour perception, may be an individual’s taster status. It turns out that genetic differences here may play an important role in determining just how much of a role colour plays in flavour perception. Some people have far more taste buds than others (the former are known as supertasters, the latter, non-tasters; with 25% of the population falling into each category). The remaining half of consumers fall into an intermediate group, known as medium tasters [ 147 ]. To give some idea of the differences in receptor density that might be involved here, it has been estimated that some individuals may have up to 14 times more taste buds than others [ 148 ]. Zampini et al . [ 68 ] have reported that supertasters are significantly less affected by the colour of a drink than medium tasters, who, in turn, are less affected than non-tasters (see Figure  5 ). It is somewhat surprising to find that this is the only study of the psychological impact of food colour to have assessed the taster status of their participants. j One can, perhaps, frame this result in terms of the literature on sensory dominance. That is, those individuals with a greater number of taste buds presumably exhibit lower variance in terms of their unisensory gustatory judgments. According to the maximum likelihood account of multisensory integration [ 149 ], the perceptual estimate with the lower variance will likely be weighted more heavily when it comes to estimating a given stimulus attribute.

Mean percentage of correct flavour identification responses for the three groups of participants (non-tasters, medium tasters, and supertasters) for the blackcurrant, orange, and flavourless solutions. The black columns represent solutions where fruit acids had been added and the white columns solutions without fruit acids. The error bars represent the between-participants standard errors of the means. The results highlight the fact that genetic differences in taster status may determine just how much of a psychological effect colour cues can have on flavour identification. (Figure reprinted with permission from [ 68 ]).

One cannot hope to attain a comprehensive understanding of the psychological impact of food colour without taking into account the individual differences. The relevant differences include genetic differences in terms of taster status and colour perception, as well as cross-cultural and age-related differences. Although beyond the scope of this article, there may be racial differences in terms of colour preferences as well [ 150 ]. What is clear from the research that has been published to date is that these individual differences can influence both the meaning of colour and its influence on the consumer. Having established the importance of such individual differences (of both genetic and experiential origin), the question becomes one of how to assess the psychological impact of food colour experimentally. One solution here has been proposed in the work of Shankar and her colleagues [ 76 - 78 ].

According to Shankar et al . [ 77 ], assessing the ‘degree of discrepancy’ between the expected flavour set by colour and the flavour when eventually experienced by the participant (or consumer) is key to understanding when colour influences flavour perception. Shankar et al . argued that under conditions of low discrepancy, the perceived disparity between the expected and actual flavour of a drink (or food) is small. Low discrepancy colour-flavour combinations might, for example, consist of cranberry- or blueberry-flavoured drinks coloured purple (purple being associated with grape flavour), whereas high discrepancy combinations might include banana- or vanilla-flavoured drinks that have been coloured purple. Across several experiments, when a particular colour - identified by participants as one that generated a strong flavour expectation - was added to the drinks that the participants were given to sniff (as compared with when no such colour was added), a significantly greater proportion of their identification responses were consistent with this expectation. k By contrast, under conditions of high discrepancy, adding the same colours to the drinks no longer affected participants’ identification responses in the same way (see Figure  6 ). That is, there was a significant difference in the proportion of responses that were consistent with participants’ colour-based expectations in conditions of low as compared with high discrepancy. Shankar et al .’s results therefore demonstrate that the degree of discrepancy between an individual’s expectation concerning the flavour (derived visually) and their actual experience on tasting the drink modulates the crossmodal influence of colour cues on judgments of flavour identity.

Summary results from two of the experiments (conducted with the same participants) reported by Shankar et al . [ 77 ] showing how the addition of food colouri ng to an otherwise colourless flavoured solution led to assimilation when the ‘degree of discrepancy’ between the flavour expected by the colour and the actual flavour of the drink when sniffed orthonasally was low, but not when the degree of discrepancy was high. (Figures reprinted with permission from [ 77 ]).

One thing to bear in mind about Shankar et al .’s [ 76 - 78 ] studies, though, is that the participants never got to taste the flavoured drinks that they were asked to judge. That is, all their judgments/ratings were made on the basis of nothing more that orthonasal olfactory cues. Of course, this should not matter all that much, given the extensive literature showing that colour cues can modulate orthonasal olfactory discrimination/identification responses across a wide range of experimental conditions ([ 151 - 158 ]; see [ 159 ], for a review). l

Bottom-up or top-down influences of colour

Now, one further question that can, and probably should, be asked before closing concerns whether colour should be considered as exerting its psychological influence over flavour perception in more of a ‘bottom-up’ or more of a ‘top-down’ manner. On the one hand, it is clear that when people know that the colour they see is inappropriate (misleading) and so should be ignored, it nevertheless still influences their perception in a seemingly automatic manner [ 47 , 68 , 145 ]. Such results support a bottom-up account of at least part of colour’s crossmodal influence over taste and flavour perception. Of course, the existence of such bottom-up effects should not be taken as evidence to deny the fact that top-down influences are also important.

Indeed, colour certainly also influence people’s flavour perception in more of a top-down manner as well. Here, it is relevant to note that researchers have demonstrated that labelling, branding, and other descriptive information can all modify the meaning of a given food colour and by so doing influence the perceived taste of a food or beverage [ 1 ]. So, for instance, Shankar et al . [ 83 ] reported that, even when blindfolded, telling a participant that a sugar-coated chocolate candy has a particular colour (or that it is light or dark chocolate) influenced the pattern of responding that was observed. In a similar manner, a variety of non-sensory (labelling) cues have also been shown to bias the way in which a normally sighted observer interprets the meaning of a given colour (as in Yeomans et al .’s, [ 80 ], study). Taken together, then, there is good evidence that colour’s psychological influence on taste and flavour perception occurs not only in a bottom-up but also in more of a top-down manner as well. Studying the interaction between these influences on flavour perception is an area of growing interest from both a theoretical and more marketing-inspired perspective [ 42 , 76 , 82 ]. A related challenge comes from trying to integrate the growing literature demonstrating the influence of everything from the colour of the product packaging [ 160 ] through to the colour of the lighting [ 161 , 162 ] in which food and drink are consumed on the multisensory flavour experience [ 1 ].

Conclusions

Since the first reports that changing the colour of a food could change the taste/flavour were published [ 54 , 55 ], somewhere in the region of 150 papers have investigated the impact of food colouring on the perception and behaviour of participants/consumers. While the majority of those studies have tended to focus on colour’s effect on taste/flavour identification (see [ 18 ], for a review), it is important to note that colour cues influence our food and drink-related behaviour in a number of different ways [ 1 , 92 , 125 , 163 ]. Food colouring undoubtedly plays an important role in driving liking and the consumer acceptability of a variety of food and beverage products. And while increasing colour variety in food can lead to enhanced consumption [ 92 ], what we see can also lead to a suppression of our appetitive behaviours when associated with off-colours (or coloration that is interpreted by the consumer as such).

Finally, given the practical difficulties associated with delivering flavours while a participant lies in the brain scanner [ 1 ], it is perhaps understandable that there has not been a great deal of neuroimaging research that has looked at the influence of colour on flavour perception as yet ([ 164 ]; see also [ 165 ]). Whether or not as the result of further neuroimaging, it is clear that additional research is most definitely needed in order to develop a better understanding of the psychological mechanisms underlying the various effects of colour on our perception of, and behaviours toward, food [ 166 ].

Certainly, the expectations, both sensory and hedonic, that are set by food colouring play an important role in determining the final flavour experience and how much it is liked. Furthermore, the degree of discrepancy between the sensory and hedonic expectations and the subsequent experience appears crucial to the question of whether assimilation or contrast will be observed. Here, recent research has increasingly demonstrated the differing meanings associated with food colour in different consumers. Identifying consistent colour-flavour mappings and training the consumer to internalize other new associations is one of the important challenges facing the food marketer interested in launching new products, or brand extensions, in a marketplace that is more colourful than ever.

a While the term ‘product-intrinsic’ is widely used in the literature when talking about the colour of a food or beverage, the appropriateness of this notion can be questioned from the perspective of (holistic) perception. Strictly speaking, colour is not a property of a (food) material but rather a percept in an observer that originates from an interaction with a material, under the influence of many other cues that are external to the coloured surface, but certainly internal to, the observer (for example, [ 167 ], p. 5).

b Here, it is perhaps worth noting that intense food colouring, while seemingly attractive to children (see [ 138 ], for a review), may lead some consumers to consider a food or beverage product as being ‘artificial’ and hence less liked (for example, [ 45 , 46 ]).

c Note that the participants in this study only ever had to report whether or not the solution had a taste. That is, they never had to identify the tastant. In fact, somewhat surprisingly, the question of whether colour influences the ability of people to identify / discriminate the basic tastes has not, as far as I am aware, been studied to date (see [ 18 ], for a review). This despite the fact that extensive evidence has been collected concerning the colours that people in different cultures associate with each of the basic tastes (see [ 40 ], for a review and cross-cultural evidence).

d Note that a lack of precise colour measurement has hampered comparison of the results of many of the studies that have been published to date (cf. [ 4 , 168 ]).

e No mention is made of whether ethical approval was obtained for this particular study!

f Though note that olfactory cues are at least as important in people’s judgment of whether a food has gone off ([ 169 ]; see also [ 170 ] on the consumer evaluation of the sensory properties of fish).

g Note that while under the majority of everyday conditions, people prefer foods and beverages that taste as they expect them to taste (that is, people do not like surprises, especially when it comes to the stimuli that enter the mouth, and hence have the potential to poison them), there are occasions, such as at the tables of the modernist restaurant where many diners seem to positively relish having their expectations played with [ 1 , 125 ].

h These ‘white strawberries’ are the result of cross-breeding the South American strawberry Frag aria chiloensis , which grows wild in some parts of Chile, and the North American strawberry Fragaria virginiana.

i Of course, here, it needs to be remembered that changing the colour of a drink can change its flavour perceptually. However, one has to imagine that any such crossmodal perceptual effects would have been picked up in consumer tests before the product was launched.

j Indeed, given the relatively small sample size and the post hoc nature of Zampini et al .’s [ 68 ] discovery, replication in a larger sample would undoubtedly be desirable to check on the generalizability of this potentially important result.

k Here, it is worth pointing out that when flavour experts were tested, their results were similar to those of normal participants [ 78 ].

l That said, Koza et al .’s [ 56 ] results concerning the differing effect of colour on orthonasal and retronasal olfactory intensity judgments needs to be borne in mind here.

Spence C, Piqueras-Fiszman B. The perfect meal: the multisensory science of food and dining. Oxford: Wiley-Blackwell; 2014.

Google Scholar  

Cardello AV. The role of the human senses in food acceptance. In: Meiselman HL, MacFie HJH, editors. Food choice, acceptance and consumption. New York, NY: Blackie Academic and Professional; 1996. p. 1–82.

Clydesdale FM. The influence of colour on sensory perception and food choices. In: Walford J, editor. Developments in food colours–2. London, UK: Elsevier Applied Science; 1984. p. 75–112.

Clydesdale FM. Color perception and food quality. J Food Qual. 1991;14:61–74.

Clydesdale FM. Color as a factor in food choice. Crit Rev Food Sci Nutrit. 1993;33:83–101.

CAS   Google Scholar  

Delwiche JF. You eat with your eyes first. Physiol Behav. 2012;107:502–4.

CAS   PubMed   Google Scholar  

Hall RL. Flavor study approaches at McCormick and Company, Inc. In: In AD Little, Inc, editor. Flavor research and food acceptance: A survey of the scope of flavor and associated research, compiled from papers presented in a series of symposia given in 1956–1957. New York, NY: Reinhold; 1958. p. 224–240).

Kanig JL. Mental impact of colors in foods studied. Food Field Reporter. 1955;23:57.

Kostyla AS, Clydesdale FM. The psychophysical relationships between color and flavor. CRC Critic Rev Food Sci Nutrit. 1978;10:303–19.

Watson E: We eat with our eyes: flavor perception strongly influenced by food color, says DDW. Downloaded from http://www.foodnavigator-usa.com/Science/We-eat-with-our-eyes-Flavor-perception-strongly-influenced-by-food-color-says-DDW on 19/12/2014.

Downham A, Collins P. Colouring our foods in the last and next millennium. Int J Food Sci Technol. 2000;35:5–22.

Tannahill R. Food in history. New York, NY: Stein and Day; 1973.

Walford J. Historical development of food coloration. In: Walford J, editor. Developments in food colours. London: Applied Science; 1980.

Crumpacker B. The sex life of food: when body and soul meet to eat. New York, NY: Thomas Dunne Books; 2006.

Wheatley J: Putting colour into marketing. Marketing 1973, October:24–29, 67.

Rozin P. “Taste-smell confusions” and the duality of the olfactory sense. Percept Psychophys. 1982;31:397–401.

Spence C, Smith B, Auvray M. Confusing tastes and flavours. In: Stokes D, Matthen M, Biggs S, editors. Perception and its modalities. Oxford: Oxford University Press; 2015. p. 247–74.

Spence C, Levitan C, Shankar MU, Zampini M. Does food color influence taste and flavor perception in humans? Chemosens Percept. 2010;3:68–84.

Deliza R, MacFie HJH. The generation of sensory expectation by external cues and its effect on sensory perception and hedonic ratings: a review. J Sens Stud. 1997;2:103–28.

Hutchings JB. Expectations and the food industry: the impact of color and appearance. New York, NY: Plenum Publishers; 2003.

Piqueras-Fizman B, Spence C. Sensory expectations based on product-extrinsic food cues: an interdisciplinary review of the empirical evidence and theoretical accounts. Food Qual Prefer. 2015;40:165–79.

Spence C. Eating with our ears: assessing the importance of the sounds of consumption to our perception and enjoyment of multisensory flavour experiences. Flavour. 2015;4:3.

Cardello AV. Consumer expectations and their role in food acceptance. In: MacFie HJH, Thomson DMH, editors. Measurement of food preferences. London, UK: Blackie Academic & Professional; 1994. p. 253–97.

Harris G: Colorless food? We blanch. The New York Times 2011, April 3:3. Downloaded from http://www.nytimes.com/2011/04/03/weekinreview/03harris.html?_r=0 on 21/12/2014.

Murakoshi T, Masuda T, Utsumi K, Tsubota K, Wada Y. Glossiness and perishable food quality: visual freshness judgment of fish eyes based on luminance distribution. PLoS One. 2013;8(3):e58994.

PubMed Central   CAS   PubMed   Google Scholar  

Péneau S, Brockhoff PB, Escher F, Nuessli J. A comprehensive approach to evaluate the freshness of strawberries and carrots. Postharvest Biol Technol. 2007;45:20–9.

Prinz JF, & de Wijk RA: Effects of flavor and visual texture on ingested volume. Poster presented at the 5th Meeting of the International Multisensory Research Forum. 2-5th June, Sitges, Spain; 2004.

Okajima K, & Spence C: Effects of visual food texture on taste perception. i-Perception 2011, 2(8), http://i-perception.perceptionweb.com/journal/I/article/ic966 .

Lawless HT, Klein BP. Sensory science theory and applications in foods. New York, NY: Marcel Dekker; 1991.

Carlsmith JM, Aronson E. Some hedonic consequences of the confirmation and disconfirmation of expectancies. J Abnormal Social Psychol. 1963;66:151–6.

Schifferstein HNJ. Effects of product beliefs on product perception and liking. In: Frewer L, Risvik E, Schifferstein H, editors. Food, people and society: A European perspective of consumers’ food choices. Berlin: Springer Verlag; 2001. p. 73.

Zellner D, Strickhouser D, Tornow C. Disconfirmed hedonic expectations produce perceptual contrast, not assimilation. Am J Psychol. 2004;117:363–87.

PubMed   Google Scholar  

Spence C: Visual contributions to taste and flavour perception. In M. Scotter (Ed.), Colour additives for food and beverages. Cambridge, UK: Woodhead Publishing; in press.

Calvo C, Salvador A, Fiszman S. Influence of colour intensity on the perception of colour and sweetness in various fruit-flavoured yoghurts. European Food Res Technol. 2001;213:99–103.

Johnson J, Clydesdale FM. Perceived sweetness and redness in colored sucrose solutions. J Food Sci. 1982;47:747–52.

Johnson JL, Dzendolet E, Damon R, Sawyer M, Clydesdale FM. Psychophysical relationships between perceived sweetness and color in cherry-flavored beverages. J Food Protect. 1982;45:601–6.

Johnson JL, Dzendolet E, Clydesdale FM. Psychophysical relationships between perceived sweetness and redness in strawberry-flavored beverages. J Food Protect. 1983;46:21–5. 28.

Norton WE, Johnson FN. The influence of intensity of colour on perceived flavour characteristics. Medical Sci Res. 1987;15:329–30.

Maga JA. Influence of color on taste thresholds. Chem Senses Flavor. 1974;1:115–9.

Wan X, Woods AT, van den Bosch J, Mckenzie KJ, Velasco C, Spence C. Cross-cultural differences in crossmodal correspondences between tastes and visual features. Frontiers Psychol: Cognit. 2014;5:1365.

Clydesdale FM, Gover R, Philipsen DH, Fugardi C. The effect of color on thirst quenching, sweetness, acceptability and flavor intensity in fruit punch flavored beverages. J Food Qual. 1992;15:19–38.

Levitan C, Zampini M, Li R, Spence C. Assessing the role of color cues and people’s beliefs about color-flavor associations on the discrimination of the flavor of sugar-coated chocolates. Chem Senses. 2008;33:415–23.

Lavin JG, Lawless HT. Effects of color and odor on judgments of sweetness among children and adults. Food Qual Prefer. 1998;9:283–9.

Alley RL, Alley TR. The influence of physical state and color on perceived sweetness. J Psychol. 1998;132:561–8.

Philipsen DH, Clydesdale FM, Griffin RW, Stern P. Consumer age affects response to sensory characteristics of a cherry flavored beverage. J Food Sci. 1995;60:364–8.

Chan MM, Kane-Martinelli C. The effect of color on perceived flavor intensity and acceptance of foods by young adults and elderly adults. J Am Dietetic Assoc. 1997;97:657–9.

Zampini M, Sanabria D, Phillips N, Spence C. The multisensory perception of flavor: assessing the influence of color cues on flavor discrimination responses. Food Qual Prefer. 2007;18:975–84.

Shermer DZ, Levitan CA. Red hot: the crossmodal effect of color intensity on piquancy. Multisensory Res. 2014;27:207–23.

Zhou X, Wan X, Mu B, Du D, & Spence C: Examining colour-receptacle-flavour interactions for Asian noodles. Food Qual Prefer in press.

Urbányi G. Investigation into the interaction of different properties in the course of sensory evaluation. I. The effect of colour upon the evaluation of taste in fruit and vegetable products. Acta Aliment. 1982;11:233–43.

Wadhwani R, McMahon DJ. Color of low-fat cheese influences flavor perception and consumer liking. J Dairy Science. 2012;95:2336–46.

Dolnick E: Fish or foul? The New York Times 2008, September 2, downloaded from http://www.nytimes.com/2008/09/02/opinion/02dolnick.html?_r=1&scp=1&sq=chocolate%20strawberry%20yogurt&st=cse on 26/12/14.

DuBose CN, Cardello AV, Maller O. Effects of colorants and flavorants on identification, perceived flavor intensity, and hedonic quality of fruit-flavored beverages and cake. J Food Sci. 1980;45:1393–9. 1415.

Moir HC. Some observations on the appreciation of flavour in foodstuffs. J Soc Chemical Ind: Chem Ind Rev. 1936;14:145–8.

Duncker K. The influence of past experience upon perceptual properties. Am J Psychol. 1939;52:255–65.

Koza BJ, Cilmi A, Dolese M, Zellner DA. Color enhances orthonasal olfactory intensity and reduces retronasal olfactory intensity. Chem Senses. 2005;30:643–9.

Frank RA, Ducheny K, Mize SJS. Strawberry odor, but not red color, enhances the sweetness of sucrose solutions. Chem Senses. 1989;14:371–7.

Bayarri S, Calvo C, Costell E, Duran L. Influence of color on perception of sweetness and fruit flavor of fruit drinks. Food Sci Technol Int. 2001;7:399–404.

Fernández-Vázquez R, Hewson L, Fisk I, Vila D, Mira F, Vicario IM, et al. Colour influences sensory perception and liking of orange juice. Flavour. 2014;3:1.

Gifford SR, Clydesdale FM. The psychophysical relationship between color and sodium chloride concentrations in model systems. J Food Protect. 1986;49:977–82.

Gifford SR, Clydesdale FM, Damon Jr RA. The psychophysical relationship between color and salt concentrations in chicken flavored broths. J Sensory Stud. 1987;2:137–47.

McCullough JM, Martinsen CS, Moinpour R. Application of multidimensional scaling to the analysis of sensory evaluations of stimuli with known attribute structures. J Applied Psychol. 1978;65:103–9.

Pangborn RM. Influence of color on the discrimination of sweetness. Am J Psychol. 1960;73:229–38.

Pangborn RM, Hansen B. The influence of color on discrimination of sweetness and sourness in pear-nectar. Am J Psychol. 1963;76:315–7.

Roth HA, Radle LJ, Gifford SR, Clydesdale FM. Psychophysical relationships between perceived sweetness and color in lemon- and lime-flavored drinks. J Food Sci. 1988;53:1116–9. 1162.

Strugnell C. Colour and its role in sweetness perception. Appetite. 1997;28:85.

Oram N, Laing DG, Hutchinson I, Owen J, Rose G, Freeman M, et al. The influence of flavor and color on drink identification by children and adults. Develop Psychobiol. 1995;28:239–46.

Zampini M, Wantling E, Phillips N, Spence C. Multisensory flavor perception: assessing the influence of fruit acids and color cues on the perception of fruit-flavored beverages. Food Qual Prefer. 2008;19:335–43.

Garber Jr LL, Hyatt EM, Starr Jr RG. The effects of food color on perceived flavor. J Market Theory Practice. 2000;8(4):59–72.

Hyman A. The influence of color on the taste perception of carbonated water preparations. Bull Psychon Soc. 1983;21:145–8.

Stillman J. Color influences flavor identification in fruit-flavored beverages. J Food Sci. 1993;58:810–2.

Guinard JX, Souchard A, Picot M, Rogeaux M, Siefferman JM. Sensory determinants of the thirst-quenching character of beer. Appetite. 1998;31:101–15.

Zellner DA, Durlach P. What is refreshing? An investigation of the color and other sensory attributes of refreshing foods and beverages. Appetite. 2002;39:185–6.

Zellner DA, Durlach P. Effect of color on expected and experienced refreshment, intensity, and liking of beverages. Am J Psychol. 2003;116:633–47.

Shankar MU, Levitan C, Spence C. Grape expectations: the role of cognitive influences in color-flavor interactions. Conscious Cognit. 2010;19:380–90.

Shankar M, Simons C, Levitan C, Shiv B, McClure S, Spence C. An expectations-based approach to explaining the crossmodal influence of color on odor identification: the influence of temporal and spatial factors. J Sensory Stud. 2010;25:791–803.

Shankar M, Simons C, Shiv B, Levitan C, McClure S, Spence C. An expectations-based approach to explaining the influence of color on odor identification: the influence of degree of discrepancy. Attent Percept Psychophys. 2010;72:1981–93.

Shankar M, Simons C, Shiv B, McClure S, Spence C. An expectation-based approach to explaining the crossmodal influence of color on odor identification: the influence of expertise. Chemosens Percept. 2010;3:167–73.

Piqueras-Fiszman B, Spence C. Crossmodal correspondences in product packaging: assessing color-flavor correspondences for potato chips (crisps). Appetite. 2011;57:753–7.

Yeomans M, Chambers L, Blumenthal H, Blake A. The role of expectancy in sensory and hedonic evaluation: the case of smoked salmon ice-cream. Food Qual Prefer. 2008;19:565–73.

Hoegg J, Alba JW. Taste perception: more than meets the tongue. J Consumer Res. 2007;33:490–8.

Miller EG, Kahn BE. Shades of meaning: the effect of color and flavor names on consumer choice. J Consumer Res. 2005;32:86–92.

Shankar MU, Levitan CA, Prescott J, Spence C. The influence of color and label information on flavor perception. Chemosens Percept. 2009;2:53–8.

Lelièvre M, Chollet S, Abdi H, Valentin D. Beer-trained and untrained assessors rely more on vision than on taste when they categorize beers. Chemosens Percept. 2009;2:143–53.

Garber Jr LL, Hyatt EM, Starr Jr RG. Placing food color experimentation into a valid consumer context. J Food Products Market. 2001;7(3):3–24.

Garber Jr LL, Hyatt EM, Starr Jr RG. Measuring consumer response to food products. Food Qual Prefer. 2003;14:3–15.

Garber Jr LL, Hyatt EM, Starr Jr RG. Reply to commentaries on: “Placing food color experimentation into a valid consumer context”. Food Qual Prefer. 2003;14:41–3.

Wan X, Velasco C, Michel C, Mu B, Woods AT, Spence C. Does the shape of the glass influence the crossmodal association between colour and flavour? A cross-cultural comparison. Flavour. 2014;3:3.

Wan X, Woods AT, Seoul KH, Butcher N, Spence C. When the shape of the glass influences the flavour associated with a coloured beverage: evidence from consumers in three countries. Food Qual Prefer. 2015;39:109–16.

Spence C. Drinking in colour. Cocktail Lovers. 2014;13:28–9.

Birren F. Color and human appetite. Food Technol. 1963;17(May):45–7.

Piqueras-Fiszman B, Spence C. Colour, pleasantness, and consumption behaviour within a meal. Appetite. 2014;75:165–72.

de Wijk RA, Polet IA, Engelen L, van Doorn RM, Prinz JF. Amount of ingested custard dessert as affected by its color, odor, and texture. Physiol Behav. 2004;82:397–403.

Gossinger M, Mayer F, Radochan N, Höfler M, Boner A, Grolle E, et al. Consumer’s color acceptance of strawberry nectars from puree. J Sensory Stud. 2009;24:78–92.

Imram N. The role of visual cues in consumer perception and acceptance of a food product. Nutrit Food Sci. 1999;99:224–30.

Schutz HG. Color in relation to food preference. In: Farrell KT, Wagner JR, Peterson MS, MacKinney G, editors. Color in foods: A symposium sponsored by the Quartermaster Food and Container Institute for the Armed Forces Quartermaster Research and Development Command U. S. Army Quartermaster Corps. Washington: National Academy of Sciences – National Research Council; 1954. p. 16–23.

Wei ST, Ou LC, Luo MR, Hutchings JB. Optimization of food expectations using product colour and appearance. Food Qual Prefer. 2012;23:49–62.

Wilson T, Klaaren K. Expectation whirls me round: the role of affective expectations on affective experiences. In: Clear MS, editor. Review of personality and social psychology: Emotion and social behavior. Newbury Park: Sage; 1992. p. 1–31.

Rolls BJ, Rowe EA, Rolls ET. How sensory properties of foods affect human feeding behaviour. Physiol Behav. 1982;29:409–17.

Geier A, Wansink B, Rozin P. Red potato chips: segmentation cues can substantially decrease food intake. Health Psychol. 2012;31:398–401.

Kahn BE, Wansink B. The influence of assortment structure on perceived variety and consumption quantities. J Consumer Res. 2004;30:519–33.

Redden JP, Hoch SJ. The presence of variety reduces perceived quantity. J Consumer Res. 2009;36:406–17.

Tepper BJ. Effects of a slight color variation on consumer acceptance of orange juice. J Sens Stud. 1993;8:145–54.

Accum F: A treatise on adulteration of food and culinary poisons. Cited in Anon. (1980); 1820.

Anon. Colourings - an interim review. Int Flavours Food Additives. 1979;10(3):96–7.

Anon. Additive use triggers consumer food concerns. Food Product Develop. 1979;13(8):8.

Anon. Food colors. A scientific status summary by the Institute of Food Technologists’ Expert Panel on Food Safety & Nutrition and the Committee on Public Information. Food Technol. 1980;34(7):77–84.

Goldenberg N. Colours - do we need them? In British Nutrition Foundation (Ed.), Why food additives? The safety of foods (pp. 22–24). London, UK: Forbes Publications; 1977.

Kramer A. Benefits and risks of color additives. Food Technol. 1978;32(8):65–7.

Lucas CD, Hallagan JB, Taylor SL. The role of natural color additives in food allergy. Advances Food Nutrit Res. 2001;43:195–216.

Meggos H. Food colours: an international perspective. Manufacturing Confectioner. 1995;75:59–65.

Stevens LJ, Kuczek T, Burgess JR, Stochelski MA, Eugene Arnold L, Galland L. Mechanisms of behavioral, atopic, and other reactions to artificial food colors in children. Nutrit Rev. 2013;71:268–81.

Tuorila-Ollikainen H. Pleasantness of colourless and coloured soft drinks and consumer attitudes to artificial food colours. Appetite. 1982;3:369–76.

Weiss B, Williams JH, Margen S, Abrams B, Caan B, Citron LJ, et al. Behavioral responses to artificial food colors. Science. 1980;207:1487–9.

Whitehill I. Human idiosyncratic responses to food colours. Food Flavour Ingred Packag Process. 1980;1(7):23–7. 37.

Wilson B. Swindled: from poison sweets to counterfeit coffee - the dark history of the food cheats. London: John Murray; 2009.

Patel A. Going green: tuneable colloidal colour blends from natural colourants. New Food Magazine. 2014;17(2):7–9.

Bridle P, Timberlake CF. Anthocyanins as natural food colours--selected aspects. Food Chem. 1997;58:103–9.

Tolliday S. Nestlé confectionary: journey with colours. New Food Magazine. 2012;13(6):27–31.

Wissgott U, Bortlik K. Prospects for new natural food colorants. Trends Food Sci Technol. 1996;7:298–302.

Dalby A. Food in the Ancient World from A to Z. London, UK: Routledge; 2003.

Greene W. Vegetable gardening the Colonial Williamsburg Way: 18th century methods for today’s organic gardeners. Rodale: New York, NY; 2012.

Macrae F: What’s for dinner? Rainbow coloured carrots and super broccoli that’s healthier and sweeter. DailyMail Online 2011, 15 October. Available at http://www.dailymail.co.uk/health/article-2044695/Purple-carrots-sale-Tescosupermarket-Orange-year.html (accessed January 2014).

Cook W: Would you eat a ‘gourmet’ burger made with charred bamboo and squid ink? Daily Mail Online 2012, 25th September. Downloaded from: http://www.dailymail.co.uk/news/article-2208321/Burger-King-black-burger-Japan-bamboo-charcoal-squid-ink.html .

Anon: ‘Anything’ and ‘Whatever’ beverages promise a surprise, every time. Press release, 17th May; 2007.

Garber Jr LL, Hyatt EM, Boya UO. The mediating effects of the appearance of nondurable consumer goods and their packaging on consumer behavior. In: Schifferstein HNJ, Hekkert P, editors. Product experience. London, UK: Elsevier; 2008. p. 581–602.

Walsh LM, Toma RB, Tuveson RV, Sondhi L. Color preference and food choice among children. J Psychol. 1990;124:645–53.

Piqueras-Fiszman B, Spence C. Sensory incongruity in the food and beverage sector: art, science, and commercialization. Petits Propos Culinaires. 2012;95:74–118.

Favre JP, November A. Colour and communication. Zurich: ABC-Verlag; 1979.

Gimba JG. Color in marketing: shades of meaning. Marketing News. 1998;32(6):16.

Hicks D. Benefits of added colourings in food and drinks. Int Flavours Food Additives. 1979;10(1):31–2.

Singh S. Impact of color on marketing. Manag Decis. 2006;44:783–9.

Garber LL, Hyatt EM, & Nafees L: The effects of food color on perceived flavor: a factorial investigation in India. J Food Products Market 2015 (in press).

Masurovsky BI. How to obtain the right food color. Food Industries. 1939;11(13):55–6.

Farrell G: What’s green. Easy to squirt? Ketchup! USA Today 2000, Monday July 10:2b.

Triplett T. Consumers show little taste for clear beverages. Market News. 1994;28(11):2. 11.

Christensen C. Effect of color on judgments of food aroma and food intensity in young and elderly adults. Percept. 1985;14:755–62.

Spence C. The development and decline of multisensory flavour perception. In: Bremner AJ, Lewkowicz D, Spence C, editors. Multisensory development. Oxford, UK: Oxford University Press; 2012. p. 63–87.

Gori M, Del Viva M, Sandini G, Burr DC. Young children do not integrate visual and haptic information. Curr Biol. 2008;18:694–8.

Cheskin L. How to predict what people will buy. New York, NY: Liveright; 1957.

Hine T. The total package: the secret history and hidden meanings of boxes, bottles, cans, and other persuasive containers. New York, NY: Little Brown; 1995.

Pangborn RM, Berg HW, Hansen B. The influence of color on discrimination of sweetness in dry table-wine. Am J Psychol. 1963;76:492–5.

Spence C. The color of wine - part 1. The World of Fine Wine. 2010;28:122–9.

Morrot G, Brochet F, Dubourdieu D. The color of odors. Brain Lang. 2001;79:309–20.

Parr WV, White KG, Heatherbell D. The nose knows: influence of colour on perception of wine aroma. J Wine Res. 2003;14:79–101.

Broackes J. What do the color-blind see? In: Cohen J, Matthen M, editors. Color ontology and color science. Cambridge, MA: MIT Press; 2010. p. 291–389.

Bartoshuk LM. Comparing sensory experiences across individuals: recent psychophysical advances illuminate genetic variation in taste perception. Chem Senses. 2000;25:447–60.

Miller IJ, Reedy DP. Variations in human taste bud density and taste intensity perception. Physiol Behav. 1990;47:1213–9.

Ernst MO, Banks MS. Humans integrate visual and haptic information in a statistically optimal fashion. Nature. 2002;415:429–33.

Scanlon BA. Race differences in selection of cheese color. Percept Motor Skills. 1985;61:314.

Blackwell L. Visual clues and their effects on odour assessment. Nutrit Food Sci. 1995;5:24–8.

Davis RG. The role of nonolfactory context cues in odor identification. Percept Psychophys. 1981;30:83–9.

Michael GA, Galich H, Relland S, Prud’hon S. Hot colors: the nature and specificity of color-induced nasal thermal sensations. Behaviour Brain Res. 2010;207:418–28.

Petit CEF, Hollowood TA, Wulfert F, Hort J. Colour-coolant-aroma interactions and the impact of congruency and exposure on flavour perception. Food Qual Prefer. 2007;18:880–9.

Stevenson RJ, Oaten M. The effect of appropriate and inappropriate stimulus color on odor discrimination. Percept Psychophys. 2008;70:640–6.

Zellner DA, Bartoli AM, Eckard R. Influence of color on odor identification and liking ratings. Am J Psychol. 1991;104:547–61.

Zellner DA, Kautz MA. Color affects perceived odor intensity. J Exp Psychol: Hum Percept Perf. 1990;16:391–7.

Zellner DA, Whitten LA. The effect of color intensity and appropriateness on color-induced odor enhancement. Am J Psychol. 1999;112:585–604.

Zellner DA. Color-odor interactions: a review and model. Chemosens Percept. 2013;6:155–69.

Spence C, Piqueras-Fiszman B. The multisensory packaging of beverages. In: Kontominas MG, editor. Food packaging: Procedures, management and trends. Hauppauge NY: Nova Publishers; 2012. p. 187–233.

Oberfeld D, Hecht H, Allendorf U, Wickelmaier F. Ambient lighting modifies the flavor of wine. J Sens Stud. 2009;24:797–832.

Spence C, Velasco C, Knoeferle K. A large sample study on the influence of the multisensory environment on the wine drinking experience. Flavour. 2014;3:8.

Maga JA. Influence of freshness and color on potato chip sensory preferences. J Food Sci. 1973;38:1251–2.

Skrandies W, Reuther N. Match and mismatch of taste, odor, and color is reflected by electrical activity in the human brain. J Psychophysiol. 2008;22:175–84.

Österbauer RA, Matthews PM, Jenkinson M, Beckmann CF, Hansen PC, Calvert GA. Color of scents: chromatic stimuli modulate odor responses in the human brain. J Neurophysiol. 2005;93:3434–41.

Kappes SM, Schmidt SJ, Lee SY. Color halo/horns and halo-attribute dumping effects within descriptive analysis of carbonated beverages. J Food Sci. 2006;71:S590–5.

Shepherd GM. Neurogastronomy: how the brain creates flavor and why it matters. New York: Columbia University Press; 2012.

Francis FJ, Clydesdale FM. Food colorimetry: theory and applications. New York, NY: Van Nostrand Reinhold/AVI; 1975.

Boesveldt S, Frasnelli J, Gordon AR, Lündstrom JN. The fish is bad: negative food odors elicit faster and more accurate reactions than other odors. Biol Psychol. 2010;84:313–7.

Sawyer FM, Cardello AV, Prell PA. Consumer evaluation of the sensory properties of fish. J Food Sci. 1988;53:12–8. 24.

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CS would like to acknowledge the AHRC Rethinking the Senses grant (AH/L007053/1).

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Food colors: Existing and emerging food safety concerns

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• 1 a Institute for Global Food Security, School of Biological Sciences, Queen's University Belfast , Belfast , United Kingdom.
• PMID: 25849411
• DOI: 10.1080/10408398.2014.889652

Food colors are added to different types of commodities to increase their visual attractiveness or to compensate for natural color variations. The use of these additives is strictly regulated in the European Union, the United States, and many other countries worldwide. There is a growing concern about the safety of some commonly used legal food colorants and there is a trend to replace the synthetic forms with natural products. Additionally, a number of dyes with known or suspected genotoxic or carcinogenic properties have been shown to be added illegally to foods. Robust monitoring programs based on reliable detection methods are required to assure the food is free from harmful colors. The aim of this review is to present an up to date status of the various concerns arising from use of color additives in food. The most important food safety concerns in the field of food colors are lack of uniform regulation concerning legal food colors worldwide, possible link of artificial colors to hyperactive behavior, replacement of synthetic colors with natural ones, and the presence of harmful illegal dyes-both known but also new, emerging ones in food. The legal status of food color additives in the EU, United States, and worldwide is summarized. The reported negative health effects of both legal and illegal colors are presented. The European Rapid Alert System for Food and Feed notifications and US import alerts concerning food colors are analyzed and trends in fraudulent use of color additives identified. The detection methods for synthetic colors are also reviewed.

Keywords: Food dyes; detection methods; legal and illegal food colors; synthetic colors.

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Eating with Your Eyes: The Chemistry of Food Colorings

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By Brian Rohrig  October 2015

Spanish version

Would you drink black water? Clear Pepsi? How about using pink butter or green ketchup? Believe it or not, these products actually existed, and not that long ago either. But there is a reason these food fads did not last. Consumers prefer that the color of food matches its flavor.

The link between color and taste is logical. Since oranges are orange, we expect orange-colored drinks to be orange-flavored. Red drinks should taste like cherries, and purple drinks should taste like grapes. If a food is multicolored, it could be moldy and should not be eaten, unless you are eating blue cheese—which gets its distinct flavor from mold!

An astonishing amount of the foods we eat is processed. These foods are altered from their natural states to make them safe, say, to remove harmful bacteria, or to make them appealing and to prolong their shelf life. About 70% of the diet of the average U.S. resident is from processed foods. Much of what we eat would not look appealing if it was not colored. Think of food coloring as cosmetics for your food. Without coloring, hot dogs would be gray. Yum!

Natural Food Coloring

To avoid so much processed food, some have advocated using natural food coloring, whenever possible. Natural dyes have been used for centuries to color food. Some of the most common ones are carotenoids, chlorophyll, anthocyanin, and turmeric.

Carotenoids have a deep red, yellow, or orange color. Probably the most common carotenoid is beta-carotene (Fig. 1), which is responsible for the bright orange color of sweet potatoes and pumpkins. Since beta-carotene is soluble in fat, it is a great choice for coloring dairy products, which typically have a high fat content. So beta-carotene is often added to margarine and cheese. And, yes, if you eat too many foods that contain beta-carotene, your skin may turn orange. Fortunately, this condition is harmless.

Beta-carotene molecule

Click image to enlarge

Figure 1. Beta-carotene is composed of two small six-carbon rings connected by a chain of carbon atoms.

Chlorophyll is another natural pigment, found in all green plants. This molecule absorbs sunlight and uses its energy to synthesize carbohydrates from carbon dioxide and water. This process is known as photosynthesis and is the basis of life on Earth. Mint- or lime-flavored foods, such as candy and ice cream, are sometimes colored using chlorophyll.

The best natural source for deep purple and blue colors is anthocyanin. Grapes, blueberries, and cranberries owe their rich color to this organic compound. Unlike beta-carotene, anthocyanins—which form a class of similar compounds rather than a single chemical compound—are soluble in water, so they can be used to color water-based products. Blue corn chips, brightly colored soft drinks, and jelly are often dyed with anthocyanins.

More than 500 different anthocyanins have been isolated from plants. They are all based on a single basic core structure, the flavylium ion (Fig. 2). This ion contains three six-carbon rings, as well as many hydroxyl (–OH) groups that make the molecule polar (it has partially negative and partially positive charges) and water-soluble.

Anthocyanin

Figure 2. Chemical structure of an anthocyanin. R 1 and R 2 are functional groups, and R 3 is a sugar molecule.

Another natural food additive you have probably consumed is turmeric, which is added to mustard to impart a deep yellow color. Turmeric is obtained from the underground stem of a plant that grows in India, and it is commonly used as a spice in Indian food. Many U.S. food companies are using turmeric and other natural spices to color their products. Turmeric is also a great acid/base indicator. If you add a basic substance to mustard, it will turn red.

Bugs, anyone?

The next time you enjoy strawberry-flavored yogurt or cranberry juice, you may be eating bugs! But don’t worry. These insects did not contaminate your food by accident. An extract from a type of insect, known as the cochineal, was deliberately added by the food manufacturer.

For centuries, the Aztecs used these insects to dye fabrics a deep-red color . If you crush up 70,000 of these bugs, you can extract a pound of a deep-red dye, called carminic acid (C 22 H 20 O 13 ) (Fig. 3). This dye is safe to ingest, so it found its way into a variety of food and cosmetic products that required a red color. However, the thought of eating bugs is unappealing to some people. Starbucks formerly used cochineal dye in its strawberry-flavored products, but it has since removed this additive in response to customer complaints.

Carminic Acid

Figure 3. Chemical structure of carminic acid

To find out if your food contains bugs, look for carmine, carminic acid, cochineal, or Natural Red 4 on the ingredient label. While these substances are typically considered safe, in rare instances people can have a severe allergic reaction to them, leading to a life-threatening condition called anaphylactic shock.

Why go artificial?

Why bother with artificial, or synthetic, food colorings? Aren’t there enough natural colors to go around? A big reason to go artificial is cost. Synthetic dyes can be mass-produced at a fraction of the cost of gathering and processing the materials used to make natural colorings.

Another reason is shelf life. Artificial dyes might be longer-lasting than natural ones of the same color. Also, although nature produces an impressive hue of colors, those suitable for use as a food dye are limited. But there is no limit to the variety of colors that can be artificially produced in a lab. Considering the thousands of different substances that color our food, it may come as a surprise to discover that the U.S. Food and Drug Administration granted approval to just seven synthetic food colorings for widespread use in food. These food colorings are summarized in Table 1.

Food Colorings

Table 1. Food colorings approved by the U.S. Food and Drug Administration. FD&C stands for laws passed by the U.S. Congress in 1938, called the Federal Food, Drug, and Cosmetic Act.

Artificial food colorings were originally manufactured from coal tar, which comes from coal. Early critics of artificial food colorings were quick to point this out. Today, most synthetic food dyes are derived from petroleum, or crude oil. Some critics will argue that eating oil is no better than eating coal. But the final products are rigorously tested to make sure they contain no traces of the original petroleum. One dye that does not have a petroleum base is Blue No. 2, or indigotine, which is a synthetic version of the plant-based indigo dye, used to color blue jeans.

How to color food

What makes a good food coloring? First, when added to water, it must dissolve. If the dye is not soluble in water, it does not mix evenly. When a typical solute, such as salt or sugar, is added to water, it dissolves, meaning it is broken down into individual ions or molecules. For instance, individual molecules of sugar (C 12 H 22 O 11 ) are held together by relatively weak intermolecular forces. So when sugar dissolves in water, the attractive forces between the individual molecules are overcome, and these molecules are released into solution.

Food-coloring molecules are usually ionic solids, that is, they contain positive and negative ions, which are held together by ionic bonds. When one of these solids dissolves in water, the ions that form the solid are released into the solution, where they become associated with the polar water molecules, which have partially negative and partially positive charges.

Another important property of food coloring is that when it is dissolved in water, the color remains. The reason this happens is that food-coloring molecules absorb some wavelengths of light and let others pass through, resulting in the color we see (Fig. 4). But why wouldn’t sugar or salt absorb portions of the visible light and scatter the rest of it, like food-coloring molecules do? Absorption of light is caused by bringing an electron in a molecule, atom, or ion to a higher energy level. Sugar molecules or the ions in salt require a large amount of energy to do that, so they do not absorb visible light but only light of shorter wavelength—typically ultraviolet light.

Blue and Red Dye

Figure 4. A food dye will appear a particular color because it absorbs light whose color is complementary to the food dye's color, as illustrated here in the case of (a) a blue dye, and (b) a red dye.

Instead, food-coloring molecules typically contain long swaths of alternating single and double bonds (Figs. 1–3) that allow electrons in these molecules to be excited at relatively low energy. The energy required for an electron to jump from that excited state to the ground state corresponds to the energy of visible light, which is why food-coloring molecules can absorb light from the visible spectrum.

What does the future hold?

It is tempting to think that natural products are healthier than artificial ones. But that is not always the case. Cochineal extract is not the only natural dye that can pose a health risk. Serious allergic reactions have also been reported with annatto and saffron—yellow food colorings derived from natural products.

So what will the food of the future look like? Some advocacy groups, such as the Center for Science in the Public Interest, seek to ban all food coloring, because of limited evidence showing that food coloring encourages children to eat junk food. Others envision a different future. One company has already manufactured an edible spray paint called Food Finish, which can be applied to any food. It comes in red, blue, gold, and silver colors.

Eating involves more than just taste. It is a full sensory experience. Both food scientists and chefs will tell you that the smell, sound, feel, and, yes, the sight of your food are just as important as taste to fully appreciate what you eat. That Slurpee would not taste the same if it did not dye your tongue an electric blue. You really can’t help watching what you eat.

Selected references

McKone, H. T. The Unadulterated History of Food Dyes. ChemMatters, Dec 1999, pp 6–7.

U.S. Food and Drug Administration. Overview of Food Ingredients, Additives and Colors. Nov 2004; revised April 2010: http://www.fda.gov/Food/IngredientsPackagingLabeling/FoodAdditivesIngredients/ucm094211.htm#qa [accessed July 2015].

Fiegl, A. Scientists Make Red Food Dye from Potatoes, Not Bugs. National Geographic, Sept 19, 2013: http://news.nationalgeographic.com/news/2013/09/130919-cochineal-carmine-red-dye-purple-sweet-potato-food-science/ [accessed July 2015].

Borrell, B. Where Does Blue Food Dye Come From? Scientific American, Jan 30, 2009: http://www.scientificamerican.com/article/where-does-blue-food-dye/ [accessed July 2015].

Brian Rohrig is a science writer who lives in Columbus, Ohio. His most recent ChemMatters article, “Smartphones, Smart Chemistry,” appeared in the April/May 2015 issue.

Try this Activity!

Can the caramel color of soda be artificially produced.

The caramel coloring of most commercially manufactured colas is derived naturally from caramelized sugar. Suppose for a moment that you are the chemist who works for a bottling plant. You are in charge of formulating the color for the latest batch of carbonated beverages. Unfortunately, the shipment of natural caramel coloring that you were expecting did not arrive, so you have to make the caramel coloring artificially. Can it be done?

• Red, blue, and yellow food coloring
• Clear plastic cups
• Eyedroppers
• Sample of commercial cola
• Prepare 3 cups of colored water using the food coloring.
• Pour a sample of the cola in a separate cup. This sample will remain untouched, and will serve as the control you are trying to replicate.
• Using eyedroppers, add colored water from the 3 cups to the single empty cup in an attempt to replicate the color of the cola.

Were you successful? What strategies did you use? Why do you think artificial coloring is typically not used in carbonated beverages?

—Brian Rohrig

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Colour Measurement and Analysis in Fresh and Processed Foods: A Review

• Review Paper
• Published: 11 May 2012
• Volume 6 , pages 36–60, ( 2013 )

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• Pankaj B. Pathare 1 ,
• Umezuruike Linus Opara 1 &
• Fahad Al-Julanda Al-Said 2  

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Colour is an important quality attribute in the food and bioprocess industries, and it influences consumer’s choice and preferences. Food colour is governed by the chemical, biochemical, microbial and physical changes which occur during growth, maturation, postharvest handling and processing. Colour measurement of food products has been used as an indirect measure of other quality attributes such as flavour and contents of pigments because it is simpler, faster and correlates well with other physicochemical properties. This review discusses the techniques and procedures for the measurement and analysis of colour in food and other biomaterial materials. It focuses on the instrumental (objective) and visual (subjective) measurements for quantifying colour attributes and highlights the range of primary and derived objective colour indices used to characterise the maturity and quality of a wide range of food products and beverages. Different approaches applied to model food colour are described, including reaction mechanisms, response surface methodology and others based on probabilistic and non-isothermal kinetics. Colour is one of the most widely measured product quality attributes in postharvest handling and in the food processing research and industry. Apart from differences in instrumentation, colour measurements are often reported based on different colour indices even for the same product, making it difficult to compare results in the literature. There is a need for standardisation to improve the traceability and transferability of measurements. The correlation between colour and other sensory quality attributes is well established, but future prospects exist in the application of objective non-destructive colour measurement in predictive modelling of the nutritional quality of fresh and processed food products.

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Reflectance colorimetry: a mirror for food quality—a mini review

Sensory Properties of Foods and Their Measurement Methods

Quality and Sensory Evaluation of Food

Abbreviations.

Water activity

CIE red(+)/green(−) colour attribute

CIE yellow(+)/blue(−) colour attribute

• Browning index
• Colour index

Colour index for red grape

Citrus number

Computer vision

Citrus colour index

Tomato colour index

Citrus yellow

Commission Internationale de l’Eclairage

Activation energy (watts per gram or kilojoules per mole)

Hue, saturation and value

Kubelka–Munk parameter

CIE lightness coordinate

Polyphenol oxidase

Universal gas constant

Red, green and blue

Yellowness index

Whiteness index

Total colour difference

Change in measured attribute

Abe, S., Yamamuro, Y., Tau, K., Takenaga, F., Suzuki, К., & Oda, M. (2011). High-pressure and heat pretreatment effects on rehydration and quality of sweet potato. American Journal of Food Technology, 6 , 63–71.

Article   Google Scholar  

Adam, E., Mühlbauer, W., Esper, A., Wolf, W., & Spiess, W. (2000). Quality changes of onion ( Allium cepa L.) as affected by the drying process. Food/Nahrung, 44 (1), 32–37.

Article   CAS   Google Scholar  

Adekunte, A., Tiwari, B., Cullen, P., Scannell, A., & O’Donnell, C. (2010). Effect of sonication on colour, ascorbic acid and yeast inactivation in tomato juice. Food Chemistry, 122 (3), 500–507.

Ahmed, J., Shivhare, U., & Raghavan, G. (2000). Rheological characteristics and kinetics of colour degradation of green chilli puree. Journal of Food Engineering, 44 (4), 239–244.

Ahmed, J., Kaur, A., & Shivhare, U. (2002a). Color degradation kinetics of spinach, mustard leaves, and mixed puree. Journal of Food Science, 67 (3), 1088–1091.

Ahmed, J., Shivhare, U., & Kaur, M. (2002b). Thermal colour degradation kinetics of mango puree. International Journal of Food Properties, 5 (2), 359–366.

Ahmed, J., Shivhare, U., & Sandhu, K. (2002c). Thermal degradation kinetics of carotenoids and visual color of papaya puree. Journal of Food Science, 67 (7), 2692–2695.

Almela, L., Javaloy, S., Fernández-López, J. A., & Lôpez-Roca, J. M. (1995). Comparison between the tristimulus measurements Yxy and L * a * b * to evaluate the colour of young red wines. Food Chemistry, 53 (3), 321–327.

Alvarez, M. D., Fernández, C., & Canet, W. (2010). Oscillatory rheological properties of fresh and frozen/thawed mashed potatoes as modified by different cryoprotectants. Food and Bioprocess Technology, 3 (1), 55–70.

Ameur, L. A., Trystram, G., & Birlouez-Aragon, I. (2006). Accumulation of 5-hydroxymethyl-2-furfural in cookies during the backing process: validation of an extraction method. Food Chemistry, 98 (4), 790–796.

Ameur, L. A., Mathieu, O., Lalanne, V., Trystram, G., & Birlouez-Aragon, I. (2007). Comparison of the effects of sucrose and hexose on furfural formation and browning in cookies baked at different temperatures. Food Chemistry, 101 (4), 1407–1416.

Arabhosseini, A., Padhye, S., Huisman, W., van Boxtel, A., & Müller, J. (2011). Effect of drying on the color of tarragon ( Artemisia dracunculus L.) leaves. Food and Bioprocess Technology, 4 , 1281–1287.

Arslan, D., Özcan, M. (2010). Dehydration of red bell-pepper ( Capsicum annuum L.): change in drying behavior; color and antioxidant content. Food and Bioproducts Processing, 89 (4), 504–513.

Google Scholar  

Arzate-Vázquez, I., Chanona-Pérez, J. J., Perea-Flores, M. J., Calderón-Domínguez, G., Moreno-Armendáriz, M. A., Calvo, H., Godoy-Calderón, S., Quevedo, R., & Gutiérrez-López, G. (2011). Image processing applied to classification of avocado variety hass ( Persea americana Mill.) during the ripening process. Food and Bioprocess Technology, 4 (7), 1307–1313.

Assawarachan, R., & Noomhorm, A. (2010). Changes in color and rheological behavior of pineapple concentrate through various evaporation methods. International Journal of Agricultural and Biological Engineering, 3 (1), 74–84.

Avila, I., & Silva, C. (1999). Modelling kinetics of thermal degradation of colour in peach puree. Journal of Food Engineering, 39 (2), 161–166.

Baini, R., & Langrish, T. (2009). Assessment of colour development in dried bananas—measurements and implications for modelling. Journal of Food Engineering, 93 (2), 177–182.

Barreiro, J., Milano, M., & Sandoval, A. (1997). Kinetics of colour change of double concentrated tomato paste during thermal treatment. Journal of Food Engineering, 33 (3–4), 359–371.

Barrett, D. M., Beaulieu, J. C., & Shewfelt, R. (2010). Color, flavor, texture, and nutritional quality of fresh-cut fruits and vegetables: desirable levels, instrumental and sensory measurement, and the effects of processing. Critical Reviews in Food Science and Nutrition, 50 (5), 369–389.

Bayarri, S., Calvo, C., Costell, E., & Durán, L. (2001). Influence of color on perception of sweetness and fruit flavor of fruit drinks. Food Science and Technology International, 7 (5), 399.

BeMiller, J. N., & Whistler, R. L. (1996). Carbohydrates. In O. R. Fennema (Ed.), Food chemistry (pp. 157–224). New York: Marcel Dekker.

Benlloch-Tinoco, M., Varela, P., Salvador, A., & Martínez-Navarrete, N. (2012). Effects of microwave heating on sensory characteristics of kiwifruit puree. Food and Bioprocess Technology . doi: 10.1007/s11947-011-0652-1 .

Boudhrioua, N., Giampaoli, P., & Bonazzi, C. (2003). Changes in aromatic components of banana during ripening and air-drying. Lebensmittel-Wissenschaft und Technologie, 36 (6), 633–642.

CAS   Google Scholar  

Brandt, S., Pék, Z., Barna, É., Lugasi, A., & Helyes, L. (2006). Lycopene content and colour of ripening tomatoes as affected by environmental conditions. Journal of the Science of Food and Agriculture, 86 (4), 568–572.

Brites, C., Trigo, M. J., Santos, C., Collar, C., & Rosell, C. M. (2010). Maize-based gluten-free bread: influence of processing parameters on sensory and instrumental quality. Food and Bioprocess Technology, 3 (5), 707–715.

Brosnan, T., & Sun, D. W. (2004). Improving quality inspection of food products by computer vision—a review. Journal of Food Engineering, 61 (1), 3–16.

Buera, M., Lozano, R., & Petriella, C. (1986). Definition of colour in the non-enzymatic browning process. Die Farbe, 32 , 318–322.

Buslig, B., Wagner, C., Jr., & Berry, R. (1987). A general purpose tristimulus colorimeter for the measurement of orange juice color. Proceedings of Florida State Horticultural Society, 100 , 47–49.

Campbell, C., Huber, D., & Koch, K. (1989). Postharvest changes in sugars, acids, and color of carambola fruit at various temperatures. HortScience, 24 (3), 472–475.

Cárcel, J., García-Pérez, J., Sanjuán, N., & Mulet, A. (2010). Influence of pre-treatment and storage temperature on the evolution of the colour of dried persimmon. LWT- Food Science and Technology, 43 (8), 1191–1196.

Carreno, J., Martinez, A., Almela, L., & Fernández-López, J. (1995). Proposal of an index for the objective evaluation of the colour of red table grapes. Food Research International, 28 (4), 373–377.

Chen, H. U. I. H., & Chiu, E. (1997). Color and gel–forming properties of horse mackerel ( Trachurus japonicus ) as related to washing conditions. Journal of Food Science, 62 (5), 985–991.

Chutintrasri, B., & Noomhorm, A. (2007). Color degradation kinetics of pineapple puree during thermal processing. LWT- Food Science and Technology, 40 (2), 300–306.

Clydesdale, F. M. (1978). Colorimetry—methodology and applications. Critical Reviews in Food Science and Nutrition, 10 (3), 243–301.

Clydesdale, F. M. (1993). Color as a factor in food choice. Critical Reviews in Food Science and Nutrition, 33 (1), 83–101.

Corzo, O., Bracho, N., & Marjal, J. (2006). Color change kinetics of sardine sheets during vacuum pulse osmotic dehydration. Journal of Food Engineering, 75 (1), 21–26.

Costa, C., Antonucci, F., Pallottino, F., Aguzzi, J., Sun, D., & Menesatti, P. (2011). Shape analysis of agricultural products: a review of recent research advances and potential application to computer vision. Food and Bioprocess Technology, 4 (5), 673–692.

Crisosto, C. H., Crisosto, G. M., & Metheney, P. (2003). Consumer acceptance of ‘Brooks’ and ‘Bing’ cherries is mainly dependent on fruit SSC and visual skin color. Postharvest Biology and Technology, 28 (1), 159–167.

Cubero, S., Aleixos, N., Moltó, E., Gómez-Sanchis, J., & Blasco, J. (2011). Advances in machine vision applications for automatic inspection and quality evaluation of fruits and vegetables. Food and Bioprocess Technology, 4 , 487–504.

Dadali, G., Apar, D. K., & Ozbek, B. (2007a). Color change kinetics of okra undergoing microwave drying. Drying Technology, 25 (5), 925–936.

Dadali, G., Demirhan, E., & Ozbek, B. (2007b). Microwave heat treatment of spinach: drying kinetics and effective moisture diffusivity. Drying Technology, 25 (10), 1703–1712.

Dana, W., & Ivo, W. (2008). Computer image analysis of seed shape and seed color for flax cultivar description. Computers and Electronics in Agriculture, 61 (2), 126–135.

Das, I., Das, S. K., & Bal, S. (2004). Specific energy and quality aspects of infrared (IR) dried parboiled rice. Journal of Food Engineering, 62 (1), 9–14.

Dede, S., Alpas, H., & Bayındırlı, A. (2007). High hydrostatic pressure treatment and storage of carrot and tomato juices: antioxidant activity and microbial safety. Journal of the Science of Food and Agriculture, 87 (5), 773–782.

Demirhan, E., & Ozbek, B. (2009). Color change kinetics of microwave-dried basil. Drying Technology, 27 (1), 156–166.

Drogoudi, P. D., Michailidis, Z., & Pantelidis, G. (2008). Peel and flesh antioxidant content and harvest quality characteristics of seven apple cultivars. Scientia Horticulturae, 115 (2), 149–153.

Du, C. J., & Sun, D. W. (2004). Recent developments in the applications of image processing techniques for food quality evaluation. Trends in Food Science & Technology, 15 (5), 230–249.

Ekpong, A., Ngarmsak, T., & Winger, R. J. (2006). Comparing sensory methods for the optimisation of mango gel snacks. Food Quality and Preference, 17 (7–8), 622–628.

Eksteen, G. J., & Truter, A. B. (1987). Controlled atmosphere storage of deciduous fruit in South Africa. International Journal of Refrigeration, 10 (1), 14–17.

Emmambux, N. M., & Minnaar, A. (2003). The effect of edible coatings and polymeric packaging films on the quality of minimally processed carrots. Journal of the Science of Food and Agriculture, 83 (10), 1065–1071.

Erkan, N., Üretener, G., Alpas, H., Selçuk, A., Özden, Ö., & Buzrul, S. (2011). Effect of high hydrostatic pressure (HHP) treatment on physicochemical properties of horse mackerel ( Trachurus trachurus ). Food and Bioprocess Technology, 4 (7), 1322–1329.

Esti, M., Cinquanta, L., Sinesio, F., Moneta, E., & Di Matteo, M. (2002). Physicochemical and sensory fruit characteristics of two sweet cherry cultivars after cool storage. Food Chemistry, 76 (4), 399–405.

Fathi, M., Mohebbi, M., & Razavi, S. M. A. (2011). Application of image analysis and artificial neural network to predict mass transfer kinetics and color changes of osmotically dehydrated kiwifruit. Food and Bioprocess Technology, 4 (8), 1357–1366.

Fennema, O. R. (1996). Food chemistry (3rd ed.). New York: Marcel Dekker.

Fernández-Artigas, P., Guerra-Hernández, E., & García-Villanova, B. (1999). Browning indicators in model systems and baby cereals. Journal of Agricultural and Food Chemistry, 47 (7), 2872–2878.

Figura, L. O., & Teixeira, A. A. (2007). Food physics: physical properties-measurement and application . New York: Springer.

Francis, F. (1980). Colour quality evaluation of horticultural crops. HortScience, 15 (1), 14–15.

Francis, F. J. (1995). Quality as influenced by color. Food Quality and Preference, 6 (3), 149–155.

Francis, F. J., & Clydesdale, F. M. (1975). Food colorimetry: theory and applications . Westport, CT: AVI Publishing.

Ganjloo, A., Rahman, R. A., Osman, A., Bakar, J., & Bimakr, M. (2011). Kinetics of crude peroxidase inactivation and color changes of thermally treated seedless guava ( Psidium guajava L.). Food and Bioprocess Technology, 4 (8), 1442–1449.

Garza, S., Ibarz, A., Pagan, J., & Giner, J. (1999). Non-enzymatic browning in peach puree during heating. Food Research International, 32 (5), 335–343.

Geel, L., Kinnear, M., & de Kock, H. L. (2005). Relating consumer preferences to sensory attributes of instant coffee. Food Quality and Preference, 16 (3), 237–244.

Giannou, V., & Tzia, C. (2008). Cryoprotective role of exogenous trehalose in frozen dough products. Food and Bioprocess Technology, 1 (3), 276–284.

Gómez-Sanchis, J., Gómez-Chova, L., Aleixos, N., Camps-Valls, G., Montesinos-Herrero, C., Moltó, E., & Blasco, J. (2008). Hyperspectral system for early detection of rottenness caused by Penicillium digitatum in mandarins. Journal of Food Engineering, 89 (1), 80–86.

Granato, D., & Masson, M. L. (2010). Instrumental color and sensory acceptance of soy-based emulsions: a response surface approach. Ciência e Tecnologia de Alimentos, 30 (4), 1090–1096.

Grossman, R. L., & Wisenblit, J. Z. (1999). What we know about consumers’ color choices. Journal of Marketing Practice: Applied Marketing Science, 5 (3), 78–88.

Hertog, M. L. (2002). The impact of biological variation on postharvest population dynamics. Postharvest Biology and Technology, 26 (3), 253–263.

Hertog, M. L., Lammertyn, J., Desmet, M., & Scheerlinck, N. (2004). The impact of biological variation on postharvest behaviour of tomato fruit. Postharvest Biology and Technology, 34 (3), 271–284.

Hertog, M. L., Lammertyn, J., Scheerlinck, N., & Nicolaï, B. M. (2007). The impact of biological variation on postharvest behaviour: the case of dynamic temperature conditions. Postharvest Biology and Technology, 43 (2), 183–192.

Hobson, G. (1987). Low-temperature injury and the storage of ripening tomatoes. Journal of Horticultural Science, 62 (1), 55–62.

Hosoda, H., Inoue, E., Iwahashi, Y., Sakaue, K., Tada, M., & Nagata, T. (2005). Inhibitory effect of sulfides on browning of apple slice. Journal of the Japanese Society for Food Science and Technology, 52 (3), 120–124.

Hsu, C. L., Chen, W., Weng, Y. M., & Tseng, C. Y. (2003). Chemical composition, physical properties, and antioxidant activities of yam flours as affected by different drying methods. Food Chemistry, 83 (1), 85–92.

Hunter, R. S., & Harold, R. W. (1987). The measurement of appearance . Hoboken, NJ: Wiley-Interscience.

HunterLab. (1995). Colorimeters vs. spectrophotometers. Applications note. Insight on Color, 5 (6), 1–2.

Hur, S. J., Park, G. B., & Joo, S. T. (2008). A comparison of the meat qualities from the Hanwoo (Korean native cattle) and Holstein steer. Food and Bioprocess Technology, 1 (2), 196–200.

Hutchings, J. B. (1994). Food colour and appearance . London: Blackie Academic.

Book   Google Scholar  

Ibanoglu, E. (2002). Kinetic study on colour changes in wheat germ due to heat. Journal of Food Engineering, 51 (3), 209–213.

Ibarz, A., Pagan, J., & Garza, S. (1999). Kinetic models for colour changes in pear puree during heating at relatively high temperatures. Journal of Food Engineering, 39 (4), 415–422.

Iwahori, S., Tominaga, S., & Oohata, J. T. (1986). Ethychlozate accelerates colouration and enhances fruit quality of ponkan, Citrus reticulata Blanco. Scientia Horticulturae, 28 (3), 243–250.

Jackman, P., Sun, D. W., & Allen, P. (2011). Recent advances in the use of computer vision technology in the quality assessment of fresh meats. Trends in Food Science & Technology, 22 , 185–197.

Jain, A. K. (1989). Fundamentals of digital image processing . Upper Saddle River, NJ: Prentice-Hall.

Jha, S., Chopra, S., & Kingsly, A. (2007). Modeling of color values for nondestructive evaluation of maturity of mango. Journal of Food Engineering, 78 (1), 22–26.

Jiménez-Cuesta, M., Cuquerella, J., & Martínez-Jávega, J. (1981). Determination of a color index for citrus fruit degreening. Proceedings of the International Society Citriculture .

Jin, S. K., Kim, I. S., Jung, H. J., Kim, D. H., Choi, Y. J., & Hur, S. J. (2011). Effect of cryoprotectants on chemical, mechanical and sensorial characteristics of spent laying hen surimi. Food and Bioprocess Technology, 4 (8), 1407–1413.

Jing, H., Yap, M., Wong, P. Y. Y., & Kitts, D. D. (2011). Comparison of physicochemical and antioxidant properties of egg-white proteins and fructose and inulin Maillard reaction products. Food and Bioprocess Technology, 4 (8), 1489–1496.

Kang, K., Oh, G., Go, Y., Kim, Y., Park, D., & Kim, H. (2004). Inhibition of enzymatic browning in Paeoniae radix rubra by citric acid. Food Science and Biotechnology, 13 , 119–125.

Kaya, A., Ko, S., & Gunasekaran, S. (2011). Viscosity and color change during in situ solidification of grape pekmez. Food and Bioprocess Technology, 4 (2), 241–246.

Kaymak-Ertekin, F., & Gedik, A. (2005). Kinetic modelling of quality deterioration in onions during drying and storage. Journal of Food Engineering, 68 (4), 443–453.

Kotwaliwale, N., Bakane, P., & Verma, A. (2007). Changes in textural and optical properties of oyster mushroom during hot air drying. Journal of Food Engineering, 78 (4), 1207–1211.

Kramer, A. (1976). Use of colour measurements in quality control of food. Food Technology, 30 , 62–64. 66, 68, 70–71.

Krokida, M., & Maroulis, Z. (1999). Effect of microwave drying on some quality properties of dehydrated products. Drying Technology, 17 (3), 449–466.

Krokida, M., Tsami, E., & Maroulis, Z. (1998). Kinetics on color changes during drying of some fruits and vegetables. Drying Technology, 16 (3/5), 667–685.

Krokida, M., Karathanos, V., & Maroulis, Z. (2000). Effect of osmotic dehydration on color and sorption characteristics of apple and banana. Drying Technology, 18 (4), 937–950.

Krokida, M. K., Maroulis, Z. B., & Saravacos, G. D. (2001). The effect of the method of drying on the colour of dehydrated products. International Journal of Food Science and Technology, 36 (1), 53–59.

Kühn, B. F., & Thybo, A. K. (2001). The influence of sensory and physiochemical quality on Danish children’s preferences for apples. Food Quality and Preference, 12 (8), 543–550.

Labell, F. (1993). Pink grapefruit beverages: mainstream refreshment. Food Process, 54 (5), 66.

Lambrecht, H. (1995). Sulfite substitutes for the prevention of enzymatic browning in foods. In Enzymatic Browning and its Prevention. ACM Symposium Series No. 600 , pp 313–324.

Lang, C., & Hübert, T. (2012). A colour ripeness indicator for apples. Food and Bioprocess Technology . doi: 10.1007/s11947-011-0694-4 .

Larrauri García, J. A., & Saura Calixto, F. (2000). Evaluation of CIE–lab colour parameters during the clarification of a sugar syrup from Mesquite pods ( Prosopis pallida L.). International Journal of Food Science and Technology, 35 (4), 385–389.

Lebesi, D. M., & Tzia, C. (2011). Effect of the addition of different dietary fiber and edible cereal bran sources on the baking and sensory characteristics of cupcakes. Food and Bioprocess Technology, 4 (5), 710–722.

Lee, H. S. (2000). Objective measurement of red grapefruit juice color. Journal of Agricultural and Food Chemistry, 48 (5), 1507–1511.

Leemans, V., Magein, H., & Destain, M. F. (1998). Defects segmentation on ‘Golden Delicious’ apples by using colour machine vision. Computers and Electronics in Agriculture, 20 (2), 117–130.

Leon, K., Mery, D., Pedreschi, F., & Leon, J. (2006). Color measurement in L * a * b * units from RGB digital images. Food Research International, 39 (10), 1084–1091.

Lin, L. Y., Liu, H. M., Yu, Y. W., Lin, S. D., & Mau, J. L. (2009). Quality and antioxidant property of buckwheat enhanced wheat bread. Food Chemistry, 112 (4), 987–991.

Little, A. (1975). Off on a tangent. Journal of Food Science, 40 , 410–411.

Liu, Y., Fan, X., Chen, Y. R., & Thayer, D. W. (2003). Changes in structure and color characteristics of irradiated chicken breasts as a function of dosage and storage time. Meat Science, 63 (3), 301–307.

Lopez, A., Pique, M., Boatella, J., Romero, A., Ferran, A., & Garcia, J. (1997). Influence drying conditions on the hazelnut quality. III. Browning. Drying Technology, 15 (3–4), 989–1002.

Lozano, J., & Ibarz, A. (1997). Colour changes in concentrated fruit pulp during heating at high temperatures. Journal of Food Engineering, 31 (3), 365–373.

Lu, S., Luo, Y., Turner, E., & Feng, H. (2007). Efficacy of sodium chlorite as an inhibitor of enzymatic browning in apple slices. Food Chemistry, 104 (2), 824–829.

Lunadei, L., Galleguillos, P., Diezma, B., Lleó, L., & Ruiz-Garcia, L. (2011). A multispectral vision system to evaluate enzymatic browning in fresh-cut apple slices. Postharvest Biology and Technology, 60 , 225–234.

Lurie, S. (2009). 1.1 Quality parameters of fresh fruit and vegetable at harvest and shelf life. In M. Zude (Ed.), Optical monitoring of fresh and processed agricultural crops (pp. 2–16). Boca Raton: CRC.

Lv, B., Li, B., Chen, S., Chen, J., & Zhu, B. (2009). Comparison of color techniques to measure the color of parboiled rice. Journal of Cereal Science, 50 (2), 262–265.

MacDougall, D. B. (2002). Colour in food: Improving quality . Boca Raton: CRC.

Maharaj, R., Arul, J., & Nadeau, P. (1999). Effect of photochemical treatment in the preservation of fresh tomato ( Lycopersicon esculentum cv. Capello) by delaying senescence. Postharvest Biology and Technology, 15 (1), 13–23.

Mangaraj, S., & Goswami, T. (2011). Modeling of respiration rate of litchi fruit under aerobic conditions. Food and Bioprocess Technology, 4 (2), 272–281.

Manickavasagan, A., Jayas, D., White, N. D. G., & Paliwal, J. (2010). Wheat class identification using thermal imaging. Food and Bioprocess Technology, 3 (3), 450–460.

Marquez, G., & Anon, M. (1986). Influence of reducing sugars and amino acids in the color development of fried potatoes. Journal of Food Science, 51 (1), 157–160.

Martins, R. C., & Silva, C. L. M. (2002). Modelling colour and chlorophyll losses of frozen green beans ( Phaseolus vulgaris , L.). International Journal of Refrigeration, 25 (7), 966–974.

Maskan, M. (2001). Kinetics of colour change of kiwifruits during hot air and microwave drying. Journal of Food Engineering, 48 (2), 169–175.

Maskan, A., Kaya, S., & Maskan, M. (2002). Effect of concentration and drying processes on color change of grape juice and leather (pestil). Journal of Food Engineering, 54 (1), 75–80.

Mayer, A. M., & Harel, E. (1979). Polyphenol oxidases in plants. Phytochemistry, 18 (2), 193–215.

McMinn, W., & Magee, T. (1997). Kinetics of ascorbic acid degradation and non-enzymic browning in potatoes. Food and Bioproducts Processing, 75 (4), 223–231.

Medlicott, A., Semple, A., Thompson, A., Blackbourne, H., & Thompson, A. (1992). Measurement of colour changes in ripening bananas and mangoes by instrumental, chemical and visual assessments. Tropical Agriculture, 69 (2), 161–166.

Meléndez-Martínez, A., Gómez-Robledo, L., Melgosa, M., Vicario, I., & Heredia, F. (2012). Color of orange juices in relation to their carotenoid contents as assessed from different spectroscopic data. Journal of Food Composition and Analysis, 26 (6), 837–844.

Meléndez-Martínez, A., Vicario, I., & Heredia, F. (2005). Instrumental measurement of orange juice colour: a review. Journal of the Science of Food and Agriculture, 85 (6), 894–901.

Mendoza, F., & Aguilera, J. (2004). Application of image analysis for classification of ripening bananas. Journal of Food Science, 69 (9), E471–E477.

Mendoza, F., Dejmek, P., & Aguilera, J. M. (2006). Calibrated color measurements of agricultural foods using image analysis. Postharvest Biology and Technology, 41 (3), 285–295.

Minolta, K. (1994). Precise color communication . Ramsey, NJ: Minolta Co.

Mitcham, B., Cantwell, M., & Kader, A. (1996). Methods for determining quality of fresh commodities. Perishables Handling Newsletter, 85 , 1–6.

Mohapatra, D., Bira, Z. M., Kerry, J. P., Frías, J. M., & Rodrigues, F. A. (2010). Postharvest hardness and color evolution of white button mushrooms ( Agaricus bisporus ). Journal of Food Science, 75 (3), E146–E152.

Mottur, G. (1989). A scientific look at potato chips: the original savory snack. Cereal Foods World (USA), 34 , 620–626.

Narender Raju, P., & Pal, D. (2009). The physico-chemical, sensory, and textural properties of misti dahi prepared from reduced fat buffalo milk. Food and Bioprocess Technology, 2 (1), 101–108.

Nevares, I., Del Alamo, M., Cárcel, L., Crespo, R., Martin, C., & Gallego, L. (2009). Measure the dissolved oxygen consumed by red wines in aging tanks. Food and Bioprocess Technology, 2 (3), 328–336.

Nieto-Sandoval, J. M., Fernández-López, J. A., Almela, L., & Muñoz, J. A. (1999). Dependence between apparent color and extractable color in paprika. Color Research and Application, 24 , 93–97.

Nisha, P., Singhal, R. S., & Pandit, A. B. (2011). Kinetic modelling of colour degradation in tomato puree ( Lycopersicon esculentum L.). Food and Bioprocess Technology, 4 , 781–787.

North, M., Cook, N. (2006). Effect of six rootstocks on ‘Forelle’ pear tree growth, production, fruit quality and leaf mineral content. XXVII International Horticultural Congress-IHC2006: International Symposium on Enhancing Economic and Environmental 772 .

O’Leary, E., Gormley, T., Butler, F., & Shilton, N. (2000). The effect of freeze-chilling on the quality of ready-meal components. Lebensmittel-Wissenschaft und Technologie, 33 (3), 217–224.

Obenland, D., Collin, S., Mackey, B., Sievert, J., Fjeld, K., & Arpaia, M. L. (2009). Determinants of flavor acceptability during the maturation of navel oranges. Postharvest Biology and Technology, 52 (2), 156–163.

Ochoa, M. R., Kesseler, A. G., De Michelis, A., Mugridge, A., & Chaves, A. R. (2001). Kinetics of colour change of raspberry, sweet ( Prunus avium ) and sour ( Prunus cerasus ) cherries preserves packed in glass containers: light and room temperature effects. Journal of Food Engineering, 49 (1), 55–62.

Oliver, J., Blakeney, A., & Allen, H. (1992). Measurement of flour color in color space parameters. Cereal Chemistry, 69 (5), 546–551.

Opara, L. U., & Al-Ani, M. R. (2010a). Antioxidant components in fresh-cut and whole fruit and vegetables. British Food Journal, 112 (8), 797–810.

Opara, L. U., & Al-Ani, M. R. (2010b). Effects of cooking methods on carotenoids content of Kingfish. British Food Journal, 112 (8), 811–820.

Opara, L. U., Al-Ani, M. R., & Al-Shuaibi, Y. S. (2009). Physico-chemical properties, vitamin C content, and antimicrobial properties of pomegranate fruit ( Punica granatum L.). Food and Bioprocess Technology, 2 (3), 315–321.

Osanai, Y., Motomura, Y., & Sakurai, N. (2003). Effect of methyl bromide on the internal browning, firmness and elasticity of flesh in un-bagged apple ‘Fuji’ fruit. Journal of the Japanese Society for Food Science and Technology, 50 (5), 254–258.

Ozdemir, M., & Devres, O. (2000a). Analysis of color development during roasting of hazelnuts using response surface methodology. Journal of Food Engineering, 45 (1), 17–24.

Ozdemir, M., & Devres, O. (2000b). Kinetics of color changes of hazelnuts during roasting. Journal of Food Engineering, 44 (1), 31–38.

Palacios, V., Caro, I., & Pérez, L. (2002). Comparative study of crossflow microfiltration with conventional filtration of sherry wines. Journal of Food Engineering, 54 (2), 95–102.

Papadakis, S. E., Abdul-Malek, S., Kamdem, R. E., & Yam, K. L. (2000). A versatile and inexpensive technique for measuring color of foods. Food Technology, 54 (12), 48–51.

Park, C., & Lee, K. (1975). A study on influence of drying methods upon the chemical changes in red pepper: Part 2. Changes of free amino acid, free sugar. Korean Journal of Nutrition, 8 , 33–37.

Parker, R. (2001). Introduction to food science. Cengage Learning.

Patras, A., Brunton, N. P., Da Pieve, S., & Butler, F. (2009a). Impact of high pressure processing on total antioxidant activity, phenolic, ascorbic acid, anthocyanin content and colour of strawberry and blackberry purées. Innovative Food Science & Emerging Technologies, 10 (3), 308–313.

Patras, A., Brunton, N. P., Tiwari, B., & Butler, F. (2011). Stability and degradation kinetics of bioactive compounds and colour in strawberry jam during storage. Food and Bioprocess Technology, 4 , 1245–1252.

Pedreschi, F., Mery, D., Mendoza, F., & Aguilera, J. (2004). Classification of potato chips using pattern recognition. Journal of Food Science, 69 (6), E264–E270.

Pedreschi, F., Bustos, O., Mery, D., Moyano, P., Kaack, K., & Granby, K. (2007). Color kinetics and acrylamide formation in NaCl soaked potato chips. Journal of Food Engineering, 79 (3), 989–997.

Pedreschi, F., Bunger, A., Skurtys, O., Allen, P., & Rojas, X. (2012). Grading of potato chips according to their sensory quality determined by color. Food and Bioprocess Technology . doi: 10.1007/s11947-011-0559-x .

Pék, Z., Helyes, L., & Lugasi, A. (2010). Color changes and antioxidant content of vine and postharvest-ripened tomato fruits. HortScience, 45 (3), 466–468.

Pereira, A. C., Reis, M. S., & Saraiva, P. M. (2009). Quality control of food products using image analysis and multivariate statistical tools. Industrial and Engineering Chemistry Research, 48 (2), 988–998.

Pott, I., Neidhart, S., Muhlbauer, W., & Carle, R. (2005). Quality improvement of non-sulphited mango slices by drying at high temperatures. Innovative Food Science & Emerging Technologies, 6 (4), 412–419.

Pristijono, P., Wills, R., & Golding, J. (2006). Inhibition of browning on the surface of apple slices by short term exposure to nitric oxide (NO) gas. Postharvest Biology and Technology, 42 (3), 256–259.

Purlis, E. (2010). Browning development in bakery products—a review. Journal of Food Engineering, 99 (3), 239–249.

Purlis, E., & Salvadori, V. O. (2009). Modelling the browning of bread during baking. Food Research International, 42 (7), 865–870.

Qin, P., Wang, Q., Shan, F., Hou, Z., & Ren, G. (2010). Nutritional composition and flavonoids content of flour from different buckwheat cultivars. International Journal of Food Science and Technology, 45 (5), 951–958.

Quevedo, R., Aguilera, J., & Pedreschi, F. (2010). Color of salmon fillets by computer vision and sensory panel. Food and Bioprocess Technology, 3 (5), 637–643.

Quintas, M. A. C., Brandão, T. R. S., & Silva, C. L. M. (2007). Modelling colour changes during the caramelisation reaction. Journal of Food Engineering, 83 (4), 483–491.

Quitão-Teixeira, L. J., Aguiló-Aguayo, I., Ramos, A. M., & Martín-Belloso, O. (2008). Inactivation of oxidative enzymes by high-intensity pulsed electric field for retention of color in carrot juice. Food and Bioprocess Technology, 1 (4), 364–373.

Ramirez-Jimenez, A., Guerra-Hernández, E., & García-Villanova, B. (2000). Browning indicators in bread. Journal of Agricultural and Food Chemistry, 48 (9), 4176–4181.

Rattanathanalerk, M., Chiewchan, N., & Srichumpoung, W. (2005). Effect of thermal processing on the quality loss of pineapple juice. Journal of Food Engineering, 66 (2), 259–265.

Rekha, M., Yadav, A. R., Dharmesh, S., Chauhan, A., & Ramteke, R. (2010). Evaluation of antioxidant properties of dry soup mix extracts containing dill ( Anethum sowa L.) leaf. Food and Bioprocess Technology, 3 (3), 441–449.

Resmini, P., Pellegrino, L., Pagani, M., & De Noni, I. (1993). Formation of 2-acetyl-3- d -glucopyranosylfuran (glucosylisomaltol) from nonenzymatic browning in pasta drying. Italian Journal of Food Science, 5 (4), 341–353.

Rhim, J. W., & Hong, S. I. (2011). Effect of water activity and temperature on the color change of red pepper ( Capsicum annuum L.) powder. Food Science and Biotechnology, 20 (1), 215–222.

Rhim, J., Nunes, R., Jones, V., & Swartzel, K. (1989). Kinetics of color change of grape juice generated using linearly increasing temperature. Journal of Food Science, 54 (3), 776–777.

Rhim, J., Wu, Y., Weller, C., & Schnepf, M. (1999). Physical characteristics of a composite film of soy protein isolate and propyleneglycol alginate. Journal of Food Science, 64 (1), 149–152.

Ribotta, P. D., Pérez, G. T., Añón, M. C., & León, A. E. (2010). Optimization of additive combination for improved soy–wheat bread quality. Food and Bioprocess Technology, 3 (3), 395–405.

Rodriguez-Aguilera, R., Oliveira, J. C., Montanez, J. C., & Mahajan, P. V. (2011). Effect of modified atmosphere packaging on quality factors and shelf-life of mould surface-ripened cheese: Part II varying storage temperature. LWT- Food Science and Technology, 44 (1), 337–342.

Rosales-Juárez, M., González-Mendoza, B., López-Guel, E. C., Lozano-Bautista, F., Chanona-Pérez, J., Gutiérrez-López, G., Farrera-Rebollo, R., & Calderón-Domínguez, G. (2008). Changes on dough rheological characteristics and bread quality as a result of the addition of germinated and non-germinated soybean flour. Food and Bioprocess Technology, 1 (2), 152–160.

Sabanis, D., & Tzia, C. (2009). Effect of rice, corn and soy flour addition on characteristics of bread produced from different wheat cultivars. Food and Bioprocess Technology, 2 (1), 68–79.

Sabanis, D., Tzia, C., & Papadakis, S. (2008). Effect of different raisin juice preparations on selected properties of gluten-free bread. Food and Bioprocess Technology, 1 (4), 374–383.

Sacks, E. J., & Francis, D. M. (2001). Genetic and environmental variation for tomato flesh color in a population of modern breeding lines. Journal of the American Society for Horticultural Science, 126 (2), 221–226.

Sahin, S., & Sumnu, S. G. (2006). Physical properties of foods . New York: Springer.

Sapers, G. M., & Douglas, F. W., Jr. (1987). Measurement of enzymatic browning at cut surfaces and in juice of raw apple and pear fruits. Journal of Food Science, 52 (5), 1258–1285.

Saricoban, C., & Yilmaz, M. T. (2010). Modelling the effects of processing factors on the changes in colour parameters of cooked meatballs using response surface methodology. World Applied Sciences Journal, 9 (1), 14–22.

Saxena, A., Maity, T., Raju, P., & Bawa, A. (2010). Degradation kinetics of colour and total carotenoids in jackfruit ( Artocarpus heterophyllus ) bulb slices during hot air drying. Food and Bioprocess Technology, 5 , 672–679.

Scanlon, M., Roller, R., Mazza, G., & Pritchard, M. (1994). Computerized video image analysis to quantify color of potato chips. American Journal of Potato Research, 71 (11), 717–733.

Schouten, R. E., Jongbloed, G., Tijskens, L., & van Kooten, O. (2004). Batch variability and cultivar keeping quality of cucumber. Postharvest Biology and Technology, 32 (3), 299–310.

Schouten, R. E., Huijben, T. P. M., Tijskens, L., & van Kooten, O. (2007). Modelling quality attributes of truss tomatoes: linking colour and firmness maturity. Postharvest Biology and Technology, 45 (3), 298–306.

Sciarini, L. S., Ribotta, P. D., León, A. E., & Pérez, G. T. (2010). Influence of gluten-free flours and their mixtures on batter properties and bread quality. Food and Bioprocess Technology, 3 (4), 577–585.

Segnini, S., Dejmek, P., & Öste, R. (1999). A low cost video technique for colour measurement of potato chips. Lebensmittel-Wissenschaft und Technologie, 32 (4), 216–222.

Sharma, R., Kaur, D., Oberoi, D., & Sogi, D. (2008). Thermal degradation kinetics of pigments and visual color in watermelon juice. International Journal of Food Properties, 11 (2), 439–449.

Shewfelt, R. (1993). Measuring quality and maturity. In R. L. Shewfelt & S. E. Prussia (Eds.), Postharvest handling: a systems approach (pp. 99–124). San Diego: Academic.

Chapter   Google Scholar  

Shewfelt, R. L. (2000). Fruit & vegetable quality. In R. L. Shewfelt & B. Brückner (Eds.), Fruit & vegetable quality: an integrated view (pp. 144–157). Lancaster: Technomic Press.

Shewfelt, R. (2003). Color. In J. A. Bartz & J. K. Brecht (Eds.), Postharvest physiology and pathology of vegetables (pp. 287–296). New York: Marcel Dekker.

Shewfelt, R., Heaton, E., & Batal, K. (1984). Nondestructive color measurement of fresh broccoli. Journal of Food Science, 49 (6), 1612–1613.

Shi, J., Maguer, M. L., Kakuda, Y., Liptay, A., & Niekamp, F. (1999). Lycopene degradation and isomerization in tomato dehydration. Food Research International, 32 (1), 15–21.

Shin, S., & Bhowmik, S. R. (1995). Thermal kinetics of color changes in pea puree. Journal of Food Engineering, 24 (1), 77–86.

Silva, F. M., & Silva, C. L. M. (1999). Colour changes in thermally processed cupuaçu ( Theobroma grandiflorum ) puree: critical times and kinetics modelling. International Journal of Food Science and Technology, 34 (1), 87–94.

Sinesio, F., & Moneta, E. (1997). Sensory evaluation of walnut fruit. Food Quality and Preference, 8 (1), 35–43.

Singh, K. K., & Reddy, B. S. (2006). Post-harvest physico-mechanical properties of orange peel and fruit. Journal of Food Engineering, 73 (2), 112–120.

Skrede, G. (1985). Color quality of blackcurrant syrups during storage evaluated by hunter L ′, a ′, b ′ values. Journal of Food Science, 50 (2), 514–517.

Soysal, Y. (2004). Microwave drying characteristics of parsley. Biosystems Engineering, 89 (2), 167–173.

Stamp, J., & Labuza, T. (1983). Kinetics of the Maillard reaction between aspartame and glucose in solution at high temperatures. Journal of Food Science, 48 (2), 543–544.

Stewart, I., Wheaton, T. (1971). Effects of ethylene and temperature on carotenoid pigmentation of citrus peel. Proceedings of Florida State Horticultural Society.

Suh, H. J., Noh, D. O., Kang, C. S., Kim, J. M., & Lee, S. W. (2003). Thermal kinetics of color degradation of mulberry fruit extract. Food/Nahrung, 47 (2), 132–135.

Sumnu, G., Turabi, E., & Oztop, M. (2005). Drying of carrots in microwave and halogen lamp–microwave combination ovens. LWT- Food Science and Technology, 38 (5), 549–553.

Sun, D. W. (2004). Computer vision—an objective, rapid and non-contact quality evaluation tool for the food industry. Journal of Food Engineering, 61 (1), 1–2.

Tao, Y., Heinemann, P., Varghese, Z., Morrow, C., & Sommer, H. (1995). Machine vision for color inspection of potatoes and apples. Transactions of ASAE, 38 (5), 1555–1562.

Tijskens, L., & Evelo, R. (1994). Modelling colour of tomatoes during postharvest storage. Postharvest Biology and Technology, 4 (1–2), 85–98.

Tijskens, L., Schijvens, E., & Biekman, E. (2001). Modelling the change in colour of broccoli and green beans during blanching. Innovative Food Science & Emerging Technologies, 2 (4), 303–313.

Tijskens, L. M. M., Konopacki, P., & Simcic, M. (2003). Biological variance, burden or benefit? Postharvest Biology and Technology, 27 (1), 15–25.

Tijskens, L., Heuvelink, E., Schouten, R., Lana, M., & Van Kooten, O. (2005). The biological shift factor: biological age as a tool for modelling in pre-and postharvest horticulture. International Conference Postharvest Unlimited Downunder 2004, 687.

Tijskens, L., Unuk, T., Tojnko, S., Hribar, J., & Simcic, M. (2011). Colour development in the apple orchard. Journal of Fruit and Ornamental Plant Research, 19 (1), 113–121.

Tiwari, B., Muthukumarappan, K., O’Donnell, C., & Cullen, P. (2008a). Effects of sonication on the kinetics of orange juice quality parameters. Journal of Agricultural and Food Chemistry, 56 (7), 2423–2428.

Tiwari, B., Muthukumarappan, K., O’Donnell, C., & Cullen, P. (2008b). Modelling colour degradation of orange juice by ozone treatment using response surface methodology. Journal of Food Engineering, 88 (4), 553–560.

Tiwari, B., O’Donnell, C., Muthukumarappan, K., & Cullen, P. (2009). Effect of low temperature sonication on orange juice quality parameters using response surface methodology. Food and Bioprocess Technology, 2 (1), 109–114.

Toivonen, P. M. A., Kappel, F., Stan, S., McKenzie, D. L., & Hocking, R. (2004). Firmness, respiration, and weight loss of ‘Bing’, ‘Lapins’ and ‘Sweetheart’ cherries in relation to fruit maturity and susceptibility to surface pitting. HortScience, 39 (5), 1066–1069.

Tsami, E., & Katsioti, M. (2000). Drying kinetics for some fruits: predicting of porosity and color during dehydration. Drying Technology, 18 (7), 1559–1581.

Turabi, E., Sumnu, G., & Sahin, S. (2008). Optimization of baking of rice cakes in infrared–microwave combination oven by response surface methodology. Food and Bioprocess Technology, 1 (1), 64–73.

Usenik, V., Fabcic, J., & Stampar, F. (2008). Sugars, organic acids, phenolic composition and antioxidant activity of sweet cherry ( Prunus avium L.). Food Chemistry, 107 (1), 185–192.

Vamos-Vigyazo, L. (1981). Polyphenol oxidase and peroxidase in fruits and vegetables. CRC Critical Reviews in Food Science and Nutrition, 15 , 49–127.

Van Boekel, M. (1996). Statistical aspects of kinetic modeling for food science problems. Journal of Food Science, 61 (3), 477–486.

Van Zeebroeck, M., Ramon, H., De Baerdemaeker, J., Nicolai, B., & Tijskens, E. (2007). Impact damage of apples during transport and handling. Postharvest Biology and Technology, 45 (2), 157–167.

Vandekinderen, I., Van Camp, J., Devlieghere, F., Veramme, K., Denon, Q., Ragaert, P., & De Meulenaer, B. (2008). Effect of decontamination agents on the microbial population, sensorial quality, and nutrient content of grated carrots ( Daucus carota L.). Journal of Agricultural and Food Chemistry, 56 (14), 5723–5731.

Vardin, H., & Fenercioǧlu, H. (2003). Study on the development of pomegranate juice processing technology: clarification of pomegranate juice. Food/Nahrung, 47 (5), 300–303.

Vásquez-Caicedo, A. L., Sruamsiri, P., Carle, R., & Neidhart, S. (2005). Accumulation of all- trans -β-carotene and its 9- cis and 13-cis stereoisomers during postharvest ripening of nine Thai mango cultivars. Journal of Agricultural and Food Chemistry, 53 (12), 4827–4835.

Voegel-Turenne, C., Allaf, K., & Bouvier, J. (1997). Analysis and modeling of browning of the Granny Smith apple during drying. Drying Technology, 15 (10), 2587–2596.

Walker, J. R. L. (1975). Enzymic browning in food. A review. Enzyme Technology Digest, 4 , 89.

Walker, P., Warner, R., & Winfield, C. (1990). Sources of variation in subcutaneous fat colour of beef carcasses. Proceedings of the Australian Society of Animal Production .

Walkling-Ribeiro, M., Noci, F., Riener, J., Cronin, D., Lyng, J., & Morgan, D. (2009). The impact of thermosonication and pulsed electric fields on Staphylococcus aureus inactivation and selected quality parameters in orange juice. Food and Bioprocess Technology, 2 (4), 422–430.

Walkling-Ribeiro, M., Noci, F., Cronin, D. A., Lyng, J. G., & Morgan, D. J. (2010). Shelf life and sensory attributes of a fruit smoothie-type beverage processed with moderate heat and pulsed electric fields. LWT- Food Science and Technology, 43 (7), 1067–1073.

Wambura, P., Yang, W., & Mwakatage, N. R. (2011). Effects of sonication and edible coating containing rosemary and tea extracts on reduction of peanut lipid oxidative rancidity. Food and Bioprocess Technology, 4 (1), 107–115.

Wand, S. J. E., Theron, K. I., Ackerman, J., & Marais, S. J. S. (2006). Harvest and post-harvest apple fruit quality following applications of kaolin particle film in South African orchards. Scientia Horticulturae, 107 (3), 271–276.

Wolf, G. (1984). Multiple functions of vitamin A. Physiological Reviews, 64 (3), 873.

Yam, K. L., & Papadakis, S. E. (2004). A simple digital imaging method for measuring and analyzing color of food surfaces. Journal of Food Engineering, 61 (1), 137–142.

Yu, H., MacGregor, J. F., Haarsma, G., & Bourg, W. (2003). Digital imaging for online monitoring and control of industrial snack food processes. Industrial and Engineering Chemistry Research, 42 (13), 3036–3044.

Zanoni, B., Peri, C., & Bruno, D. (1995). Modelling of browning kinetics of bread crust during baking. Lebensmittel-Wissenschaft und Technologie, 28 (6), 604–609.

Zepka, L. Q., Borsarelli, C. D., da Silva, M. A. A. P., & Mercadante, A. Z. (2009). Thermal degradation kinetics of carotenoids in a cashew apple juice model and its impact on the system color. Journal of Agricultural and Food Chemistry, 57 (17), 7841–7845.

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This work is based upon research supported by the South African Research Chairs Initiative of the Department of Science and Technology and National Research Foundation.

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Pathare, P.B., Opara, U.L. & Al-Said, F.AJ. Colour Measurement and Analysis in Fresh and Processed Foods: A Review. Food Bioprocess Technol 6 , 36–60 (2013). https://doi.org/10.1007/s11947-012-0867-9

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DOI : https://doi.org/10.1007/s11947-012-0867-9

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Technological Applications of Natural Colorants in Food Systems: A Review

Ivan luzardo-ocampo.

1 Instituto de Neurobiología, Universidad Nacional Autónoma de México (UNAM), Santiago de Querétaro, QRO 76230, Mexico; [email protected]

Aurea K. Ramírez-Jiménez

2 Tecnologico de Monterrey, School of Engineering and Science, Avenida Eugenio Garza Sada 2501 Sur, Monterrey, N. L. 64849, Mexico; xm.cet@jzerimara (A.K.R.-J.); xm.mseti@68523800A (J.Y.)

Jimena Yañez

Luis mojica.

3 Tecnología Alimentaria, Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco (CIATEJ), A. C., Camino Arenero #1227 Col. El Bajío, Zapopan, JAL 45019, Mexico; xm.jetaic@acijoml

Diego A. Luna-Vital

Associated data.

Data are available upon reasonable request.

Natural colorants have emerged as an alternative to their synthetic counterparts due to an existing health concern of these later. Moreover, natural-food colorants are a renewable option providing health benefits and interesting technological and sensory attributes to the food systems containing them. Several sources of natural colorants have been explored aiming to deliver the required wide color range demanded by consumers. This review aimed to compare and discuss the technological applications of the main natural-food colorants into food system in the last six years, giving additional information about their extraction process. Although natural colorants are promising choices to replace synthetic ones, optimization of processing conditions, research on new sources, and new formulations to ensure stability are required to equate their properties to their synthetic counterparts.

1. Introduction

Modification or preservation of the visible appearance of foods is perhaps one of the main applications of natural or artificial colorants [ 1 ]. Although the food ingredient industry is more devoted to develop synthetic colorants due to their stability, attractive color, and low cost, natural food-colorants are gradually being preferred due to the changing consumers’ lifestyle and increased concerns about potential adverse health effects and environmental damage caused by synthetic colorants [ 2 ]. For instance, some synthetic colorants have been linked to allergic reactions in susceptible individuals and six of them (tartrazine E102, quinoline yellow WS E104, sunset yellow FCF E110, carmoisine E122, ponceau 4R E124, and Allura red AC E129) are associated to increased hyperactive behavior in children [ 3 ]. Moreover, the use of natural colorants can provide technological and bioactive functionalities to those foods in which they are applied, delivering additional value-added properties [ 4 ].

Nowadays, natural-food colorants have found their niche for valuable food applications. Single-phase coloring systems such as baking products (solid phase) or drinks (liquid phase) have been successfully assayed with natural colorants such as carotenoids or anthocyanins (ANC) [ 5 ]. In addition, as genetical modification have been explored to increase the concentration of natural colorants in plants, there is more interest in using these procedures to increase the plants’ production yield of colorants and find more suitable applications to be used in food applications, together with technological treatments aiming to stabilize these colorants [ 6 ].

Different natural colorants have been commercially exploited and approved for their use in the USA and the European union such as ANC (grape skin extract, grape color extract, berry fruit juice, or carrot and cabbage juices), carotenoids (annatto from Bixa orellana L., astaxanthin from Paracoccus carotinifaciens or Phaffia rhodozyma ; b-carotene from carrots, carrot oil, corn endosperm, and bell pepper from Capsicum annuum L.), chlorophyls from alfalfa ( Medicago sativa ), curcuminoids from turmeric ( Curcuma longa L.), betalains from beet ( Beta vulgaris L.) powder, carminic acid from cochineal ( Dactylopius coccus ) extract, and caramel from heating of sugars [ 7 ]. Beyond these sources, novel plants and plant-based materials and fruits, microorganisms, and insects have been considered for such purpose [ 8 ]. Colorants can be added to food systems after a technological extraction or could be part of the colored raw material. However, as some of the natural bioactive compounds that chemically constitute these colorants can be lost due to the matrix storage and processing conditions, some of them can be encapsulated to take advantage of their technological and biological properties [ 9 ]. In addition, encapsulated colorants are easier to handle and often exhibit enhanced physicochemical properties such as better solubility, stability, and flow properties [ 10 ]. The preservation of their coloring properties can be achieved by adding biopolymers such as heat-denatured whey protein isolate to reduce ANC complexation with ascorbic acid [ 11 ]. Other mechanisms involve using glutathione, dihydrolipoic acid, cysteine, and cysteine-derivatives to anchor anthocyanidins; sugars and calcium carbonate as pH-modifiers; aromatic acyl groups to acylate the 3′ position of the anthocyanin, or metal ions to form ANC-anthocyanidins complex suspended un polysaccharide matrices [ 12 ].

Food colorants play a crucial role in food production, masking unpleasant attributes or enhancing the food products’ natural properties [ 1 ]. Therefore, based on their color, they can also be used for specific purposes. For instance, ANC are highly common water-soluble flavonoids exhibiting pH-dependent colors from red to blue, and recognized by several bioactive properties such as antioxidant, anti-inflammatory, hypoglycemic, and chemopreventive effects [ 13 ]. Carotenoids are highly appreciated for their red, orange, and yellow color, primarily fruits and vegetables, contributing to desirable flavors in food and beverages [ 14 ]. Betalains are other type of colorants that have proven to be the most promissory candidates to replace Allura Red AC (Red 40), a synthetic colorant that contains benzidine, a potential human and animal carcinogen [ 15 ].

In this review, we compare and discuss some of the most recent findings in the last six years regarding the technological use of natural colorants in food systems, not only at a commercial, but also at an experimental level, providing a larger perspective on the functional aspects of colorants to be extensively used in the food industry, primarily aiming to increase the organoleptic value and enhance the natural color of food products. Furthermore, a brief description of the most important natural pigments used in the food industry and the industrial methods of production are also covered.

2. Natural Pigments Used in the Food Industry

Despite the wide range of natural pigments than have been used in the food industry, ANC, carotenoids, phycobiliproteins, betalains, and chlorophylls remain as the most commonly used for food applications. Some representative chemicals structures from these natural colorants are depicted in Figure 1 .

Representative chemical structures from the most common types of natural colorants applied in food systems. The chemical structures were downloaded from https://pubchem.ncbi.nlm.nih.gov (accessed on 21 February 2021). Chemical structures from phycobiliproteins were adapted from Hsieh-Lo et al. [ 16 ] with permission of Elsevier or applicable copyright owner.

2.1. Anthocyanins (ANC)

Anthocyanins (from Greek anthos , meaning flower and kyáneos meaning dark blue), are water-soluble vacuolar polyphenolic pigments members of the flavonoid group. Their presence in different plant organs gives the leaves, flowers, and fruits colors from red-orange to blue-purple [ 17 ]. Their basic structure is a flavan nucleus consisting of two aromatic rings: benzopyrylium and a phenolic ring joined by glucoside at carbon atom 3 of the benzopyrylium. ANC are considered the glycosylated forms of anthocyanidins since they are made up of an anthocyanidin molecule, the aglycone, to which sugar is bound through beta-glycosidic interactions such as glucose, galactose, rhamnose, and arabinose, commonly conjugated to the C3 hydroxyl group in the C-ring ( Figure 1 ). The instability of anthocyanidins causes ANC to be found almost exclusively in their glycosylated form [ 17 , 18 ]. The presence of conjugated bonds in ANC results in red, blue, and purple colors, mainly depending on pH conditions [ 19 ].

What differentiates ANC from each other is the number of hydroxyl groups in the molecule, the degree of methylation of these hydroxyl groups, the nature and number of sugars bound to the molecule, their position of binding, and the nature and number of aliphatic or aromatic acids attached to the sugars [ 18 ]. The prevalent ANC forms in nature are six and represent ~90% of all ANC identified to date: pelargonidin, cyanidin, peonidin, delphinidin, petunidin, and malvidin. All of them are synthesized in plants by the phenylpropanoid pathway [ 17 , 20 ]. ANC are a very popular natural food-colorants susceptible to several pH-dependent color gradients, used in very popular foodstuff such as beverages, desserts, ice cream, and dairy products [ 12 , 21 ]. Some commercial ANC are grouped by E163 food additive, a purple colorant derived from grape skin, such as cyanidin (E163a), delphinidin (E163b), malvidin (E163c), pelargonidin (E163d), peonidin (E163e), petunidin (E163f), grape skin extract (E163ii), ANC mixture (E163ii), and blackcurrant extract (E163iii) [ 19 , 22 ]. Among the major health properties associated to ANC are its anti-cancer activity linked to chemopreventive and chemoprotective effects in vivo and in vitro in several cancer cell lines [ 23 ], antioxidant, and anti-inflammatory benefits [ 24 , 25 ].

2.2. Carotenoids

Based on their functional groups, carotenoids are classified in xanthophylls (oxygen-containing groups: β-cryptoxanthin, lutein, and zeaxanthin) and those having just carbon chains (α-carotene, β-carotene, and lycopene, among others) ( Figure 1 ). Due to their hydrophobicity, they are mainly extracted using organic solvents, and depending on the natural source, the raw material might require a series of pretreatment stages [ 21 ]. Together with technological features (yellow, orange, and red color shades), most of them provide health benefits. For example, lycopene, a bioactive red colored pigment naturally found in red fruits, provides antioxidant properties with interesting health benefits linked to reduced cancer, cardiovascular disease, or diabetes risk [ 26 ]. Vitamin A is an essential carotenoid required for a plethora of metabolic purposes in the human body (immunity, growth development, and vision) [ 27 ]. Lutein and zeaxanthin provide ocular benefits and could improve the cognitive performance in elderly populations [ 28 ]. Alternative sources of carotenoids are microalgae, e.g., Dunaliella algae produce β-carotene under stress conditions, whereas Haematococcus pluvialis can produce astaxanthin [ 29 ]. Fucoxanthin is one of the most abundant carotenoids in nature, mainly extracted from brown macroalga such (class Phaeophyta: Undaria , Sargassum , Laminaria , Eisenia , Alaria , Cystoseira , and Hijikia ), exhibiting interesting properties in those food products in which has been added, such as photoprotective, anti-obesity, anti-inflammatory, neuroprotective, anti-diabetic, antioxidant, and anti-cancer effects [ 30 ].

Some of the major technological applications of carotenoids include meat products (sausages), vegetable oils, and butter. Carotenoids are recognized as GRAS by several regulatory agencies such as the Food and Drug Administration (FDA) and the European Food Safety Authority (EFSA). However, acceptable daily intake (ADI) has been proposed for lutein (1 mg/kg body weight, BW/day), lycopene (0.5 mg/kg BW/day), zeaxanthin (0.75 mg/kg BW/day), β-carotene (<15 mg/kg BW/day), bixin (6 mg/kg BW/day), and norbixin (0.4 mg/kg BW/day) [ 27 ]. Their use as colorant additives and functional ingredients is challenging due to their water insolubility, instability, and low bioavailability, and suitable alternatives have been developed, such as carotenoid delivery in water-dispersible products, colloidal suspensions, emulsions, and colloidal dispersions [ 31 ].

2.3. Betalains

Betalains are water-soluble pigments chemically based on nitrogenous-functional groups ( Figure 1 ), classified into red violet betacyanins and yellow betaxanthins. The being betanin obtained from red beetroot ( Beta vulgaris ) was the first FDA-approved betalain [ 21 ]. Betanins are used in confections, ice cream, yogurt, ready-made frostings, cake mixes, and beverages, among other applications [ 32 ]. However, betalains extracted from plants like cactus pear ( Opuntia ficus-indica L. Mill. cv. “Gialla”: proline-betaxanthin, γ-aminobutyric acid-betaxanthin, C 15 -stereoisomers betanin/isobetanin, and 2-decarboxy-betanin) , Celosia argentea (miraxanthin-V or dopamine-betaxanthin, 3-methoxytyramine-betaxanthin, and (S)-tryptophan-betaxanthin), ulluco (Ullucus tuberosus Caldas: phyllocatin, gomphrenin III, betanin, and vulgaxanthin) [ 33 ], and Stenocereus sp. have been characterized [ 34 ].

Several technological efforts have been made to use betalains in food systems. However, these pigments are highly light- and high-temperature sensitive and might deliver an unappealing earthy taste to food products [ 8 ]. Nonetheless, betalains display higher water solubility, increased coloring potential, and better neutral pH-stability compared to ANC [ 21 ].

2.4. Other Pigments Potential Used in the Food Industry

Chlorophylls are pigments widely distributed in green fruits and vegetables, structurally composed by a porphyrin ring chelated (intramolecular bond) with a magnesium atom. Chlorophyll also contains a fifth ring beyond the four pyrrole-like rings and a chain of propionic acid esterified with phytol (C 20 H 39 ) ( Figure 1 ). The main chlorophylls found in plants are a and b in a 3:1 proportion in chloroplasts [ 35 ]. Chlorophylls exhibit several derivatives depending on high temperature, oxygen availability and changes in pH (pheophytins, chlorophyllides, phephorbides, piroderivatives, chlorin-type derivatives, and other allomerized compounds). Chlorophylls could exert biological activities such as antioxidants, antimutagenics, and anticancer activities [ 36 ]. In the food industry, chlorophylls are identified as E140i colorant and copper-chlorophylls as E141i colorant. The corresponding water-soluble forms, chlorophylins (E141ii) and copper-chlorophylins (E141ii) are also marketed. However, one of the most used chlorophyll sources is the Spirulina extract, which has approved use in the USA (spirulina from Arthrospira platensis ) to be added to confections, frostings, ice cream, and frozen desserts, beverage mixtures and powders, yogurts, custards, puddings, among other food applications [ 37 ].

Phycobiliproteins are another source of blue-protein pigments, more stable compared to ANC at pH beyond the blue-range for these latter compounds (pH: 5–7) [ 16 ] ( Figure 1 ), although ANC are more stable at acidic pH. This photosynthetic pigment is formed by fluorescent phycobiliproteins attached to the thylakoid membrane of the algae chloroplasts and chemically are built up of chromophores (bilins or open-chain tetrapyrroles) linked to thioether covalent bonds to an apoprotein [ 1 ]. Phycobiliproteins are classified into three categories: phycoerythrin (red color), phycocyanin (blue color), and allophycocyanin (bluish green color), and consist of a protein-pigment complex [ 38 ]. Phycobiliproteins can be extracted from Spirulina ( A. platensis ) phycobiliproteins, stable at pH 5.0–7.5 (25 °C) and predominantly used for color confections, gum, dairy products, and soft drinks. However, pH-stable solutions are being explored to expand their use [ 21 ]. Moreover, phycobiliproteins are very thermolabile, losing their color intensity at 60 °C for 30 min in neutral solutions. Technological approaches such as high-pressure processing have been used to pasteurize beverages at low temperatures as an alternative for using these pigments [ 39 ].

3. Industrial Methods of Production

3.1. electric field-based technologies.

Electric field (EF)-based technologies are emergent processes with the potential for the rapid and uniform thermal treatment of materials. Ohmic heating (OH) and pulsed electric fields (PEF) are included in this category. Although it is not common to use these methods to extract natural colorants, some studies have addressed the potential of EF on the stability, functionality, and application of biomolecules. In addition, the electric field’s non-thermal effects (mainly electroporation) seem to enhance the extraction of compounds [ 40 , 41 ].

3.2. Ohmic Heating

With this method, an alternating electrical current is passed through a material. Consequently, the material is internally heated from the core to the outer material’s surface due to the food’s electrical resistance [ 42 ]. This feature is the main innovation of OH, making it a highly energy-efficient process suitable for rapid and uniform plant material processing. Using this technology, plants are not over-processed, and minimal changes in phytochemicals and color are produced [ 43 ].

Previous studies have used OH to extract phenolic compounds, mainly ANC, from different plant tissues [ 40 , 41 , 44 , 45 , 46 ]. The best conditions to extract polyphenols from wheat bran using OH were set at 20 V/cm, 80 °C, and 10 min, using water instead of the solvents commonly used to extract phenolic compounds [ 1 ]. A recent study also evaluated the extraction yield of ANC from Solanum tuberosum L. var. Vitelotte, a colored potato with blue and violet tones, using OH at different temperatures and voltages [ 40 ]. An 85% recovery of total anthocyanidins (TA) was achieved at 90 °C and 15 V after 10 min holding time, compared with a conventional thermal treatment that yielded 73% recovery. This effect depended on the time and temperature applied, but enhanced by the non-thermal effects that might cause the potato tissues’ permeabilization due to an electroporation phenomenon [ 40 , 47 ]. The main pigments extracted from potatoes were petunidin glucosides, malvidin, and delphinidin, responsible for the purple color. Given the antioxidant nature of ANC, this extract may be a functional colorant in foods and beverages, although its stability has not yet been studied.

A colorant powder was obtained from black rice bran ( Oryza sativa L.) with ohmic heating-assisted solvent extraction [ 45 ]. The colorant yield obtained (up to 20.63%) was significantly higher compared to a steaming extraction process (17.64%). Dark purple ANC (cyanidin-3-O-glucoside or C3G, delphinidin, cyanidin, and pelargonidin) were successfully extracted with OH, and tocopherols such as γ-Oryzanol. Moreover, the solubility and color of the powder were not affected by the OH process; essential parameters used when evaluating the feasibility of a method for industrial applications. ANC extraction was enhanced by the electric field that causes cell wall permeabilization, allowing a higher and homogeneous release of intracellular components [ 41 ]. This effect was also observed for ANC ethanolic extraction from red grape pomace after OH application [ 41 ], with a 36% yield at 400 V/cm.

By-products such as peels and vine pruning residues (VPR) can also be used as sources of colorants. VRP is a good source of polyphenols. The OH technology has been used to obtain ethanol-water polyphenol extracts from this material (840 V/cm, 80 °C and 60 min extraction). Moreover, VP extracts may have beneficial effects on health such as antioxidant capacity, antimicrobial and anticancer activity against several cancer cell lines including HepG2, MDA-MB-231, MCF-7, and Caco-2 [ 48 ].

Color stability is an important feature when evaluating the feasibility and application of industrial systems. Processing conditions significantly affect this stability, as reported for ANC, carotenoids, and fungal pigments exposed to OH. Typically, the OH methods reach a temperature higher than 70 °C, at which phenolic compounds degrade. As shown for blueberry ( Vaccinium spp.) pulp treated by OH, ANC degradation depends on the temperature-electric field combination [ 6 ]. At high voltages (>200 V), degradation was larger than the observed with conventional heating, and depended on the total solids content. In another study, a red extract produced by Penicillium purpurogenum GH2 incorporated in a beverage model system was processed with OH for microbial inactivation at 30 V and 0–80 min holding time [ 49 ]. The degradation kinetics showed lower stability for the samples treated with OH compared with conventional pasteurization. These observations indicate that the thermal effect and the concomitant influence of electric field and matrix compositions must be taken into account to maximize ANC yield and stability.

3.3. Pulsed Electric Fields (PEF)

This non-thermal technology uses high electric voltage in the 5–50 kV/cm range applied to food in short pulses (<1 s). Electroporation is the main accepted phenomenon occurring throughout the PEF process. Once the electric field is applied, it modifies the trans-membrane potential due to the accumulation of charges, which leads to membrane disruption and the release of intracellular components [ 50 , 51 ]. Since processing time is brief, degradation of bioactive compounds and natural colorants is expected to be minimal. However, several studies demonstrate that temperature, electric field strength, and time must be controlled to assure natural colorants’ optimal extraction.

Several works have extracted colorants from diverse plant species. A method based on PEF extraction of ANC was optimized for Beibinghong ( Vitis amurensis Rupr.) [ 52 ]. The optimal conditions were found with a response surface model: four pulses at 15.08 kV to recover 166 mg ANC. In another work, PEF pretreatment for aqueous and ethanolic extraction was tested for the recovery of ANC from purple-fleshed potato ( Ipomoea batatas L.) [ 53 ]. Processing time was the variable with the greatest effect on ANC yield, whereas electric field strength and temperature improved cell permeability. PEF allowed the use water as a solvent and decreased the temperature and processing time to obtain a similar ANC yield than the untreated samples (higher temperature and using ethanol as solvent) due to the cell permeabilization effect caused by the PEF pretreatment.

Other colorants, including betalains, astaxanthin, chlorophyll, and β-phycoerythrin, have also been extracted with PEF [ 54 , 55 , 56 , 57 ]. Betalains were extracted from red beet ( Beta vulgaris L.) using PEF-assisted aqueous extraction [ 54 ]. With PEF, the maximum recovery (95%) and the minimal color degradation (10%) were reached at low temperature (30 °C), whereas the untreated samples needed higher temperature to reach >80% yield. In other study, PEF were used to disrupt microalgal biomass ( Haematococcus pluvialis ) and extract astaxanthin (pink/red color carotenoid) [ 55 ]. Applying 10–80 pulses of 5 ms at 0.2–1 kV/cm for 6 h, it was possible to observe a twofold increase in the colorant yield compared with the untreated sample. The solvent used had an important influence on the colorant recovery, methanol and ethanol were the best diluents in this experiment. In parallel work, the authors extracted β-phycoerythrin, a water-soluble red colorant present in the microalga Porphyridium cruentum [ 56 ]. This compound can be used in the food, cosmetic and pharmaceutical field. Interestingly, this study showed a strong correlation between the permeabilization percentage of cells treated by PEF and the extraction efficiency. Even at low intensities (~4 kV/cm), high cell damage was observed and allowed nearly a 100% recovery of β-phycoerythrin when followed by a 24 h incubation in citrate-phosphate McIlvaine buffer. These studies show the importance of testing the specific conditions to maximize cell permeabilization before colorant extraction.

PEF have shown to be a suitable method to preserve chlorophyll stability extracted from spinach ( Spinacia oleracea L.) [ 14 ]. Once the colorant was extracted with an ethanol solution, PEF were applied to the chlorophyll extract with the following conditions: 0–26 kV/cm, 20–45 °C, and 0.32 ms as effective treatment time. The maximum chlorophyll recovery (14.62 mg/mL) was achieved at 35 °C and the highest electric field strength (26.7 kV/cm). The structural characterization by Fourier Transform Infrared (FT-IR) and X-ray (XR) diffraction showed a relatively higher stability after the PEF treatment. According to the authors, PEF induced chemical changes in the pyrrole ring and favored the formation of chlorophyll aggregates that increase the stability of the colorant. As observed, PEF can be used not only as pretreatment, but also as a method to increase or at least, to lessen colorant degradation.

3.4. High-Pressure-Assisted Extraction (HPE)

High-pressure-assisted extraction (HPE) obeys the isostatic principle, which states the process is volume-independent, or that pressure is transmitted instantaneously and uniformly throughout a sample, with no pressure gradients [ 58 ]. This methodology is characterized by using low or room temperatures, and pressure ranges from 100 to 600 MPa [ 59 ].

HPE is considered one of the most recent potential extraction techniques since heat is unnecessary, and therefore, the damaging effects on bioactive compounds are avoided, particularly to heat-labile compounds. As the pressure increases, there is a slight increase in temperature of 3 °C per 100 MPa, which is neglected because it is not enough to produce degradation by heat [ 60 ]. HPE has other advantages: faster extraction time from hours to minutes, lower solvent requirement, and the possibility of combining different solvents, higher extraction yields, increased extraction efficiency, and fewer impurities generation reason why it has been considered a green technology [ 59 , 60 ].

This methodology has become an attractive alternative for extracting bioactive compounds such as ANC since it avoids thermal degradation and oxidation reactions because of the absence of light and oxygen [ 61 ]. To mention some examples, in our workgroup, Luna-Vital et al. [ 62 ] described the ANC extraction from purple corn pericarp by using HPE. The solvent chosen for the extraction was deionized water and the process was carried out at a temperature of 50 °C for 5 min at 10.34 MPa of pressure. The extract was obtained successfully containing: C3G (45.8%), cyanidin-3-(6′-malonylglucoside) (C3G-Mal) (17.2%), a condensed form of flavanol-ANC (16.8%), peonidin-3-O-glucoside (P3G) (9.3%), peonidin-3-(6′-malonylglucoside) (P3G-Mal) (3.1%), pelargonidin-3-(6′-malonylglucoside) (Pr3G-Mal) (2.4%), and pelargonidin-3- O -glucoside (Pr3G) (2.0%). However, ANC were not the unique components of this extract since several phenolic acids were also extracted, such as ferulic, protocatechuic, caffeic, chlorogenic, and gallic acids [ 63 ]. Putnik et al. [ 64 ] evaluated the performance of the high hydrostatic pressure extraction (HHPE) on the recovery of ANC from the grape skin pomace extracts under moderate temperatures. In this case, two solvents were used (ethanol and methanol), the compression fluid was propylene glycol, and the conditions of the extraction process were the following: 300, 400, and 500 MPa of pressure for 3, 6.5, and 10 min at 22, 26, and 30 °C. The authors obtained, mainly, malvidin derivatives in two forms: malvidin-3-glucoside (2.33 mg/g) and malvidin-3- O -(6- O -acetyl)-glucoside (0.83 mg/g), representing 55.77% of overall ANC content. Followed by malvidin-3- O -(6- O -coumaroyl)-glucoside (0.66 mg/g) being 11.65%, the remaining ANC were found in amounts lower than 0.5 mg. Once analyzed the applied parameters, the ideal settings for the process were pressure 268.44 MPa, extraction time 3.39 min, and temperature 29.48 °C.

Haining and Yongkun [ 65 ] had the purpose of evaluating the influence of HHPE on the extraction of blueberry pomace ANC. The pressurizing fluid used was dioctyl sebacate, and the chosen solvents were ethanol and hydrochloric acid. The extraction process was carried out under different pressures (100 and 600 MPa) and holding times (5 and 30 min) at room temperature. According to their optimization model, the significant extraction parameters were a liquid-solid ratio of 41 mL/g, ethanol concentration of 63%, and extraction pressure of 443 MPa. The non-significant parameters such as hydrochloric acid concentration, holding time, and extraction cycles were fixed at 0.185%, 5 min, and 1 cycle, respectively. At the optimal HHPE conditions, 107.9 mg/100 g of ANC were obtained, and 10 ANC were identified, being malvidin-3-galactoside and malvidin-3-glucoside the main ones.

3.5. Supercritical Fluid Extraction (SFE)

Supercritical fluid extraction (SFE) is a process used for separating one component, named the extractant, from another known as the matrix, using supercritical fluids as the extracting solvent [ 66 ]. The conditions of these fluids are above their critical point of pressure and temperature, their density is similar to liquids, their viscosity is comparable to gases, and their diffusivity is between both gases and liquids [ 67 ]. The main advantage of a supercritical fluid is that its density can be modified by changing its pressure and temperature. The properties mentioned earlier allow supercritical fluids to penetrate deeper and faster to solid matrices because they diffuse easily through them [ 67 , 68 ].

Carbon dioxide (CO 2 ) is the most commonly used solvent due to its low cost, safety, and moderate critical temperature (31.2 °C) that enables the preservation of bioactive compounds in extracts [ 67 , 69 ].

Other remarkable advantages in comparison with standard extraction techniques are the use of solvents generally recognized as safe (GRAS), lower extraction times, increased yields meaning higher efficiency of the extraction process, and the option of direct coupling with analytical chromatographic techniques such as gas chromatography (GC) or supercritical fluid chromatography (SFC) [ 68 ]. Jiao and Kermanshahi [ 70 ] obtained ANC extracts from Haskap berry ( Lonicera caerulea ) pulp by SFE. Likewise, the authors carried out the extraction of ANC by the conventional method using water, intending to compare the yields obtained. A relevant aspect of this work was the combination of water and CO 2 . The highest total ANC yield (52.7%) from berry pulp paste using CO 2 was achieved using 45 MPa, 65 °C, 5.4 g water to 3.2 g paste, 15 min static, and 20 min dynamic time. In conclusion, compared with conventional extraction, using CO 2 as solvent and water use as co-solvent offered higher ANC extraction efficiency (52.7% vs. 38.3%).

The recent work conducted by Idham et al. [ 71 ] aimed to evaluate the effects of different particle sizes, flow rates, and modified ratios on the extraction yield and ANC content of Roselle ( Hibiscus sabdariffa ) by using the supercritical carbon dioxide (SC-CO 2 ) method. The pressure and temperature were kept constant at 10 MPa and 70 °C respectively, and 75% ethanol was used as a modifier. Different solvent flow rates were studied: 4 mL/min, 5 mL/min, and 6 mL/min. Three different ground dried Roselle sizes were used: 200–355 μm, 355–500 μm, and 500–710 μm. Finally, three percentages of modifiers ratios were compared: 5%, 7.5%, and 10%. The effect of these three parameters showed different results of overall extraction yield and total anthocyanin content (TAC), demonstrating that these conditions are key to obtain the highest ANC concentration. The optimal parameters that allowed reaching the highest ANC concentration were extraction time of 120 min, flow rate of 4 mL/min obtaining a TAC of 5 mg equivalents of C3G (EC3G)/L, particle size of 200–355 μm showing a TAC of 4.95 × 10 4 mg EC3G/L, and a 10% of modifier ratio obtaining a TAC of 3.84 × 10 4 mg EC3G/L. A summary of the primary outcomes from reported industrial extraction technologies of natural colorants is presented in Table 1 .

Main outcomes from reported industrial extraction technologies of natural colorants.

ANC: Anthocyanins.

4. Technological Properties of Natural Food Colorants in Food Systems

Several food colorants have been isolated from diverse sources to be applied in food systems. An overview of some of the most important food systems in which natural colorants are applied is presented in Figure 2 .

Natural colorants in food systems. Figures reprinted from Abdel-Moemin et al. [ 73 ], Amjadi et al. [ 74 ], Carballo et al. [ 75 ], da Silva et al. [ 76 ], de Amarante et al. [ 77 ], Freitas-Sá et al. [ 78 ], Jiménez-López et al. [ 79 ], Rodríguez-Sánchez et al. [ 34 ], Sharma et al. [ 80 ] with permission of Elsevier, MDPI A. G., or applicable society copyright owner.

4.1. Bakery Products

Purified colorants or plant extracts have been used to improve bakery products’ nutritional properties without a major sensory impact. As such, Abdel-Moemin et al. [ 73 ] reported an enhanced chemical composition and high overall liking scores from cupcakes added with 20 g Roselle ( Hibiscus sabdariffa L.) calyces extract/100 g cupcake, commonly used in the preparation of beverages. This functional extract was prepared with dry calyces to produce a fine powder (0.55 mm) mixed with water and then boiled for 1 h (80 °C). The formulated cupcakes showed lower total carbohydrates (−11.28%) and lipids (−16.48%), while higher dietary fiber (126.18%) and ash (179.68%) than the control cupcakes (without Roselle). Moreover, Roselle-added cupcakes retained 77% of the total ANC content from the dry calyces (435 mg/100 g cyanidin-3-glucoside), potentially providing up to 32-fold the minimum daily intake from Americans (12.5–215 mg). Although the resulting cupcakes displayed a crust and crumb pink color due to surface Maillard reactions developed during the baking process (175 °C for 20 min), no differences ( p > 0.05) were found for the sensory evaluation of the color, appearance, texture, taste, volume, and aroma compared to control cupcakes, but received a lower liking.

Jiménez-López et al. [ 79 ] assessed the feasibility of a C3G extract from Arbutus unedo L. fruits to be incorporated into wafers. An optimized heat-assisted extraction was used to obtain an antioxidant C3G-rich extract with antioxidant potential (2,2-diphenyl-1-picrylhydrazyl or DPPH half-maximal effective concentration, EC 50 : 295 μg/mL and β-carotene EC 50 : 901 μg/mL) with anti-bacterial properties ( Salmonella enteritidis minimum inhibitory concentration (MIC): 150 μg/mL; Salmonella typhimurium minimum bactericidal concentration (MBC): 200 μg/mL). The extract exhibited the highest stability at T < 20 °C and pH > 3.5. When added to wafers, the prepared product showed a golden color, higher sucrose amount, increased concentrations of fatty acids (palmitic, stearic, and linoleic acids), and improved antioxidant capacity compared to the untreated wafers.

Fruit and vegetable waste can also be a source of colorants. Tomato waste was employed as a lycopene source to be used in cakes and cookies [ 26 ]. Lycopene from tomato waste (fibrous pulp without peel and seeds) containing 654.8 mg/100 total carotenoids and 300.85 mg/100 g lycopene. Oil from the cake’s formula and butter from the cookies’ ingredients was replaced with 1%, 3%, and 5% lycopene, and the resulting products were evaluated. Lycopene-containing cakes showed a dose-dependent volume increase, higher DPPH inhibition, and increased crust and crumb’ lightness, but only 5% formulation showed a higher volume than control cakes (without lycopene). Sensory evaluation of the cakes showed significant differences in crust and crumb’s color and texture (cakes were perceived as more yellow and redness than control cakes). Still, no differences were found among panelists for taste, odor, and overall acceptability. The same outcomes were found for the lycopene-added cookies.

Beetroot ( Beta vulgaris L.) pomace was used as a source of betacyanin and betacyanin-derivatives extract, further encapsulated and used in pseudocereals (amaranth, buckwheat, and quinoa)-enriched wheat einkorn ( Triticum monococcum ) water biscuits. Independently of the pseudo-cereal, all extract-added biscuits showed a dose-dependent betanin, isobetanin, and betanin-derivatives increase (5.7%, 10.4%, 14.9%, and 10.8% extract addition) compared to control biscuits. Buckwheat ( Fagopyrum esculentum ) biscuits displayed the highest total phenolic compounds (TPC) content (~2500 mg gallic acid equivalents or GAE/kg dry matter, DM), ferric ion reducing antioxidant power (FRAP), and 2,2′-azino-(bis-ethylbenzothiazoline-6-sulfonic acid) (ABTS) values (~18 and 14 mmol Trolox equivalents/kg DM, respectively). Quinoa ( Chenopodium quinoa ) biscuits showed the highest furosine contents (~275 mg/100 g protein), suggesting a lower ability of the encapsulated extract to prevent heat damage for this ingredient.

Rubus ulmifolius Schott has been investigated as a novel source of food colorants incorporated in bakery products [ 76 ]. Heat-assisted extraction was conducted to produce an ANC-rich extract, and the main identified ANC (cyanidin- O -di-hexoside, C3G, Pr3G, cyanidin-3- O -xyloside, and cyanidin-3- O -dioxayl-glucoside) were used as responses for a Response Surface Analysis (RSM). The extract contained 33 mg ANC/g extract and showed a red-burgundy color. When added to donuts, lightness and yellowness (b*) decreased (−24.34 to 25.97% and −44.67 to 48%, respectively), but the redness was increased (+109 to 338.67%) when compared to control donuts. The formulated donuts also showed lower carbohydrates and energy value contents, higher free sugars values ( p < 0.01), and no differences were found for the free fatty acids content.

Albuquerque et al. [ 81 ] optimized a heat- and ultrasound-assisted ANC-rich extract from jabuticaba ( Myrciaria jaboticaba (Vell.) Berg) epicarp as a natural colorant to be used in the manufacturing of french macarons. Heat-assisted extraction proved to be the most successful extraction using delphinidin-3- O -glucoside and cyanidin-3- O -glucoside levels as responses. The resulting macarons (13 min at 130 °C, conventional oven) showed lightness (L*), redness (a*), and yellowness (b*) preservation (overall −0.05% change) up to six days of storage, while low glucose, fructose, and sucrose changes were observed during the same evaluation period.

Several reports have informed the potential of whole food products for coloring or technological properties. For instance, colored tubers such as purple-fleshed sweet potato ( I. batatas L.)-colored flours were used in biscuit formulations [ 82 ]. Although no colorants were mainly extracted from the raw materials, the flour contained high TPC (80.89 mg GAE/100 g) and TAC (38.90 mg C3G equivalents/100 g). Despite 67.24% TPC and 27.79% TAC were retained in the biscuits, respectively, due to compound losses during the baking process (160 °C, 20 min, electric oven), potato-supplemented biscuits exhibited TPC: 2.27- and TAC: 10.82-fold increase, compared to control biscuits. The enhanced nutritional composition yielded high FRAP and DPPH levels.

Similarly, Croitoru et al. [ 83 ] partially replaced wheat flour with black rice flour to manufacture muffins. The 50% and 100% black rice formulations showed an outstanding TPC, total flavonoids (TF), and TAC contents, compared to wheat-only muffins, which was reflected on the antioxidant capacity (up to four-times compared to control muffins). No differences were found ( p > 0.05) for the overall acceptability of the novel muffins, showing a beneficial potential of colored ingredients to improve the nutritional composition without a negative impact on the sensory parameters.

In summary, natural food-colorants can be used to positively impact the crust and crumb’s color from several bakery products, producing a pleasant flavor and interesting health-added benefits, mainly antioxidant properties. However, most researchers have not evaluated these properties at in vivo level but in vitro tests using assays that hardly mimics the antioxidant levels found in organisms [ 84 ]. Moreover, more research is needed evaluating the impact of the processing conditions at which bakery products are subjected (high temperature, low moisture, among others) in the dyeing properties of natural food-colorants. Hence, encapsulation might be a suitable technological advantage using proper wall materials allowing colorants to exert their function but also preserving their healthy characteristics.

4.2. Beverages

Consumers usually associate the beverages’ colors from natural sources such as yellow for lemons or red for strawberries, to mention some examples. Hence, color is a critical feature with the potential to enhance their appeal and acceptability [ 85 ].

Most beverages require colorants since food processing contributes to substantial color loss. Thus, various food and non-food natural sources can be used as materials to isolate functional colorants, retaining stability and shelf life. Commercial purple carrot ANC (0.025%) combined with green tea extract rich in epigallocatechin gallate (EGCG) showed high stability to ANC degradation and delayed half-life of ANC from 2.62 days to 6.73 days in first-order reaction kinetics [ 13 ]. These protective effects provided by the green tea extract are a consequence of EGCG protection over ascorbic acid condensation or oxidation by hydrogen peroxide, allowing even higher stability at increasing temperatures (from 25 °C to 40 °C).

Cyclodextrins are cyclic molecules used as encapsulants of flavors, vitamins, colorants, and ingredients, increasing their shelf-life and promoting controlled release for technological or physiological features such as improved bioaccessibility, and antioxidant capacity [ 86 ]. Particularly for beverages, it can be used for co-pigmentation purposes, stabilizing highly degradable pigments. For example, black bean coats anthocyanin-rich extracts were stabilized with 2% β-cyclodextrins to manufacture a model sport beverage [ 87 ]. The extracts were prepared using coats from two black beans ( Phaseolus vulgaris L.) varieties (“Negro Otomi” and “Idaho” cultivars) after an optimized pH-adjusted aqueous ANC extraction (40 °C for 4 h). High destruction values were obtained for the ANC powders and coat extracts (9.51–119.93 days), but encapsulation with β-cyclodextrin retarded their degradation (up to 43 months). β-Cyclodextrin widely used as additive to protect colorants from environmental conditions. The addition of the β-cyclodextrin-encapsulated extracts to a sports beverage extended ANC half-life (up to 13 months) and reduced color differences under darkness at 4 °C.

Beverage models can be used to evaluate the stability of natural colorants at varying pH, acidity, and other environmental conditions. Rodríguez-Sánchez et al. [ 34 ] evaluated pitaya ( Stenocereus pruinosus ) betaxanthins (betalain-type pigments) extracts in a model yellow beverage, obtaining a highly disperse chroma (21.38–87.78) and hue (53.9–87.8) values and several shades of yellow-orange. However, beverages pigmented with 5% pitaya juice were those with the most similar color to their commercial counterparts (color difference ΔE = 9 vs. control beverage). Formulated beverages retained up to 75% of total betaxanthins during the first nine days of storage. The authors suggested the ability of this pigment to substitute synthetic yellow pigments in commercial beverages.

Lobo et al. [ 88 ] encapsulated yellow bell pepper pigments with β-cyclodextrin and evaluated their stability in isotonic beverages (pH: 2.9; 0.02%, 0.05%, and 0.06% of extract addition). Lutein, zeaxanthin, α-cryptoxanthin, α-carotene, and β-carotene were the main carotenoids found. Extract-added beverages exhibited dose-dependent luminosity and redness increase but decreasing yellowness. No differences along time (21 days) were observed among the beverages for lightness, but yellowness significantly decreased ( p < 0.05).

Soft-drink beverage models were assayed to evaluate the stability of a vacuum-concentrated colorant extracted from yellow-orange cactus ( Opuntia ficus indica ) [ 89 ]. The extract (0.7% v/v ) was added to soft drinks (86 g/L sucrose, 0.14 g/L sodium benzoate, 0.18 g/L potassium benzoate, 0.02 g/L ascorbic acid, and 1.52 g/L citric acid, among other components). Indicaxanthin was the main identified betaxanthin (concentration: 256.53–264.86 mg indicaxanthin equivalents/kg). First-order reactions were fitted for betaxanthin degradation in the soft-beverage models, where the beverages’ pH (3.0) could influence the degradation as betaxanthin are stable at pH: 5.0. As suggested by the authors, this extract could also be used in chilled matrices such as yogurt and ice cream.

The yellow color is a very demanded pigment in the beverage industry, being carotenoids (bixin, lutein, and crocin), betalains (betaxanthins), flavonoids (carthamin), curcuminoids (curcumin), and riboflavins the most usual colorants [ 90 ]. An extensive evaluation of several yellow natural pigments (annatto from Bixa orellana L. seeds, gardenia yellow from Gardenia jasminoides Ellis, lutein from marigold flowers or Tagetes erecta L., curcumin from turmeric or Curcuma longa L., and safflower extract from Carthamus tinctorius L.) were evaluated in colored beverage model systems [ 91 ]. To simulate alcoholic and non-alcoholic beverages, McIlvaine buffer (pH: 3.5, 5.5, and 7.5; concentrations: 0.001, 0.005, 0.01, 0.02, 0.03, 0.05, 0.10, and 0.30% v/v ) with or without ethanol (15% v/v ), were prepared. Gardenia, safflower, and curcumin exhibited the highest color intensity and the lowest turbidity level, whereas safflower showed the highest heat (25, 40, 60, and 80 °C) and light (550 W/m 2 , 30 °C) stability.

Cyanidin-rich or pelargonidin-rich purple corn extract-added model beverages were tested for stability with and without a flavone-rich extract [ 92 ]. The cyanidin-rich beverages were more stable than pelargonidin ones, but a 50% increased half-life was obtained for both systems after adding the flavone extract. Together with their technological features, these extracts have also shown interesting biological properties in vitro and in vivo, playing a dual role in replacing artificial colorants and delivering potential health benefits [ 63 ]. Compared to extract-added-only beverages, the addition of alginate and zinc ions to these extracts protected ANC from degradation in a beverage model, improving ANC half-life (10.4 weeks), C3G concentration (7.5 weeks), and chroma (18.4 weeks) [ 62 ].

Gomes Rocha et al. [ 93 ] developed whey-based beverages containing ANC from jabuticaba ( Plinia cauliflora ) skins for protein beverages. Delphinidin-3- O -glucoside (D3G: 9.8 mg/L) and C3G (198.9 mg/L) were identified in the jabuticaba extract. The highest whey-containing beverages (4.0% and 6.0% w/v ) exhibited clearer colors, with no differences in a* and chroma parameters. The red color was predominant in the beverages. All beverages contained the same ( p > 0.05) ANC content (1.4–1.5 mg/100 g), but TPC and antioxidant capacity were whey dose dependent.

Jelly drinks were pigmented with encapsulated ANC pigments from purple sweet potato ( Ipomoea batatas L.) cv. Ayamurasaki [ 94 ]. The resulting beverage stored at 5 °C without light exposure showed the smallest ANC and redness decreased after 30 days of storage, while its calculated shelf-life was estimated in 200 days.

Among alga-derived sources, Porphyridium aerugineum microalga-derived blue color has been used for acidic beverages. These pigments display pinkish-red or blue color extracted by cell breakage using water or buffered solutions, centrifugated, purified, and sterilized by microfiltration, spray-drying, or freeze-drying [ 95 ]. The blue color is stable at pH 4.0–5.0 for 1 month at room temperature or up to 40 min at 60 °C. It can be added to acidic non-heat treated carbonated beverages (Pepsi ®® ) or low-grade alcohol beverages (Bacardi Breezer ®® ) [ 1 , 95 ].

Concluding, beverages are one of the most suitable models for studying the natural food-colorants’ shelf life since the aqueous media and processing conditions provide challenging conditions to test colorants’ behavior. Since beverages have been used to promote the consumption of vegetables and fruits as their intake remain below the recommended levels in many countries [ 96 ], colorants are also used to prevent beverages’ color loss during the thermal processing.

4.3. Confectionery

Confections belong to a very dynamic food industry sector with high demand for coloring agents. Several confections have been targeted as concerning due to cadmium and lead-based colors potentially causing brain glioma, urinary bladder and kidney tumors, or hypersensitivity [ 97 ].

Figs ( Ficus carica ) and blackthorns ( Prunus spinosa L.) extracts were used to manufacture beijinho , a condensed milk-based confection, and doughnut icing [ 98 ]. Peels from F. carica and the epicarp of P. spinosa were freeze-dried, milled (20 mesh), and ultrasound-assisted extraction was conducted, using 100 mL of acidified solvent (pH 3, citric acid). The peel was rich in cyanidin-3-rutinoside, while the blackthorns extracts were rich in cyanidin-3-rutinoside and peonidin-3-rutinoside. Both food products contained sucrose > lactose > fructose contents. Up to 21 fatty acids were identified in both foods, and palmitic acid was the most abundant (icing: 14%; beijinhos: 10%). Saturated fatty acids were the most relevant group (75%), followed by monounsaturated. Blackthorn-added products displayed intense purple colors, and figs-added products exhibited light tones.

A betaxanthin-rich extract from pitaya ( S. pruinosus ) was used to produce yellow gummies, showing disperse chroma values depending on the juice or pulp concentration (10.6–15.6 and 10.6–13.2, respectively), with shading varying from yellow to orange. Half of the pigment was lost after 11 days at 40 °C, and betaxanthins followed a first-order kinetic evolution [ 34 ]. Calcium alginate-encapsulated betalains from Opuntia ficus-indica (purple pulp) were added to gelatin-based gummies, and no differences in the color parameters (lightness, a*, and b*) were found after a 30 days-storage at 4 °C [ 99 ].

Saffron ( Cocus sativus ) and beetroot ( Beta vulgaris L.) aqueous extracts were encapsulated in maltodextrin, gum arabic, modified starch, and chitosan and incorporated in a chewing gum system [ 100 ]. Modified starch and other ingredients were used as wall materials to protect target pigments in food systems [ 101 ]. The luminosity from the chew gums decreased along time (25 °C and 40 °C storage), whereas a* almost disappeared after two-weeks’ storage at 40 °C. However, gum arabic and modified starch proved to be the best color stability mixture independently of the extracts, displaying the highest a* (for beetroot) and b* (for saffron) values.

Promising underutilized fruit products can be used as sources of varied colorants for the confection industry, despite a colorant not being extracted from these raw materials. Açaí ( Euterpe oleracea Mart.) was evaluated for its coloring properties in a chewy candy model [ 102 ]. The resulting candies had lower a w and no differences were found for the hardness or the moisture content than non-added Açaí candies. Higher color acceptance (4.34%) and the same texture evaluation were obtained for both non- and added-Açaí candies. Although the positive purchase intent was lower in the Açaí candies (−42.86%), high uncertainty in the purchase intent (166.7%) was observed in the Açaí testers, suggesting the potential of these candies to be acquired.

Dragees or hard-panning confections are elaborated by applying several layers of coating material such as saturated sugar syrup to produce a hard or crispy shell [ 103 ]. Most water-soluble pigments can be used in these confections, but as the panning syrup is prepared at temperatures higher than 80 °C to prevent recrystallization of sugar, the tested pigments require to preserve most of its properties at these working conditions [ 104 ]. Avelar et al. [ 105 ] explored the possibility of using by-products from Uvaia ( Eugenia pyriformis ), a native fruit from southeastern Brazil, as a low-cost coloring agent in hard panning confections. Coated confections exhibited the lowest a w and luminosity, but the highest a*, b*, and hardness than fruit-based concentrate- and artificial colorant-added candies. The best appearance and color attributes were obtained for the Uvaia-added candies, but they displayed the lowest crispness (6.61 score vs. 6.77 and 7.16 for fruit-based and artificial colorants).

Several pigments can be used to color jelly gummies, confections composed of sugars, gelling agents (pectin, agar-agar, gum arabic, gelatin, among others) and food-grade acids (citric or tartaric acids). For the yellow shades, Carthamus ( Carthamus tinctorius L.) has been used to provide a transparent appearance, but bright yellow can be reached using curcumin. However, these oily pigments need to be formulated using proper emulsion, suspensions, or encapsulation systems since curcumin exhibits poor stability [ 104 ]. For warmer color shades, carotenes can be applied to jelly gum from varied sources such as palm carotenes, resulting from the fungal fermentation of Blakeslea trispora , or those produced by the alga Dunaliella salina. Nonetheless, for another color, unconventional or underutilized fruit and vegetable sources can be used. Małgorzata et al. [ 106 ] reported the potential of black elderberry ( Sambucus nigra L.) extracts prepared from their flowers and fruits as dyes to manufacture healthy jelly gum confections. ANC such as cyanidin-3- O -sambubioside-5-glucoside, cyanidin-3,5-diglucoside, cyanidin-3- O -sambubioside, and cyanidin-3- O -rutinoside were identified in the extracts. However, the flowers exhibit a rich polyphenolic profile governed by quercetin derivatives (4.04 mg/g quercetin-3-rutinoside and 0.56 mg/g quercetin-3-glucoside) and chlorogenic acid (2.82 mg/g). The designed jelly gummies showed high FRAP (597.46–849.58 μmol Trolox equivalents, TE/g), DPPH (68.23–90.11% inhibition), and TPC (14.68–25.34 mg GAE/g).

Microalgae are an important source of natural pigments, containing macro and micronutrients with interesting biological properties that could add health benefits to natural colorants in confections [ 107 ]. For example, Genc Polat et al. [ 108 ] applied spray-dried encapsulated Nannochloropsis oculata microalga extract in white chocolate as a coloring agent. The obtained chocolate presented varied luminosity (61.6–78.0) and increased a* and hue compared to control chocolate samples. Although the alga-added samples showed lower scores for the appearance, texture, and smell, their values were not different ( p < 0.05) than the control samples.

The red microalga genus Porphyridium has proven to be a source of fluorescent phycobiliproteins with pigment properties on confections. The red or pink colorant can be added to transparent lollipops made from sugar solutions or dry sugar-drop candies for cake decorations, exhibiting high stability at 60 °C for 30 min and long shelf life at pH 6.0–7.0 [ 1 ].

Last but not least, adding natural food-colorants to confection opens an opportunity to diversify the functional confectionery market, reaching traditional population targets such as children, to deliver health benefits in low sugar formulations with increased nutritional properties. Functional confectionery no only relies on adding isolated natural food-colorants, but also food by-products with demonstrated beneficial nutritional composition such as high dietary fiber and antioxidant compounds contents [ 109 ].

4.4. Milk, Dairy, and Dairy-Like Products

Similar to other food products, natural food-colorants can be added to milk and dairy products to restore the natural color potentially lost during processing and storage or to reduce the batch-to-batch variations. Moreover, colorants can intensify natural colors in case they are weak, provide color to colorless products, and produce acceptable and attractive products for consumers [ 8 ]. Several researchers have used natural colorants in milk and dairy products for several purposes, such as those described above.

Dairy food matrices are challenging since colorants might affect some of their textural properties. Natural colors are usually preferred for yogurts due to their heat stability during processing and can be easily labeled as “vegetable color”. Some of the most common natural colorants used in yogurts are carmine from cochineal beetle (brilliant red color ranging from “strawberry” to “blackcurrant” color), annatto from Bixa orellana , ANC-rich extracts from mulberry ( Morus rubra ), red color from strawberries, and orange color from the carrot addition to yogurt [ 110 ]. Betacyanin pigments extracted from Ayrampo ( Opuntia soehrensii Britton and Rose) were used in 3% fat yogurt as natural colorants. After an optimized extraction and purification, betacyanins showed first-order degradation kinetics when subjected to heat treatment (80 °C for 90 min) at several pHs (3, 4, and 5) [ 111 ]. However, an average half-life of 272 days was obtained when betacyanins were stored at 4 °C, whereas a half-life of 26 days was shown for 25 °C storage. The application of this extract in yogurt (32–192 μg betacyanin/100 g yogurt) resulted in the lowest ΔE at 96 μg betacyanin/100 g, while greater values exhibited decreased L* values and higher ΔE, compared to commercial yogurt. Color stability during storage (up to 5 weeks) was similar to synthetic colorant Red no. 40 (>94%), and even higher than red beet extracts also applied to the same yogurts.

For example, natural curcumin (E100) was applied to a hydrophilic matrix represented by yogurt [ 112 ]. As curcumin exhibits poor water solubility and susceptibility to alkaline conditions, light, oxidation, and heat, encapsulation was also assayed. Diverse color changes (closer to organ color) were obtained from the formulations (4.75–5.25%), where water, protein, ash, galactose, energy, and b* were the dominant parameters having a discriminant effect among the samples. Stored yogurts for seven days displayed a* reduction, but overall color could be maintained a long time.

Pires et al. [ 113 ] incorporated natural colorants extracted from flowers such as Dahlia mignon , Rosa damascena “Alexandria”, Rosa gallica “Francesca”, and Centaurea cyanus L. Centaurea contained the highest amount of TAC (26 μg/g), and cyanidin-3,5-di- O -glucoside and cyanidin-3- O -(6′’-malonylglucoside)-5- O -glucoside were the most abundant ANC. Except for the galactose contents ( Centaurea was the highest), there were no differences ( p > 0.05) for the water, fat, protein, ash, carbohydrates, lactose, or energy contents and these parameters did not change during the seven-day storage of the yogurts. Furthermore, compared to a commercial colorant (E163), there were no differences in L*, a*, b*, or pH values.

Jabuticaba ( Myrciaria jaboticaba (Vell) O. Berg) and jamelão ( Syzygium cumini L. Skeels) peel powders were testes as colorants in yogurts [ 78 ]. Test consumers (106) participated in a matching task associating the manufactured yogurts with fruit flavor variants, and high dependence ( p < 0.01) between color and flavors of yogurts was found. For the sensory evaluation, Jabuticaba-added yogurts received the best appearance (6.6–6.8), flavor (6.9), and overall liking (6.8) scores among the flavored-yogurts. However, all values were lower ( p < 0.05) than the not-colored yogurt except for the appearance.

Benchikh et al. [ 114 ] optimized ANC extraction from strawberries ( Fragaria ananassa ) using the response surface methodology and applied the obtained colorant to yogurt. ANC’s optimal conditions were obtained for agitation speed of 586 rpm, and sample to solvent ratio of 1.26 g/40 mL, obtaining TAC: 38.04 mg C3G equivalents/100 g fresh weight, and 21.22 μg ascorbic acid equivalents/100 g yogurt for the antioxidant capacity (DPPH). The yogurts contained 10–40 μg/100 g TAC and a remaining red color after the manufacturing process (pH: 4.6, 4 °C), but no shelf-life evaluations were conducted.

The color stability of betalain- and ANC-rich extracts in yogurt-like fermented soy from several sources such as red beetroot ( Beta vulgaris L.), opuntia ( Opuntia stricta ), Roselle ( Hibiscus sabdariffa ), and radish ( Raphanus sativus L.) was evaluated [ 115 ]. The authors showed that red beetroot contained the highest amount of betacyanins (20.1 mg equivalents of betacyanin/L) and betaxanthins (4.27 mg equivalents of indicaxanthin/L), while Roselle the highest quantity of ANC (13.01 g/L). The extracts were applied in an encapsulated and non-encapsulated form (liposomes of soybean lecithin), showing high retention of the extracts after 21 storage days, being Roselle and red radish, the most stable ones compared to untreated yogurt samples. The beetroot-added yogurts exhibited the highest a* values, followed by red radish, opuntia, and Roselle.

Flavored fermented milk was prepared with a microencapsulated extracted pigment (Canthaxanthin), a carotenoid-type colorant from Dietzia natronolimnaea HS-1 bacteria, which is permitted to be used in milk products up to 15 mg/L [ 116 ]. Fermented milk beverages showed significant reductions ( p < 0.05) in the antioxidant capacity (DPPH method) after 7, 14, and 21 days (−40.16%, −49.61%, and −52.83%, respectively). Regarding the color parameters, b* and L* increased during 21-days storage, but no changes ( p < 0.05) were reported for the color difference (ΔE). Microcapsules-added yogurts also exhibited a decrease in viscosity values, but this was attributed to capsule disintegration during storage and hydrogen bond formation between protonated carboxyl groups from alginate due to low pH.

Other dairy products have been formulated with natural colorants. Montibeller [ 117 ] assessed an ANC-rich extract from grape skin (Cabernet Sauvignon) on kefir, obtaining a decreased pH (up to ~4.55), increased acidity (up to ~0.080% citric acid), and low total soluble solids (~7.6 °Brix) after the addition of the extract in a 16-days evaluation of kefir performance. At the same time, L* and b* values increased (reaching 96.6 and 5.1, respectively), and a* progressively decreased to ~1.2. The storage time affected ANC retentions, but high values were obtained for peonidin-3-glucoside and delphinidin-3- O - p -coumarylglucoside (~77–88%). The authors suggested that the ANC-formulated kefir showed similar physical properties compared natural kefir without additives.

Ice creams are popular dairy or dairy-like frozen desserts at neutral pH, sometimes formulated with milk fat, milk proteins, fruits, and flavors. Stabilization of color in ice creams is still a problem that merits further research since some of them must be stabilized with polysorbate, negatively affecting the formation of overrun, one of the most desired attributes of ice creams [ 118 ]. The most common colorants used in ice cream are curcumin (intense lemon shade), Carthamus (bright yellow with slight greenish shade), β-carotenes (orange-yellow hues, preferred for vanilla-flavored products), annatto (yellow shades), beetroot (pink-red color), lycopene (red color), and chlorophylls or copper-chlorophylls (yellowish-green and bright green colors, respectively) [ 119 ].

Singo and Beswa [ 120 ] reported the impact of aqueous Roselle ( Hibiscus sabdariffa ) extracts (5%, 10%, 15%, and 20% v/v ) on selected quality characteristics of ice cream. The extracts exhibited a direct relationship between the dose increase and L*, b*, and whiteness index, while a* progressively augmented up to 1.50 for the highest Roselle concentration. All Roselle-added ice creams showed lower L*, a*, and whiteness index values. Compared to a commercial vanilla-flavored ice cream control, overrun and melting rate values were higher ( p < 0.05) (25.71–139.28% and 85.71–228.57%, respectively), but viscosity and pH were lower for the highest Roselle concentrations ( p < 0.05, −2.97% to −3.13%; −4% to −6.22, respectively). The lowest Roselle-formulated ice creams (5% and 10%) showed no differences against the control in the sweetness and gummy taste evaluations. The authors considered that Roselle formula above 5% v / v would produce less viscous, high melting rate, unpopular color, and undesirable characteristics.

Durmaz et al. [ 121 ] used spray-dried microalga ( Nannochloropsis oculata , Porphyridium cruentum , and Diacronema vilkianum ) as coloring agents for ice cream (0.1, 0.2, and 0.3 g/100 g ice cream). The main pigments found in the spray-dried products were carotenoids (0.40–0.77 mg/g dry weight), chlorophyll a (1.06–4.76 mg/g dry weight), and ANC (2.34–23.96 mg C3G/kg). Compared to control ice cream, apparent viscosity decreased once added the microalga extracts, showing a resemblance to Newtonian fluids, being P. cruentum -added ice creams those with the most advantageous behavior as this microalga contains several carbohydrates such as cell storage polymers (starch derivatives), lipopolysaccharides, and extracellular polysaccharides. Ice creams enriched with P. cruentum displayed pinkish color, and the two other alga species showed a greenish color. Luminosity was not affected by type and concentration, while b* values increased together with alga concentration. Alga addition negatively impacted melting behavior, but the authors suggested the potential of optimization studies improving the ice cream composition and using bulking agents to overcome this situation.

Aqueous and ethanolic/methanolic betacyanin extracts from red pitahaya ( Hylocereus polyrhizus ) were applied as a colorant in ice creams [ 122 ]. The highest betacyanin yields (up to 18%) were acquired by adding pectinase (1.5% and 2.0% v/v ) in the 95% ethanol extractions. During 21-day storage, betacyanins concentrations increased (~0.02%), and no significant color changes were found ( p > 0.05). Betacyanin-supplemented ice creams exhibited the highest free radical scavenging activities (DPPH: 50–57%).

Using colorants in cheese is also a common practice. Natural colorants are preferred mainly for their health benefits, providing additional properties such as antioxidant, antimicrobial, and surface-active activity to colored cheese products [ 4 ]. The main colorant used in cheese and butter is annatto, but for the cheese industry, the colorant is mainly composed of norbixin, responsible for imparting yellow/orange color to cheddar cheese [ 123 ]. Other usual colorants used in cheese are carminic acid and ANC, paprika oleoresin, vegetable carbon, chlorophylls and chlorophyllin, and curcumin [ 80 ]. Saffron ( Crocus sativus L.) was used as a colorant for fresh ovine cheese starting from a concentrated extract (1000 mg/L) and added to 2 L pasteurized ovine milk [ 124 ]. No differences were found for all treatments regarding moisture, total protein, salt, and fat contents ( p > 0.05), saffron-added cheeses exhibited the lowest pH levels (4.13–4.36) and highest antioxidant capacity values (23.84–25.97% RSA). Saffron did not affect L*, but a* and b* values were higher compared to control cheeses. The 50 mg/L saffron-supplemented cheese was evaluated equally to control cheeses, while the highest saffron concentration negatively affected the sensory scores.

Sea buckthorn ( Hippophae rhamnoides L.) fruit extracts were also assayed as colorants for cream cheese [ 125 ]. Chlorophylls (2.79 mg/L chlorophyll a ; 4.73 mg/L chlorophyll b )), carotenoids (8.27 mg/L total carotenoids), and TPC (1842.86 mg/100 g dry weight) were the major quantified pigments and polyphenols from the fruits’ extracts. The addition of the extracts increased (2.04%) the average organoleptic score, decreased dynamic viscosity (up to 11258 mPa·s), and showed the same total viable count (4 × 10 2 cfu/g) compared to 0.01% tartrazine-added cheese.

Lastly, dairy products are ideal complex food systems that can be used to test natural food-colorants properties since phenolics, and other components form interactions potentially reducing their abundance and health benefits. Hence, yogurt is one of the most tested dairy products to particularly test coloring properties and antioxidant capacity of their bioactive compounds [ 126 ]. Carotenoid and ANC are the most common colorant types used in dairy products, but the blue pigment provided by phycocyanobilins and the pH-stable shades given by betacyanins have opened an opportunity to these chemical groups to be more widely incorporated.

4.5. Meat and Meat Products

Curing is a highly valued process in the meat industry since it prevents Clostridium botulinum growth and development. Concerns about this process’ carcinogenic and toxic effects of nitrosamines as a result of the nitrite and nitrates have stimulated research in other colorants not only for a generation of a stable color but to reduce the need of using curing salts. In this sense, it has been found specific applications for plant-derived colorants such as beetroot ( Beta vulgaris L.: red betacyanins and yellow betaxanthins), paprika ( Capsicum annuum L.: red color), tomato ( Solanum lycopersicum : lycopene); and microbial pigments like pigments from Monascus purpureus (purple color) [ 127 ].

Slightly colored meat products (e.g., pork and turkey) are some of the most routinely used food systems to evaluate the pigment properties of natural colorants. Several researchers have focused on the assessment of these pigments in sausages, widely consumed worldwide. Microencapsulated jabuticaba ( Myrciaria cauliflora ) extract (2% and 4% w/w ) was added to fresh sausages [ 128 ] and the resulting product showed the same ( p > 0.05) proximal composition, lower ( p < 0.05) thiobarbituric acid reactive substances (TBARS) development (0.01–0.05 mg malonaldehyde, MDA/kg sample, compared to 0.39–0.60 mg MDA/kg), and major color preservation compared to control and carmine-formulated sausages. Purified fucoxanthin from Tunisian seaweed ( Cystoseira barbata ) allowed reductions from 150 to 80 ppm in the nitrite concentration of turkey-meat sausages due to enhanced color preservation and improved oxidative stability, but no antimicrobial evaluations were carried out, one of the main purposes of using nitrites [ 129 ]. Similar sausages were formulated with carotenoproteins from blue crab ( Porturus segnis ) shells (84.44% yield, 1211–1135 μg GAE/g extract) [ 130 ], where the developed sausages exhibited a 10-day shelf life with decreasing diene formation, metmyoglobin, and heme iron preservation, and improved DPPH radical scavenging than control sausages.

The evaluation of colorants can also be used in cooked meat to preserve color and avoid lipid oxidation. Both complex processes still a major concern in loss of sensory quality, nutritional properties, and economic value [ 131 ]. Astaxanthins from Haematococcus pluvialis (20 mg/kg, 40 mg/kg, 60 mg/kg, and 80 mg/kg) showed strong antioxidant properties when applied to fresh, frozen, and cooked lamb patties [ 75 ], showing pH preservation, lower TBARS levels than control patties (no antioxidants; and low L*, higher a*, and higher b* values than control patties. More recently, Cunha et al. [ 132 ] reported the antioxidative properties of encapsulated pitaya ( Hylocereus costaricensis ) peel extract (100 and 1000 ppm) on pork patties subjected to high-pressure processing, manifested in slight L* and b* increases, a* preservation, color differences closer to 1, preserved cohesiveness and springiness, and low concentrations of MDA along time.

As meat products are mainly associated with reddish and orange colors, carotenoids have especially found a niche in these food products. Moreover, since nitrites and nitrates are applied into these products to take advantage of the antibacterial properties, using nitrogen-based natural food-colorants could be an alternative to reduce the amount their amount, preventing health concerns associated to their use. Thus, betacyanins could be one of the most potential colorants to be used in these food systems, but process extraction and optimization is needed to test their curing ability, nitrosamine formation, and their ability to produce a desirable color.

4.6. Other Food Products

Natural colorants are widely used in pasta products to produce new ways of colored pasta, especially the popular “vegetable-added pasta”. Dalla Costa et al. [ 133 ] used 20% carrot ( Daucus carota sbsp. sativus) flour as a substitute for β-carotene for commercial dry wheat ( Triticum aestivum ) pasta and found 307% higher levels of carotenoids, 132% increased antioxidant capacity, and 608% higher total fiber compared to no carrot-added pasta. Saffron ( Crocus sativus L.) enrichment (0.2–0.4% w/w ) of wheat flour pasta [ 134 ] decreased L* but increased a* and b* values compared to commercial pasta, and no textural parameters were affected (hardness, cohesiveness, elasticity, and chewiness). In contrast, saffron allowed higher antioxidant capacity values (DPPH: 4–6 μmol Trolox equivalents/g dry base vs. 0.5–4 μmol Trolox equivalents/g dry base in control pasta). Panelists positively scored saffron-added pasta in terms of aspect, color, aroma, taste, and global acceptability.

The addition of “Senduduk” fruit ( Melastoma malabatrhicum L.) (2–10%) to jackfruit jam enhanced β-carotene (300–314 g/100 mL), ANC (6.86–9.43 mg/L), TPC (0.99–1.34 mg/mL), and antioxidant capacity [ 135 ].

Cerezal Mezquita et al. [ 136 ] assayed lutein obtained from Muriellopsis sp. alga biomass as a natural and antioxidant in a mayonnaise-like dressing sauce. Prepared mayonnaises showed high pigment stability in the matrix based on the L*, a*, and b* values. The tested mayonnaise showed similar moisture and lipids than corn oil mayonnaise and higher lutein than commercially available mayonnaises.

Finally, the plenty applications of natural food-colorants demonstrate their potential to be incorporated in several food systems beyond the traditional formulations. New sources are constantly being incorporated as sources of colorants after an optimization procedure to overcome not only technological aspects, but also legal and toxicological concerns, and the consumers’ attitudes towards these colorants. A summary of all technological applications of natural colorants in food systems is shown in Table 2 .

Technological applications of natural colorants in food systems.

ΔE: Color difference against control samples, in the L*C*h* color space; a*: Redness color change; b*: Yellowness color change; ANC: Anthocyanins; C3G: Cyanidin-3- O -glucoside; cfu: colony forming units; cP: Centipoise; D3G: Delphinidin-3- O -glucoside; DM: Dry matter; DPPH: 2,2-diphenyl-1-picrylhydrazyl; IAT: Inlet air temperature; L*: Luminosity or Lightness; MDA: Malonaldehyde; OAT: Outlet air temperature; RSA: Radical scavenging activity (%); RSM: Response surface methodology; TAC: Total anthocyanin content; TBARS: Malonaldehyde acid reactive substances; TEAC: Trolox equivalent antioxidant capacity.

5. Conclusions and Perspectives

The use of natural colorants in food systems is still limited due to technological issues. Alternative sources of colorants should be explored, aiming to find more stable, physicochemical feasible, and improved color stability from traditional and novel sources. Underutilized tropical fruits and vegetables such as Andean, Amazonian, and South-Asian products are still underdeveloped raw materials to extract valuable natural food-colorants. Emerging technologies such as ohmic heating and EF-based technologies have the advantage of using less energy and water for extracting compounds, whereas PEF easily induces electroporation on the food matrix, accelerating the extraction to reach <80% yield for some colorants. For heat-labile compounds, HPE allows the extraction without using temperature, preserving its functional characteristics. However, extraction technologies should be optimized to provide environmentally feasible and low-cost colorants from the actual and novel sources.

Although the addition of some of these novel ingredients might affect the physicochemical properties of these products, as shown in dairy and dairy-like products such as ice creams, optimization procedures improving the existing formulations could positively enhance the inclusion of these nutritionally rich ingredients. Hence, new textures and sensory outcomes could be provided, together with a nutritional advantage derived from the health-associate properties of most of these colorants. Understanding the chemical composition of the natural food-colorants and their interaction with the food matrix is a key factor to manufacture food products with the desired color stability. More research is needed to stabilize most of these colorants at the varied range of the usual pH and temperature conditions in the intended food systems.

Acknowledgments

Author I. Luzardo-Ocampo acknowledges Programa de Becas Posdoctorales de la UNAM (DGAPA-CTIC) for his postdoctoral fellowship [grant number: 5267].

Abbreviations

Author Contributions

Conceptualization: D.A.L.-V.; methodology: D.A.L.-V., I.L.-O., A.K.R.-J., and L.M.; validation: D.A.L.-V., I.L.-O., A.K.R.-J., and L.M.; investigation: I.L.-O., A.K.R.-J., L.M., J.Y., and D.A.L.-V.; writing—original draft preparation: I.L.-O., A.K.R.-J., L.M., J.Y., and D.A.L.-V.; writing—review and editing: I.L.-O. and D.A.L.-V.; supervision: D.A.L.-V. All authors have read and agreed to the published version of the manuscript.

This review was financially supported by a UIC-TEC Seed Fund.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Data availability statement, conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

ORIGINAL RESEARCH article

Effects of coloring food images on the propensity to eat: a placebo approach with color suggestions.

• Department of Clinical Psychology, University of Graz, Graz, Austria

Background: Research findings on the appetite-enhancing effect of the color red and the appetite-reducing effect of blue have been inconsistent. The present study used a placebo approach and investigated whether verbal suggestions can enhance color-appetite effects.

Method: A total of 448 women participated in two experiments. They viewed images with differently colored sweet foods (original color, blue, red, colorless (black-and-white); experiment 1; n = 217) or sweet foods on blue, red, white, and gray backgrounds; experiment 2; n = 231). Before viewing the images, half of the participants received information about the effects of red and blue food color on appetite (color suggestion). The other half received no suggestion. For each of the experiments, the reported propensity to eat (food wanting) was compared between the conditions.

Results: All colored food items were associated with a lower propensity to eat compared to the food items in the original color. The color suggestion (compared to no suggestion) additionally decreased the propensity to eat blue and black-and-white food items. Colored backgrounds did not influence food wanting.

Conclusion: This study demonstrated that red and blue coloring of visual food cues did not have the predicted effects on food wanting. However, the combination of specific food colors with specific color suggestions might be useful to change the willingness to eat sweet products.

Introduction

Color signals the edibility and the nutritional value of food ( Spence, 2015 ). The food color red is very common in nature and is typical for ripe fruits and fresh meat. In contrast, there aren’t many naturally occurring blue-hued foods, and sometimes ‘blue’ even indicates non-edibility (e.g., mold). Therefore, it is not surprising that the color red is considered appetizing, whereas blue acts as an appetite suppressant (for reviews see Spence et al., 2010 ; Zellner, 2013 ; Wadhera and Capaldi-Phillips, 2014 ; Spence, 2015 ).

Based on these observations, the adding of coloring to food and drink has a long history in the food industry. However, research on the effects of red/blue food coloring on the wanting and liking of food has produced heterogeneous results. In some of the studies the predicted effects occurred (e.g., increased appetite for red-colored food: e.g., Foroni et al., 2016 , decreased appetite for blue-colored food; e.g., Cho et al., 2015 ; Suzuki et al., 2017 ), but not in other studies (e.g., Gifford et al., 1987 ; Frank et al., 1989 , Chan and Kane-Martinelli, 1997 ; Alley and Alley, 1998 ).

Discrepant findings also characterize the research on the influence of color context (e.g., color of dishware) on food wanting, liking, and consumption (e.g., Tomita et al., 2007 ; Genschow et al., 2012 , Piqueras-Fiszman et al., 2012 ; for a review see Spence, 2018 ). For example, some studies have shown that red plates/cups increase appetite and food/drink consumption ( Piqueras-Fiszman and Spence, 2012 ), whereas other investigations even reported the opposite effect (e.g., Genschow et al., 2012 ).

The color of food not only provides information about the edibility but also about the palatability of food ( Spence, 2015 ). The evaluation of the hedonic reward from food is highly susceptible to suggestion ( Shankar et al., 2010 ). Placebo research has shown that the desire to eat specific food items can be influenced by verbal suggestions (e.g., Crum et al., 2011 ; Hoffmann et al., 2018 ; Potthoff et al., 2019 ). For example, participants consumed less in a test session when they were reminded of their last meal ( Higgs, 2002 ), when the food was labeled ‘healthy’ ( Provencher and Jacob, 2016 ) or ‘high-caloric’ ( Crum et al., 2011 ). In a study by Schienle et al. (2020) , a placebo (inert treatment of the tongue) was able to alter taste sensations and the affective ratings for food pictures. Pictures of spoiled food (with black/blue mold) were rated as less disgusting in the placebo condition (compared to the condition without placebo). Thus, the wanting and liking of food (cues) can be shaped by inducing expectations through verbal suggestions.

The aim of the present study was twofold. First, we attempted to replicate the effects of red/blue food coloring and red/blue backgrounds on food wanting (i.e., the propensity to eat). A large sample ( n = 448) was examined to overcome problems of previous studies on food-color effects with small sample sizes. Second, we attempted to enhance the color-appetite effects by using verbal suggestions. The participants viewed images with colored food items (original color, blue, red, black-and-white) or food items on colored backgrounds (white, blue, red, gray). Before viewing the pictures, half of the participants received the information that red color increases appetite, and blue color acts as an appetite suppressant (color suggestion); the other half received no suggestion. Ratings for food wanting (the propensity to eat the depicted food item) were compared between the conditions in each of the experiments.

Materials and Methods

Participants.

A total of 448 females aged between 18 and 35 years ( M = 22.54 years; SD = 3.36) participated in two experiments (experiment 1: n = 217; experiment 2: n = 231). The participants had a mean body mass index (BMI) of M = 21.74 ( SD = 2.92). The reported hunger level at the time of testing was M = 3.04 ( SD = 2.26; 1 = not hungry; 9 = very hungry), and the average time since the last meal was M = 3.30 h ( SD = 3.53). We only tested females because of reported sex differences concerning self-reports for appetite and food preferences (e.g., Blechert et al., 2014 ; Gregersen et al., 2011 , Bédard et al., 2015 ). Participants were recruited via announcements at the university campus; the majority were students (91%).

The computed pairwise comparisons ( t -tests) did not show statistically significant differences between the participants assigned to the two conditions (suggestion vs. no-suggestion) in each of the two experiments concerning BMI, hunger level, and time since last meal (all p > 0.19; for means ( M ) and standard deviations ( SD ) see Supplementary Table 1 ).

Stimuli and Design

The stimulus material for experiment 1 consisted of 12 images of sweet foods (e.g., chocolate chip cookie, cupcake, and cream cake) taken from the Food Pics Database ( Blechert et al., 2014 ) and non-copyrighted sources from the internet. We selected images of sweet food because these stimuli receive on average neutral to positive ratings for food wanting ( Blechert et al., 2014 ). Thus, changes in reported food wanting can be induced, including both an increase and a decrease.

For each of the 12 original pictures, three additional versions with the food items colored in blue, red, and black-and-white (colorless) were created (see Figure 1 ), resulting in a total of 48 food images. The black-and-white images served as a control condition that was characterized by the absence of blue and red color. The original images were considered the reference or baseline condition (reflecting individual preferences concerning a food item). The images had a resolution of either 600 × 450 pixels or 350 × 500 pixels. Luminance scores for blue and red color were equivalent (160 lm).

Figure 1. Examples of food images in the two experiments.

In Experiment 2, the same 12 food images were used as in experiment 1 (in original color). Four different versions were created with a white, red, blue, and gray (black-and-white) background (see Figure 1 ). In both experiments, the same red and blue coloring was used.

The images of experiment 1 and experiment 2 were presented via two independent online surveys (LimeSurvey GmbH, Hamburg). To avoid boredom and habituation because of the repeated presentation of the same food images in different color versions, each participant was presented with a random selection of 12 pictures (three images in blue, red, black-and-white (gray), and original color). The pictures were displayed in randomized order and the participants rated their food wanting (“How much would you like to eat this food right now?”) on a 7-point Likert scale (1 = not at all; 7 = very much) for each picture.

In both experiments, the participants were randomly assigned to one of two experimental conditions. In the color suggestion condition, the participants were provided with information about the appetizing effect of the color red and the appetite-suppressant effect of blue. Participants of the no suggestion condition received no color information.

The study was approved by the ethics committee of the University and was performed following the Declaration of Helsinki. All participants gave written informed consent.

Statistical Analysis

To adjust for individual differences in food wanting for the original items ( M = 3.87; SD = 1.56; range = 1–7), we computed difference scores. To do this, we first calculated mean scores for each color condition based on the three ratings for wanting of each participant. Then, difference scores (between the conditions) were calculated (Experiment 1: Difference score_red: wanting for red-colored food minus wanting for food in the original color, Difference score_blue: blue minus original, Difference score_black-and-white: black-and-white minus original; Experiment 2: Difference score_red: wanting for food on red background minus wanting for food on white background, Difference score _blue: blue minus white, Difference score_gray: gray minus white).

For each of the two experiments, a 3 × 2 analysis of variance (ANOVAs) was performed to test the effects of COLOR (Difference score_red, Difference score _blue, Difference score _black-and-white/grey) and CONDITION (color suggestion, no-suggestion) on the propensity to eat. After controlling for hunger level, BMI, and hours since the last meal in additionally computed analyses of covariance (ANCOVA), the results did not change. Therefore, we report the ANOVA findings.

Effect sizes are expressed by partial eta squared ( part. η 2 ). If violations of sphericity occurred, Greenhouse-Geisser corrections were used. Significant effects were followed up by Bonferroni-adjusted pairwise comparisons. The analyses were conducted with SPSS version 26 ( IBM Corp, 2019 ).

A power analysis with G ∗ Power 3.1.9.2 Faul et al. (2007) indicated that a sample size of n = 192 would be necessary to detect an effect size of part. η 2 = 0.03 (i.e., small effect) with a probability of 1–β = 0.80, α = 0.05 for the interaction effect COLOR x CONDITION.

Experiment 1 (Colored Food)

The ANOVA revealed significant effects for COLOR [ F (2, 430) = 8.74, p < 0.001, part. η 2 = 0.039], COLOR x CONDITION [ F (2, 430) = 6.34, p = 0.002, part. η 2 = 0.029] and CONDITION [ F (1, 215) = 6.41, p = 0.012, part. η 2 = 0.029]. Compared to original color, the coloring (red, blue, black-and-white) of the food items reduced the propensity to eat significantly (all p < 0.001). The reduction in food wanting was larger for blue and black-and-white food in the suggestion condition than in the no-suggestion condition (all p < 0.047; see Figure 2 ). The ratings for red food did not differ between the suggestion and no-suggestion condition ( p = 0.653).

Figure 2. Means and standard errors of difference scores for food wanting in experiment 1 and experiment 2 across the different conditions. Experiment 1: “Difference score_red” = wanting of red-colored food items minus food in original color; “Difference score_blue” = wanting of blue-colored food minus food in original color; “Difference score_b-w” = wanting of black-and-white colored food minus food items in original color; Experiment 2: “Difference score_red” = wanting of food on red background minus white background; “Difference score_blue” = wanting of food on blue background minus white background; “Difference score_gray” = wanting of food on grey background minus white background; Asterisks ( ∗ ) indicate p < 0.05.

In the suggestion condition, the reduction in the propensity to eat blue and black-and-white food was greater compared to red food (all p < 0.001). Blue and black-and-white food did not differ from each other ( p > 0.99). In the no-suggestion condition, food wanting did not differ between the color conditions (all p > 0.072; Figure 2 ).

Experiment 2 (Colored Backgrounds)

The ANOVA revealed no statistically significant results for COLOR [ F (1.93, 442.36) = 0.204, p = 0.816, part.η 2 = 0.001], CONDITION [ F (1, 229) = 0.261, p = 0.610, part. η 2 = 0.001], and the interaction COLOR x CONDITION [ F (1.93, 442.36) = 1.079, p = 0.339, part. η 2 = 0.005; Figure 2 ]. Food wanting did not differ between food items with white backgrounds and food with colored backgrounds (red, blue, gray; all p > 0.243).

This study examined the effects of red/blue coloring of visual food cues and verbal color suggestions on reported food wanting. It was shown that both blue and red coloring of the depicted food items had an appetite-reducing effect. Thus, ‘red’ and ‘blue’ did not have the predicted opposite effects on the propensity to eat but were always considered negative. For example, compared to the original brown chocolate chip cookie, all color variants (red, blue, black-and-white) were experienced as less appetizing. In the no-suggestion condition, the appetite-reducing effect of ‘blue’ and ‘red’ did not differ from each other. This effect very likely is a result of ‘color expectancy deviations’. We all have concepts of how specific food items should look like. If a ‘color expectancy violation’ occurs, this induces reductions in food wanting. In a classic study by Wheately (1973) , participants were presented with a dinner consisting of a blue steak, red peas, and green French fries. The dinner started under dim lighting to hide the food’s true color. When the lighting was returned to normal, the ‘inappropriate’ food coloring elicited appetite reduction and even nausea in some of the participants. In a recent study by Suzuki et al. (2017) , blue soup decreased reported appetite and palatability compared to soup with typical colors (white, yellow).

In the present investigation, the ‘blue effect’ on reported food wanting was enhanced by the verbal suggestion of this color as an appetite suppressant. Additionally, we observed an appetite-reducing effect of black-and-white coloring in the suggestion condition. An explanation might be that achromatic/black-and-white is more likely perceived as belonging to the blue color spectrum (e.g., Weiss et al., 2017 ) and that toxic or spoiled food is often blue, black, or purple. The ‘red suggestion’ did not affect food wanting because an appetite increase was suggested, while the participants experienced a reduction.

No influence of color on food wanting was observed in experiment 2 although our large sample size was associated with sufficient power to detect even small effects. Previous studies have reported effects of different color contexts, such as table cloths, plates, cups, and ambient illumination on appetite and taste ratings (for a review see Spence, 2018 ). A possible explanation for the absence of the color-background effect in the present experiment can be derived from the findings by Schifferstein et al. (2016) . The authors presented five differently colored vegetables (tomato, carrot, yellow bell pepper, cucumber, and eggplant) against one of four different backgrounds (either light or dark orange or light or dark blue). The participants rated the attractiveness of the vegetables. The main result of this study was that each food item had its optimal background color. For example, a light orange made the cucumber most attractive, while light blue was optimal for the eggplant. Thus, different food items seem to be associated with different appetizing contexts.

The following limitations of the current study need to be addressed. In the present study, female participants (mainly university students) were presented with images depicting sweet foods. Thus, our results cannot be generalized to other samples and food types. Moreover, the coloring of images vs. real food items might have different effects. Therefore, in a future study, the consumption of colored food items (e.g., amount of food eaten in a test meal) should be assessed. The present study only relied on self-reports for the propensity to eat the depicted food items.

In conclusion, this study identified conditions under which color suggestions can influence food wanting. Future research now needs to find optimal combinations of food coloring and color suggestions for specific food items to alter the propensity to eat in the intended direction.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

The studies involving human participants were reviewed and approved by Ethics committee of the University of Graz. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

CS and AS designed the study. CS collected and analyzed the data. AS wrote the manuscript. Both authors contributed to the article and approved the submitted version.

This publication was supported by the University of Graz.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2020.589826/full#supplementary-material

Supplementary Table 1 | Descriptive Statistics (means and standard deviations (M, SD) for the participants in the non-suggestion condition and the suggestion condition in Experiment 1 and Experiment 2.

Alley, R. L., and Alley, T. R. (1998). The influence of physical state and color on perceived sweetness. J. Psychol. 132, 561–568. doi: 10.1080/00223989809599289

PubMed Abstract | CrossRef Full Text | Google Scholar

Bédard, A., Hudon, A. M., Drapeau, V., Corneau, L., Dodin, S., and Lemieux, S. (2015). Gender differences in the appetite response to a satiating diet. J. Obesity 2015, 1–9. doi: 10.1155/2015/140139

Blechert, J., Meule, A., Busch, N. A., and Ohla, K. (2014). Food-pics: an image database for experimental research on eating and appetite. Front. Psychol. 5:617. doi: 10.3389/fpsyg.2014.00617

Chan, M. M., and Kane-Martinelli, C. (1997). The effect of color on perceived flavor intensity and acceptance of foods by young adults and elderly adults. J. Am. Diet. Assoc. 97, 657–659. doi: 10.1016/s0002-8223(97)00165-x

CrossRef Full Text | Google Scholar

Cho, S., Han, A., Taylor, M. H., Huck, A. C., Mishler, A. M., Mattal, K. L., et al. (2015). Blue lighting decreases the amount of food consumed in men, but not in women. Appetite 85, 111–117. doi: 10.1016/j.appet.2014.11.020

Crum, A. J., Corbin, W. R., Brownell, K. D., and Salovey, P. (2011). Mind over milkshakes: mindsets, not just nutrients, determine ghrelin response. Health Psychol. 30, 424–429. doi: 10.1037/a0023467

Faul, F., Erdfelder, E., Lang, A. -G., and Buchner, A. (2007). G ∗ power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav. Res. Methods 39, 175–191. doi: 10.3758/BF03193146

Foroni, F., Pergola, G., and Rumiati, R. I. (2016). Food color is in the eye of the beholder: the role of human trichromatic vision in food evaluation. Sci. Rep. 6:37034.

Google Scholar

Frank, R., Ducheny, K., and Mize, S. (1989). Strawberry odor, but not red color, enhances the sweetness of sucrose solutions. Chem. Senses 14, 371–377. doi: 10.1093/chemse/14.3.371

Genschow, O., Reutner, L., and Wänke, M. (2012). The color red reduces snack food and soft drink intake. Appetite 58, 699–702. doi: 10.1016/j.appet.2011.12.023

Gifford, S. R., Clydesdale, F. M., and Damon, R. A. Jr. (1987). The psychophysical relationship between color and salt concentrations in chicken flavored broths. J. Sens. Stud. 2, 137–147. doi: 10.1111/j.1745-459x.1987.tb00193.x

Gregersen, N., Møller, B., Raben, A., Kristensen, S., Holm, L., Flint, A., et al. (2011). Determinants of appetite ratings: the role of age, gender, BMI, physical activity, smoking habits, and diet/weight concern. Food Nutr. Res. 55:7028. doi: 10.3402/fnr.v55i0.7028

Higgs, S. (2002). Memory for recent eating and its influence on subsequent food intake. Appetite 39, 159–166. doi: 10.1006/appe.2002.0500

Hoffmann, V., Lanz, M., Mackert, J., Müller, T., Tschöp, M., and Meissner, K. (2018). Effects of placebo interventions on subjective and objective markers of appetite–a randomized controlled trial. Front. Psychiatry 9:706. doi: 10.3389/fpsyt.2018.00706

IBM Corp. (2019). IBM SPSS Statistics for Windows , Version 26. Armonk, NY: IBM Corp.

Piqueras-Fiszman, B., and Spence, C. (2012). The influence of the color of the cup on consumers’ perception of a hot beverage. J. Sensory Stud. 27, 324–331. doi: 10.1111/j.1745-459X.2012.00397.x

Piqueras-Fiszman, B., Alcaide, J., Roura, E., and Spence, C. (2012). Is it the plate or is it the food? Assessing the influence of the color (black or white) and shape of the plate on the perception of the food placed on it. Food Qual. Prefer. 24, 205–208. doi: 10.1016/j.foodqual.2011.08.011

Potthoff, J., Jurinec, N., and Schienle, A. (2019). Placebo effects on visual food cue reactivity: an eye-tracking investigation. Front. Psychiatry 10:525. doi: 10.3389/fpsyt.2019.00525

Provencher, V., and Jacob, R. (2016). Impact of perceived healthiness of food on food choices and intake. Curr. Obesity Rep. 5, 65–71. doi: 10.1007/s13679-016-0192-0

Schienle, A., Gremsl, A., and Schwab, D. (2020). Placebos can change affective contexts: an event-related potential study. Biol. Psychol. 150:107843. doi: 10.1016/j.biopsycho.2020.107843

Schifferstein, H. N. J., Howell, B. F., and Pont, S. (2016). Colored backgrounds affect the attractiveness of fresh produce, but not it’s perceived color. Food Qual. Prefer. 56, 173–180. doi: 10.1016/j.foodqual.2016.10.011

Shankar, M. U., Levitan, C. A., and Spence, C. (2010). Grape expectations: the role of cognitive influences in color–flavor interactions. Conscious. Cogn. 19, 380–390. doi: 10.1016/j.concog.2009.08.008

Spence, C. (2015). On the psychological impact of food colour. Flavour 4:21. doi: 10.1186/s13411-015-0031-3

Spence, C. (2018). Background colour & its impact on food perception & behaviour. Food Qual. Prefer. 68, 156–166.

Spence, C., Levitan, C. A., Shankar, M. U., and Zampini, M. (2010). Does food color influence taste and flavor perception in humans? Chemosens. Percept. 3, 68–84. doi: 10.1007/s12078-010-9067-z

Suzuki, M., Kimura, R., Kido, Y., Inoue, T., Moritani, T., and Nagai, N. (2017). Color of hot soup modulates postprandial satiety, thermal sensation, and body temperature in young women. Appetite 114, 209–216. doi: 10.1016/j.appet.2017.03.041

Tomita, K., Ono, M., Aiba, T., and Ohtani, K. (2007). Psychological effects of tablecloth color on diners under different brightness. Jpn. Assoc. Integr. Study Dietary Habits 18, 48–55. doi: 10.2740/jisdh.18.48

Wadhera, D., and Capaldi-Phillips, E. D. (2014). A review of visual cues associated with food on food acceptance and consumption. Eat. Behav. 15, 132–143. doi: 10.1016/j.eatbeh.2013.11.003

Weiss, D., Witzel, C., and Gegenfurtner, K. (2017). Determinants of colour constancy and the blue bias. i Percept. 8, 1–29.

Wheately, J. (1973). Putting color into marketing. Marketing 67, 24–29.

Zellner, D. A. (2013). Color-odor interactions. a review and model. Chemosens. Percept. 6, 155–169. doi: 10.1007/s12078-013-9154-z

Keywords : food coloring, colored backgrounds, blue, red, verbal suggestions, placebo, food wanting

Citation: Schlintl C and Schienle A (2020) Effects of Coloring Food Images on the Propensity to Eat: A Placebo Approach With Color Suggestions. Front. Psychol. 11:589826. doi: 10.3389/fpsyg.2020.589826

Received: 31 July 2020; Accepted: 07 October 2020; Published: 29 October 2020.

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Copyright © 2020 Schlintl and Schienle. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Anne Schienle, [email protected]

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