essay on modern technology in agriculture

Essay on Impact Of Technology On Agriculture

Students are often asked to write an essay on Impact Of Technology On Agriculture in their schools and colleges. And if you’re also looking for the same, we have created 100-word, 250-word, and 500-word essays on the topic.

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100 Words Essay on Impact Of Technology On Agriculture

Improving crop growth.

Technology helps farmers grow more food. Machines like tractors make preparing soil easy. Seeds are planted quickly with special tools. There are even computers that tell farmers the best time to plant. This means more crops can grow and people have plenty of food.

Protecting Plants from Pests

Pests can destroy crops, but technology fights them. There are apps that can spot harmful bugs. Farmers use this information to protect plants. They only spray chemicals where needed, which is safer for the environment.

Keeping Track of Farms

Drones fly over fields and take pictures. These images show which parts of the farm need more water or fertilizer. This helps farmers take care of their crops better and saves them time and money.

Climate and Weather

Technology predicts the weather accurately. Farmers know when it will rain or be too hot. They can plan when to water the plants or when to harvest. This way, bad weather does less harm to the crops.

Storing Food Properly

After harvest, technology keeps food fresh. Cold storage units and better packaging methods stop food from going bad. This means less waste and more food for everyone.

250 Words Essay on Impact Of Technology On Agriculture

Technology makes farming easier.

Long ago, farmers had to work the land with their hands and simple tools. Now, machines do many tasks, making work faster and less tiring. Tractors plow fields in a day, which once took weeks. Machines also plant seeds and harvest crops. This means farmers can grow more food with less effort.

Better Crop Care with Technology

Technology helps farmers take care of plants better. There are special sensors that tell farmers how much water each plant needs. This way, not a single drop is wasted. Drones fly over fields to spot sick plants. Then, farmers can make them healthy before it’s too late. This helps to make sure more plants grow well and are ready to eat.

Keeping Track with Computers

Farmers use computers to keep an eye on their farms. They can see how much food they grow and how their animals are doing. Computers help them make smart choices. For example, they can find out the best time to sell their crops or when to buy new seeds.

Staying Safe from Bad Weather

Bad weather can destroy crops. But now, with new technology, farmers can be ready. They get weather reports on their phones and can protect their plants before storms hit. Some even use big covers to shield their crops from too much sun or rain.

In conclusion, technology has changed farming a lot. It makes growing food easier, helps farmers take better care of their plants, keeps track of farm details, and protects crops from bad weather. All this means we have more food on our tables every day.

500 Words Essay on Impact Of Technology On Agriculture

Introduction to technology in farming.

Farming is an important job because it gives us food to eat. Long ago, farmers used simple tools to grow crops and raise animals. Now, technology has changed farming a lot. Technology means using science to make tools and machines that can do tasks for us. In agriculture, which is another word for farming, technology helps farmers grow more food, take care of their plants and animals better, and protect the environment.

Better Farming Tools and Machines

One big change technology has brought to farming is better tools and machines. Before, farmers had to do a lot of hard work with their hands or use animals to help them. Now, there are machines like tractors, planters, and harvesters. These machines can do the work faster and save a lot of time. They can also be very precise, which means they make fewer mistakes, like planting seeds at the perfect depth in the soil.

Keeping Plants Healthy

Technology also helps farmers keep their plants healthy. There are special computers and apps that tell farmers when to water their plants or if a plant is sick. This is great because it means farmers can use less water and fewer chemicals, which is better for the earth. Drones, which are like small flying robots, can fly over fields and take pictures so farmers can see if all the plants are healthy or if some parts of the field need more care.

Understanding the Weather

Another helpful part of technology in farming is being able to understand the weather better. There are tools that can check the weather and tell farmers what it will be like in the future. This is important because if a farmer knows it will rain soon, they might decide not to water their crops that day. Or if they know it will be very cold, they can protect their plants to make sure they don’t freeze.

Helping Animals

Farms that have animals also use technology. There are special collars for cows that can track where they go and how much they eat. This helps the farmer know if the cow is healthy. There are also machines that can help milk cows. This is good for the farmer because it saves time, and it’s good for the cows because the machines are gentle and keep everything clean.

Storing and Moving Food

After the food is grown, technology helps keep it fresh and gets it to the stores where we buy it. There are big refrigerators that can keep fruits and vegetables cold so they don’t spoil. There are also trucks and ships with special coolers that can move food from the farm to the store without it going bad.

In conclusion, technology has made a big difference in farming. It has made it easier for farmers to grow food and take care of their plants and animals. It has also helped make sure that the food stays fresh until it gets to us. All these changes mean that we can have lots of different foods to eat all year round, and it’s also helping the planet because farmers can use less water and chemicals. Technology in agriculture is very important, and it will keep helping farmers do their job better in the future.

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Agriculture’s connected future: How technology can yield new growth

The agriculture industry has radically transformed over the past 50 years. Advances in machinery have expanded the scale, speed, and productivity of farm equipment, leading to more efficient cultivation of more land. Seed, irrigation, and fertilizers also have vastly improved, helping farmers increase yields. Now, agriculture is in the early days of yet another revolution, at the heart of which lie data and connectivity. Artificial intelligence, analytics, connected sensors, and other emerging technologies could further increase yields, improve the efficiency of water and other inputs, and build sustainability and resilience across crop cultivation and animal husbandry.

The future of connectivity

As the world experiences a quantum leap in the speed and scope of digital connections, industries are gaining new and enhanced tools to boost productivity and spur innovation. Over the next decade, existing technologies like fiber, low-power wide-area networks (LPWAN), Wi-Fi 6, low- to mid-band 5G, and short-range connections like radio-frequency identification (RFID) will expand their reach as networks are built out and adoption grows. At the same time, new generations of these technologies will appear, with upgraded standards. In addition, new types of more revolutionary—and more capital-intensive—frontier connectivity, like high-band 5G and low-Earth-orbit (LEO) satellites, will begin to come online.

Together, these technological developments will unlock powerful new capabilities across industries. Near-global coverage will allow the expansion of use cases even to remote areas and will enable constant connectivity universally. Massive use of Internet of Things (IoT) applications and use cases will be enabled as new technologies allow very high device densities. And mission-critical services will take advantage of ultralow-latency, high-reliability, and high-security connections.

Without a solid connectivity infrastructure, however, none of this is possible. If connectivity is implemented successfully in agriculture, the industry could tack on $500 billion in additional value to the global gross domestic product by 2030, according to our research. This would amount to a 7 to 9 percent improvement from its expected total and would alleviate much of the present pressure on farmers. It is one of just seven sectors that, fueled by advanced connectivity, will contribute $2 trillion to $3 trillion in additional value to global GDP over the next decade, according to research by the McKinsey Center for Advanced Connectivity  and the McKinsey Global Institute  (MGI) (see sidebar “The future of connectivity”).

Demand for food is growing at the same time the supply side faces constraints in land and farming inputs. The world’s population is on track to reach 9.7 billion by 2050, 1 The World Population Prospects: 2015 Revision, United Nations, Department of Economic and Social Affairs, Population Division, 2015. requiring a corresponding 70 percent increase in calories available for consumption, even as the cost of the inputs needed to generate those calories is rising. 2 World Resources Report: Creating a Sustainable Food Future, United Nations, World Resources Institute, and the World Bank, 2013. By 2030, the water supply will fall 40 percent short of meeting global water needs, 3 World Could Face Water Availability Shortfall by 2030 if Current Trends Continue, Secretary-General Warns at Meeting of High-Level Panel, United Nations, 2016. and rising energy, labor, and nutrient costs are already pressuring profit margins. About one-quarter of arable land is degraded and needs significant restoration before it can again sustain crops at scale. 4 The State of the World’s Land and Water Resources for Food and Agriculture: Managing systems at risk, Food and Agriculture Organization of the United Nations and Earthscan, 2011. And then there are increasing environmental pressures, such as climate change and the economic impact of catastrophic weather events, and social pressures, including the push for more ethical and sustainable farm practices, such as higher standards for farm-animal welfare and reduced use of chemicals and water.

To address these forces poised to further roil the industry, agriculture must embrace a digital transformation enabled by connectivity. Yet agriculture remains less digitized compared with many other industries globally. Past advances were mostly mechanical, in the form of more powerful and efficient machinery, and genetic, in the form of more productive seed and fertilizers. Now much more sophisticated, digital tools are needed to deliver the next productivity leap. Some already exist to help farmers more efficiently and sustainably use resources, while more advanced ones are in development. These new technologies can upgrade decision making, allowing better risk and variability management to optimize yields and improve economics. Deployed in animal husbandry, they can enhance the well-being of livestock, addressing the growing concerns over animal welfare.

Demand for food is growing at the same time the supply side faces constraints in land and farming inputs.

But the industry confronts two significant obstacles. Some regions lack the necessary connectivity infrastructure, making development of it paramount. In regions that already have a connectivity infrastructure, farms have been slow to deploy digital tools because their impact has not been sufficiently proven.

The COVID-19 crisis has further intensified other challenges agriculture faces in five areas: efficiency, resilience, digitization, agility, and sustainability. Lower sales volumes have pressured margins, exacerbating the need for farmers to contain costs further. Gridlocked global supply chains have highlighted the importance of having more local providers, which could increase the resilience of smaller farms. In this global pandemic, heavy reliance on manual labor has further affected farms whose workforces face mobility restrictions. Additionally, significant environmental benefits from decreased travel and consumption during the crisis are likely to drive a desire for more local, sustainable sourcing, requiring producers to adjust long-standing practices. In short, the crisis has accentuated the necessity of more widespread digitization and automation, while suddenly shifting demand and sales channels have underscored the value of agile adaptation.

Current connectivity in agriculture

In recent years, many farmers have begun to consult data about essential variables like soil, crops, livestock, and weather. Yet few if any have had access to advanced digital tools that would help to turn these data into valuable, actionable insights. In less-developed regions, almost all farmwork is manual, involving little or no advanced connectivity or equipment.

Even in the United States, a pioneer country in connectivity, only about one-quarter of farms currently use any connected equipment or devices to access data, and that technology isn’t exactly state-of-the-art, running on 2G or 3G networks that telcos plan to dismantle or on very low-band IoT networks that are complicated and expensive to set up. In either case, those networks can support only a limited number of devices and lack the performance for real-time data transfer, which is essential to unlock the value of more advanced and complex use cases.

Nonetheless, current IoT technologies running on 3G and 4G cellular networks are in many cases sufficient to enable simpler use cases, such as advanced monitoring of crops and livestock. In the past, however, the cost of hardware was high, so the business case for implementing IoT in farming did not hold up. Today, device and hardware costs are dropping rapidly, and several providers now offer solutions at a price we believe will deliver a return in the first year of investment.

These simpler tools are not enough, though, to unlock all the potential value that connectivity holds for agriculture. To attain that, the industry must make full use of digital applications and analytics, which will require low latency, high bandwidth, high resiliency, and support for a density of devices offered by advanced and frontier connectivity technologies like LPWAN, 5G, and LEO satellites (Exhibit 1).

The challenge the industry is facing is thus twofold: infrastructure must be developed to enable the use of connectivity in farming, and where connectivity already exists, strong business cases must be made in order for solutions to be adopted. The good news is that connectivity coverage is increasing almost everywhere. By 2030, we expect advanced connectivity infrastructure of some type to cover roughly 80 percent of the world’s rural areas; the notable exception is Africa, where only a quarter of its area will be covered. The key, then, is to develop more—and more effective—digital tools for the industry and to foster widespread adoption of them.

As connectivity increasingly takes hold, these tools will enable new capabilities in agriculture:

• Massive Internet of Things. Low-power networks and cheaper sensors will set the stage for the IoT to scale up, enabling such use cases as precision irrigation of field crops, monitoring of large herds of livestock, and tracking of the use and performance of remote buildings and large fleets of machinery.
• Mission-critical services. Ultralow latency and improved stability of connections will foster confidence to run applications that demand absolute reliability and responsiveness, such as operating autonomous machinery and drones.
• Near-global coverage. If LEO satellites attain their potential, they will enable even the most remote rural areas of the world to use extensive digitization, which will enhance global farming productivity.

Connectivity’s potential for value creation

By the end of the decade, enhanced connectivity in agriculture could add more than $500 billion to global gross domestic product, a critical productivity improvement of 7 to 9 percent for the industry. 5 This represents our estimate of the total potential for value added in agricultural production; it is not an estimate of the agritech and precision-agriculture market size. Much of that value, however, will require investments in connectivity that today are largely absent from agriculture. Other industries already use technologies like LPWAN, cloud computing, and cheaper, better sensors requiring minimal hardware, which can significantly reduce the necessary investment. We have analyzed five use cases—crop monitoring, livestock monitoring, building and equipment management, drone farming, and autonomous farming machinery—where enhanced connectivity is already in the early stages of being used and is most likely to deliver the higher yields, lower costs, and greater resilience and sustainability that the industry needs to thrive in the 21st century (Exhibit 2).

It’s important to note that use cases do not apply equally across regions. For example, in North America, where yields are already fairly optimized, monitoring solutions do not have the same potential for value creation as in Asia or Africa, where there is much more room to improve productivity. Drones and autonomous machinery will deliver more impact to advanced markets, as technology will likely be more readily available there (Exhibit 3).

About the use-case research

The value of our agriculture-connectivity use cases resides primarily in labor efficiencies, input optimization, yield increases, reduced overhead, and improvements in operation and maintenance of machinery. Each use case enables a series of improvement levers in those areas that promise to enhance the productivity of farming (exhibit).

We applied those levers to the profitability drivers of agricultural production to derive an economic potential for the industry as a whole. For example, a use case might enable a 5 to 10 percent reduction in fertilizer usage, saving costs for the farmer, or enable 3 percent higher yields, leading to greater revenues for the farmer. In fact, higher yields represent the largest opportunity, with advanced connectivity potentially adding some $350 billion of value to global food production without additional inputs or labor costs.

Potential value initially will accrue to large farms that have more investing power and better incentives to digitize. Connectivity promises easier surveying of large tracts, and the fixed costs of developing IoT solutions are more easily offset in large production facilities than on small family farms. Crops like cereals, grains, fruits, and vegetables will generate most of the value we identified, for similar reasons. Connectivity enables more use cases in these sectors than in meat and dairy, because of the large average size of farms, relatively higher player consolidation, and better applicability of connected technologies, as IoT networks are especially adapted to static monitoring of many variables. It’s also interesting to note that Asia should garner about 60 percent of the total value simply because it produces the biggest volume of crops (see sidebar “About the use-case research”).

Use case 1: Crop monitoring

Connectivity offers a variety of ways to improve the observation and care of crops. Integrating weather data, irrigation, nutrient, and other systems could improve resource use and boost yields by more accurately identifying and predicting deficiencies. For instance, sensors deployed to monitor soil conditions could communicate via LPWAN, directing sprinklers to adjust water and nutrient application. Sensors could also deliver imagery from remote corners of fields to assist farmers in making more informed and timely decisions and getting early warnings of problems like disease or pests.

Smart monitoring could also help farmers optimize the harvesting window. Monitoring crops for quality characteristics—say, sugar content and fruit color—could help farmers maximize the revenue from their crops.

Most IoT networks today cannot support imagery transfer between devices, let alone autonomous imagery analysis, nor can they support high enough device numbers and density to monitor large fields accurately. Narrowband Internet of Things (NB-IoT) and 5G promise to solve these bandwidth and connection-density issues. The use of more and smoother connections between soil, farm equipment, and farm managers could unlock $130 billion to $175 billion in value by 2030.

Use case 2: Livestock monitoring

Preventing disease outbreaks and spotting animals in distress are critical in large-scale livestock management, where most animals are raised in close quarters on a regimen that ensures they move easily through a highly automated processing system. Chips and body sensors that measure temperature, pulse, and blood pressure, among other indicators, could detect illnesses early, preventing herd infection and improving food quality. Farmers are already using ear-tag technology from providers such as Smartbow (part of Zoetis) to monitor cows’ heat, health, and location, or technology from companies such as Allflex to implement comprehensive electronic tracing in case of disease outbreaks.

Similarly, environmental sensors could trigger automatic adjustments in ventilation or heating in barns, lessening distress and improving living conditions that increasingly concern consumers. Better monitoring of animal health and growth conditions could produce $70 billion to $90 billion in value by 2030.

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Use case 3: building and equipment management.

Chips and sensors to monitor and measure levels of silos and warehouses could trigger automated reordering, reducing inventory costs for farmers, many of whom are already using such systems from companies like Blue Level Technologies. Similar tools could also improve shelf life of inputs and reduce post-harvest losses by monitoring and automatically optimizing storage conditions. Monitoring conditions and usage of buildings and equipment also has the potential to reduce energy consumption. Computer vision and sensors attached to equipment and connected to predictive-maintenance systems could decrease repair costs and extend machinery and equipment life.

Such solutions could achieve $40 billion to $60 billion in cost savings by 2030.

Use case 4: Farming by drone

Agriculture has been using drones for some two decades, with farmers around the world relying on pioneers like Yamaha’s RMAX remote-controlled helicopter to help with crop spraying. Now the next generation of drones is starting to impact the sector, with the ability to survey crops and herds over vast areas quickly and efficiently or as a relay system for ferrying real-time data to other connected equipment and installations. Drones also could use computer vision to analyze field conditions and deliver precise interventions like fertilizers, nutrients, and pesticides where crops most need them. Or they could plant seed in remote locations, lowering equipment and workforce costs. By reducing costs and improving yields, the use of drones could generate between $85 billion and $115 billion in value.

Use case 5: Autonomous farming machinery

More precise GPS controls paired with computer vision and sensors could advance the deployment of smart and autonomous farm machinery. Farmers could operate a variety of equipment on their field simultaneously and without human intervention, freeing up time and other resources. Autonomous machines are also more efficient and precise at working a field than human-operated ones, which could generate fuel savings and higher yields. Increasing the autonomy of machinery through better connectivity could create $50 billion to $60 billion of additional value by 2030.

Additional sources of value

Connected technologies offer an additional, indirect benefit, the value of which is not included in the estimates given in these use cases. The global farming industry is highly fragmented, with most labor done by individual farm owners. Particularly in Asia and Africa, few farms employ outside workers. On such farms, the adoption of connectivity solutions should free significant time for farmers, which they can use to farm additional land for pay or to pursue work outside the industry.

We find the value of deploying advanced connectivity on these farms to achieve such labor efficiencies represents almost $120 billion, bringing the total value of enhanced connectivity from direct and indirect outcomes to more than $620 billion by 2030. The extent to which this value will be captured, however, relies largely on advanced connectivity coverage, which is expected to be fairly low, around 25 percent, in Africa and poorer parts of Asia and Latin America. Achieving the critical mass of adopters needed to make a business case for deploying advanced connectivity also will be more difficult in those regions, where farming is more fragmented than in North America and Europe.

Connected world: An evolution in connectivity beyond the 5G revolution

Implications for the agricultural ecosystem.

As the agriculture industry digitizes, new pockets of value will likely be unlocked. To date, input providers selling seed, nutrients, pesticides, and equipment have played a critical role in the data ecosystem because of their close ties with farmers, their own knowledge of agronomy, and their track record of innovation. For example, one of the world’s largest fertilizer distributors now offers both fertilizing agents and software that analyzes field data to help farmers determine where to apply their fertilizers and in what quantity. Similarly, a large-equipment manufacturer is developing precision controls that make use of satellite imagery and vehicle-to-vehicle connections to improve the efficiency of field equipment.

Advanced connectivity does, however, give new players an opportunity to enter the space. For one thing, telcos and LPWAN providers have an essential role to play in installing the connectivity infrastructure needed to enable digital applications on farms. They could partner with public authorities and other agriculture players to develop public or private rural networks, capturing some of the new value in the process.

Agritech companies are another example of the new players coming into the agriculture sphere. They specialize in offering farmers innovative products that make use of technology and data to improve decision making and thereby increase yields and profits. Such agritech enterprises could proffer solutions and pricing models that reduce perceived risk for farmers—with, for example, subscription models that remove the initial investment burden and allow farmers to opt out at any time—likely leading to faster adoption of their products. An Italian agritech is doing this by offering to monitor irrigation and crop protection for wineries at a seasonal, per-acre fee inclusive of hardware installation, data collection and analysis, and decision support. Agritech also could partner with agribusinesses to develop solutions.

Still, much of this cannot happen until many rural areas get access to a high-speed broadband network. We envision three principal ways the necessary investment could take place to make this a reality:

• Telco-driven deployment. Though the economics of high-bandwidth rural networks have generally been poor, telcos could benefit from a sharp increase in rural demand for their bandwidth as farmers embrace advanced applications and integrated solutions.
• Provider-driven deployment. Input providers, with their existing industry knowledge and relationships, are probably best positioned to take the lead in connectivity-related investment. They could partner with telcos or LPWAN businesses to develop rural connectivity networks and then offer farmers business models integrating connected technology and product and decision support.
• Farmer-driven deployment. Farm owners, alone or in tandem with LPWAN groups or telcos, could also drive investment. This would require farmers to develop the knowledge and skills to gather and analyze data locally, rather than through third parties, which is no small hurdle. But farmers would retain more control over data.

How to do it

Regardless of which group drives the necessary investment for connectivity in agriculture, no single entity will be able to go it alone. All of these advances will require the industry’s main actors to embrace collaboration as an essential aspect of doing business. Going forward, winners in delivering connectivity to agriculture will need deep capabilities across various domains, ranging from knowledge of farm operations to advanced data analytics and the ability to offer solutions that integrate easily and smoothly with other platforms and adjacent industries. For example, data gathered by autonomous tractors should seamlessly flow to the computer controlling irrigation devices, which in turn should be able to use weather-station data to optimize irrigation plans.

Connectivity pioneers in the industry, however, have already started developing these new capabilities internally. Organizations prefer keeping proprietary data on operations internal for confidentiality and competitive reasons. This level of control also makes the data easier to analyze and helps the organization be more responsive to evolving client needs.

But developing new capabilities is not the end game. Agriculture players able to develop partnerships with telcos or LPWAN players will gain significant leverage in the new connected-agriculture ecosystem. Not only will they be able to procure connectivity hardware more easily and affordably through those partnerships, they will also be better positioned to develop close relationships with farmers as connectivity becomes a strategic issue. Input providers or distributors could thus find themselves in a connectivity race. If input providers manage to develop such partnerships, they could connect directly with farmers and cut out distributors entirely. If distributors win that race, they will consolidate their position in the value chain by remaining an essential intermediary, closer to the needs of farmers.

The public sector also could play a role by improving the economics of developing broadband networks, particularly in rural areas. For example, the German and Korean governments have played a major role in making network development more attractive by heavily subsidizing spectrum or providing tax breaks to telcos. 6 “Das Breitbandförderprogramm des Bundes” [in German], Bundesministerium für Verkehr und digitale Infrastruktur, 2020, bmvi.de; 5G in Korea: Volume 1: Get a taste of the future, Samsung Electronics, 2019, samsungnetworks.com. Other regions could replicate this model, accelerating development of connective products by cost-effectively giving input providers and agritech companies assurance of a backbone over which they could deliver services. Eventual deployment of LEO satellite constellations would likely have a similar impact.

Agriculture, one of the world’s oldest industries, finds itself at a technological crossroads. To handle increasing demand and several disruptive trends successfully, the industry will need to overcome the challenges to deploying advanced connectivity. This will require significant investment in infrastructure and a realignment of traditional roles. It is a huge but critical undertaking, with more than $500 billion in value at stake. The success and sustainability of one of the planet’s oldest industries may well depend on this technology transformation, and those that embrace it at the outset may be best positioned to thrive in agriculture’s connectivity-driven future.

Lutz Goedde is a senior partner and global leader of McKinsey’s Agriculture Practice in the Denver office; Joshua Katz is a partner in the Stamford office; and Alexandre Menard is a senior partner in the Paris office, where Julien Revellat is an associate partner.

The authors wish to thank Nicolas D. Estais, Claus Gerckens, Vincent Tourangeau, and the McKinsey Center for Advanced Connectivity for their contributions to the article.

This article was edited by Daniel Eisenberg, a senior editor in the New York office.

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March 5, 2021

Importance of New Technologies for Crop Farming

by: Michael Langemeier and Michael Boehlje

Adoption of technology has been important to production agriculture for decades. Through the adoption of technology and improved managerial practices, aggregate agricultural U.S. farm output in the United States tripled from 1948 to 2017 with almost no corresponding increase in aggregate input (USDA-ERS, 2021). For reasons explained below, the adoption of technology in production agriculture is expected to accelerate in the next decade. This article discusses types of technology that are currently being adopted or that are likely to be adopted in the near future. Upcoming articles will discuss the critical role of information and precision agriculture technologies, possible payoffs of precision agriculture, automation and robotics, and gaps in skills pertaining to the adoption of new technologies.

Changes to Crop Agriculture

Crop farming around the world is undergoing a profound technological transition. The management of production is moving toward increased micro-management of production activities by individual field or location within a field driven by site-specific information about environmental, biological, and economic factors that affect physical output, profitability, and soil and water quality.

Increased use of monitoring technology will greatly expand the amount of information available regarding what affects plant growth and well-being. This will be made possible by innovations in sensors to use in monitoring and control systems, communication technologies, and data analytics. In addition, greater understanding of how various growth and environmental factors interact is forthcoming. This understanding will then be incorporated into management systems to determine optimum combinations of inputs at the field or within a field level. Precision farming in crop production includes the use of global positioning systems (GPS), yield monitors, and variable rate application technology to more precisely apply crop inputs to enhance growth, lower cost, and reduce environmental degradation.

Growing crops through precision production practices might be described as “biological manufacturing” which combines biotechnology and nutritional technology; monitoring, measuring, and information technology; and process control technology. The critical linchpin among these “technologies buckets” for successful execution is the data and information that can be continuously captured and utilized to manage the system and intervene in real time to control and enhance the plant growth process.

The transition of production agriculture from an industry that grows crops to one that biologically manufactures raw materials with specific attributes and characteristics for food and industrial use products is well underway. The discussion below will focus on three types of technology: biotechnology and nutritional technology; monitoring, measuring, and information technology; and process control technology.

Biotechnology and Nutritional Technology

The focus of biotechnology and nutritional technology is to manipulate the growth, attribute development, and deterioration process in plant production. An improved scientific base impacts not only plant growth but attribute development and is providing additional capacity to manipulate and control processes. Also, biotechnology is advancing our capacity to control and manipulate plant growth and development including attribute composition (for example, starch or amino acid composition) through genetic manipulation. By combining nutritional and biotechnology concepts with mechanical and other technologies to control or adjust the growth environment (temperature, humidity and moisture, pest and disease infestation, etc.), the process control approach and thinking that is part of the assembly line used in mechanical manufacturing becomes closer to reality in biological manufacturing.

Monitoring, Measuring, and Information Technology

The focus of this technology is to trace the development and/or deterioration of attributes in the plant growth process, and to measure the impact of controllable and uncontrollable variables that are impacting that growth process. In crop production, yield monitors, global positioning systems (GPS), global information systems (GIS), satellite or aerial photography and imagery, weather monitoring and measuring systems, and plant and soil sensing systems are part of this technology. In future years, inplant sensors to detect growth rates and disease characteristics may be available. These systems will be tied to growth models to detect ways to improve plant growth performance, as well as to financial and physical performance accounting systems to monitor overall performance. The computer technology to manipulate the massive amounts of information is readily available; new monitoring and measuring technology including near-infrared (NIR) and electromagnetic scanning is now being developed to measure a broad spectrum of characteristics of the plant growth process.

Process Control Technology

The concept of process control technology is to intervene with the proper adjustments or controls that will close the gap any time actual performance of a process deviates from potential performance. Greenhouse production increasingly utilizes such technology to manipulate sunlight, humidity, temperature, and other characteristics of the plant growth environment. Irrigation systems are an example of this technology in field crop production; modern irrigation systems tied to weather stations and plant and soil sensors automatically turn irrigation systems on and off to ensure that moisture levels are adequate for optimum growth. Variable rate application of fertilizer and chemicals and row shut-off technology are current examples of process control technology in rain-fed crop production. Modern precision planter technology that automatically adjusts seed placement, depth, and soil coverage based on soil sensors is another example.

Combining real time monitoring and measuring technology with anytime intervention process control technology has the potential to generate significant benefits. Any-time intervention technology allows one to detect a problem when it occurs and in real-time solve that problem rather than anticipate a possible problem and preemptively dispense control inputs that may be completely unnecessary (and thus costly) and possibly even harmful to the growth environment if that problem does not occur. For example, anytime intervention technology allows the detection of corn borers and the treatment of those borers once they meet an economic threshold, rather than spending funds and using materials in anticipation that a corn borer infestation might occur which are unneeded if the infestation does not reach an economic threshold during the growing season. A similar approach might be used to control weeds. Similar approaches to fertility management may facilitate lower levels of pre-season fertilizer applications by enabling additional applications during the growth season as real-time sensing technology and drop-down nozzle attachments for high clearance equipment enable split applications of fertilizer to be applied when needed. If such technology is developed, it may be less essential to use biotechnology to control certain insects or larger than necessary fertilizer applications to insure the optimum yield.

It would be unrealistic to expect these process control and sensing technologies and methods to be as successful as they have been in industrial manufacturing in reducing variability and systemizing the processes of producing manufactured goods such as automobiles, computers, or even chemical and industrial goods. However, it is also unrealistic to ignore the potential of these technologies in reducing variability and obtaining more control over biological growth processes so as to increase efficiency, reduce costs, improve quality, minimize environmental impacts and in general more systematically produce biological based attributes for food, feed, fuel, and fiber raw materials. In essence, this is what the concepts of biological manufacturing are all about, to use monitoring and measuring, biological and nutritional manipulation, and process control technologies to systematically manufacture food and industrial use products.

Concluding Comments

This article discusses types of technology that are currently being adopted or that are likely to be adopted in the near future. Specifically, technologies related to biotechnology and nutrition; technologies related to monitoring, measuring, and information; and technologies related to process control were briefly described. It is not an understatement to note that these technologies are going to result in profound changes to production agriculture operations. Upcoming articles will discuss the critical role of information technologies, possible payoffs of precision agriculture, automation and robotics, and gaps in skills pertaining to the adoption of new technologies in production agriculture.

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Erickson, B. and J. Lowenberg-DeBoer. “2020 Precision Agriculture Dealership Survey.” Departments of Agricultural Economics and Agronomy, Purdue University, August 2020.

Pope, M. and S. Sonka. “Evidence, Data and Farmer Decision Making.” farmdoc daily (10):45, Department of Agricultural and Consumer Economics, University of Illinois at Urbana-Champaign, March 11, 2020.

Thompson, N.M., C. Bir, D.A. Widmar, and J.R. Mintert. “Farmer Perceptions of Precision Agriculture Technology Benefits.” Journal of Agricultural and Applied Economics. 51(Issue 1, 2019):142-163.

United States Department of Agriculture, Economic Research Service. Statistics Service. Agricultural Productivity in the U.S., https://www.ers.usda.gov/data-products/agricultural-productivity-in-the-us/ , accessed on February 26, 2021.

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• Published: 27 April 2017

Technology: The Future of Agriculture

• Anthony King  

Nature volume  544 ,  pages S21–S23 ( 2017 ) Cite this article

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A technological revolution in farming led by advances in robotics and sensing technologies looks set to disrupt modern practice.

Over the centuries, as farmers have adopted more technology in their pursuit of greater yields, the belief that 'bigger is better' has come to dominate farming, rendering small-scale operations impractical. But advances in robotics and sensing technologies are threatening to disrupt today's agribusiness model. “There is the potential for intelligent robots to change the economic model of farming so that it becomes feasible to be a small producer again,” says robotics engineer George Kantor at Carnegie Mellon University in Pittsburgh, Pennsylvania.

Twenty-first century robotics and sensing technologies have the potential to solve problems as old as farming itself. “I believe, by moving to a robotic agricultural system, we can make crop production significantly more efficient and more sustainable,” says Simon Blackmore, an engineer at Harper Adams University in Newport, UK. In greenhouses devoted to fruit and vegetable production, engineers are exploring automation as a way to reduce costs and boost quality (see ‘ Ripe for the picking ’). Devices to monitor vegetable growth, as well as robotic pickers, are currently being tested. For livestock farmers, sensing technologies can help to manage the health and welfare of their animals (‘ Animal trackers ’). And work is underway to improve monitoring and maintenance of soil quality (‘ Silicon soil saviours ’), and to eliminate pests and disease without resorting to indiscriminate use of agrichemicals (‘ Eliminating enemies ’).

Although some of these technologies are already available, most are at the research stage in labs and spin-off companies. “Big-machinery manufacturers are not putting their money into manufacturing agricultural robots because it goes against their current business models,” says Blackmore. Researchers such as Blackmore and Kantor are part of a growing body of scientists with plans to revolutionize agricultural practice. If they succeed, they'll change how we produce food forever. “We can use technology to double food production,” says Richard Green, agricultural engineer at Harper Adams.

Ripe for the picking

The Netherlands is famed for the efficiency of its fruit- and vegetable-growing greenhouses, but these operations rely on people to pick the produce. “Humans are still better than robots, but there is a lot of effort going into automatic harvesting,” says Eldert van Henten, an agricultural engineer at Wageningen University in the Netherlands, who is working on a sweet-pepper harvester. The challenge is to quickly and precisely identify the pepper and avoid cutting the main stem of the plant. The key lies in fast, precise software. “We are performing deep learning with the machine so it can interpret all the data from a colour camera fast,” says van Henten. “We even feed data from regular street scenes into the neural network to better train it.”

In the United Kingdom, Green has developed a strawberry harvester that he says can pick the fruit faster than humans. It relies on stereoscopic vision with RGB cameras to capture depth, but it is its powerful algorithms that allow it to pick a strawberry every two seconds. People can pick 15 to 20 a minute, Green estimates. “Our partners at the National Physical Laboratory worked on the problem for two years, but had a brainstorm one day and finally cracked it,” says Green, adding that the solution is too commercially sensitive to share. He thinks that supervised groups of robots can step into the shoes of strawberry pickers in around five years. Harper Adams University is considering setting up a spin-off company to commercialize the technology. The big hurdle to commercialization, however, is that food producers demand robots that can pick all kinds of vegetables, says van Henten. The variety of shapes, sizes and colours of tomatoes, for instance, makes picking them a tough challenge, although there is already a robot available to remove unwanted leaves from the plants.

Another key place to look for efficiencies is timing. Picking too early is wasteful because you miss out on growth, but picking too late slashes weeks off the storage time. Precision-farming engineer Manuela Zude-Sasse at the Leibniz Institute for Agricultural Engineering and Bioeconomy in Potsdam, Germany, is attaching sensors to apples to detect their size, and levels of the pigments chlorophyll and anthocyanin. The data are fed into an algorithm to calculate developmental stage, and, when the time is ripe for picking, growers are alerted by smartphone.

So far, Zude-Sasse has put sensors on pears, citrus fruits, peaches, bananas and apples ( pictured ). She is set to start field trials later this year in a commercial tomato greenhouse and an apple orchard. She is also developing a smartphone app for cherry growers. The app will use photographs of cherries taken by growers to calculate growth rate and a quality score.

Growing fresh fruit and vegetables is all about keeping the quality high while minimizing costs. “If you can schedule harvest to optimum fruit development, then you can reap an economic benefit and a quality one,” says Zude-Sasse.

Eliminating enemies

The Food and Agriculture Organization of the United Nations estimates that 20–40% of global crop yields are lost each year to pests and diseases, despite the application of around two-million tonnes of pesticide. Intelligent devices, such as robots and drones, could allow farmers to slash agrichemical use by spotting crop enemies earlier to allow precise chemical application or pest removal, for example. “The market is demanding foods with less herbicide and pesticide, and with greater quality,” says Red Whittaker, a robotics engineer at Carnegie Mellon who designed and patented an automated guidance system for tractors in 1997. “That challenge can be met by robots.”

“We predict drones, mounted with RGB or multispectral cameras, will take off every morning before the farmer gets up, and identify where within the field there is a pest or a problem,” says Green. As well as visible light, these cameras would be able to collect data from the invisible parts of the electromagnetic spectrum that could allow farmers to pinpoint a fungal disease, for example, before it becomes established. Scientists from Carnegie Mellon have begun to test the theory in sorghum ( Sorghum bicolor ), a staple in many parts of Africa and a potential biofuel crop in the United States.

Agribotix, an agriculture data-analysis company in Boulder, Colorado, supplies drones and software that use near-infrared images to map patches of unhealthy vegetation in large fields. Images can also reveal potential causes, such as pests or problems with irrigation. The company processes drone data from crop fields in more than 50 countries. It is now using machine learning to train its systems to differentiate between crops and weeds, and hopes to have this capability ready for the 2017 growing season. “We will be able to ping growers with an alert saying you have weeds growing in your field, here and here,” says crop scientist Jason Barton, an executive at Agribotix.

Modern technology that can autonomously eliminate pests and target agrichemicals better will reduce collateral damage to wildlife, lower resistance and cut costs. “We are working with a pesticide company keen to apply from the air using a drone,” says Green. Rather than spraying a whole field, the pesticide could be delivered to the right spot in the quantity needed, he says. The potential reductions in pesticide use are impressive. According to researchers at the University of Sydney's Australian Centre for Field Robotics, targeted spraying of vegetables used 0.1% of the volume of herbicide used in conventional blanket spraying. Their prototype robot is called RIPPA (Robot for Intelligent Perception and Precision Application) and shoots weeds with a directed micro-dose of liquid. Scientists at Harper Adams are going even further, testing a robot that does away with chemicals altogether by blasting weeds close to crops with a laser. “Cameras identify the growing point of the weed and our laser, which is no more than a concentrated heat source, heats it up to 95 °C, so the weed either dies or goes dormant,” says Blackmore.

Animal trackers

Smart collars — a bit like the wearable devices designed to track human health and fitness — have been used to monitor cows in Scotland since 2010. Developed by Glasgow start-up Silent Herdsman, the collar monitors fertility by tracking activity — cows move around more when they are fertile — and uses this to alert farmers to when a cow is ready to mate, sending a message to his or her laptop or smartphone. The collars ( pictured ), which are now being developed by Israeli dairy-farm-technology company Afimilk after they acquired Silent Herdsman last year, also detect early signs of illness by monitoring the average time each cow spends eating and ruminating, and warning the farmer via a smartphone if either declines.

“We are now looking at more subtle behavioural changes and how they might be related to animal health, such as lameness or acidosis,” says Richard Dewhurst, an animal nutritionist at Scotland's Rural College (SRUC) in Edinburgh, who is involved in research to expand the capabilities of the collar. Scientists are developing algorithms to interrogate data collected by the collars.

In a separate project, Dewhurst is analysing levels of exhaled ketones and sulfides in cow breath to reveal underfeeding and tissue breakdown or excess protein in their diet. “We have used selected-ionflow-tube mass spectrometry, but there are commercial sensors available,” says Dewhurst.

Cameras are also improving the detection of threats to cow health. The inflammatory condition mastitis — often the result of a bacterial infection — is one of the biggest costs to the dairy industry, causing declines in milk production or even death. Thermal-imaging cameras installed in cow sheds can spot hot, inflamed udders, allowing animals to be treated early.

Carol-Anne Duthie, an animal scientist at SRUC, is using 3D cameras to film cattle at water troughs to estimate the carcass grade (an assessment of the quality of a culled cow) and animal weight. These criteria determine the price producers are paid. Knowing the optimum time to sell would maximize profit and provide abattoirs with more-consistent animals. “This has knock on effects in terms of overall efficiency of the entire supply chain, reducing the animals which are out of specification reaching the abattoir,” Duthie explains.

And researchers in Belgium have developed a camera system to monitor broiler chickens in sheds. Three cameras continually track the movements of thousands of individual birds to spot problems quickly. “Analysing the behaviour of broilers can give an early warning for over 90% of problems,” says bioengineer Daniel Berckmans at the University of Leuven. The behaviour-monitoring system is being sold by Fancom, a livestock-husbandry firm in Panningen, the Netherlands. The Leuven researchers have also launched a cough monitor to flag respiratory problems in pigs, through a spin-off company called SoundTalks. This can give a warning 12 days earlier than farmers or vets would normally be able to detect a problem, says Berckmans. The microphone, which is positioned above animals in their pen, identifies sick individuals so that treatment can be targeted. “The idea was to reduce the use of antibiotics,” says Berckmans.

Berckmans is now working on downsizing a stress monitor designed for people so that it will attach to a cow's ear tag. “The more you stress an animal, the less energy is available from food for growth,” he says. The monitor takes 200 physiological measurements a second, alerting farmers through a smartphone when there is a problem.

Silicon soil saviours

The richest resource for arable farmers is soil. But large harvesters damage and compact soil, and overuse of agrichemicals such as nitrogen fertilizer are bad for both the environment and a farmer's bottom line. Robotics and autonomous machines could help.

Data from drones are being used for smarter application of nitrogen fertilizer. “Healthy vegetation reflects more near-infrared light than unhealthy vegetation,” explains Barton. The ratio of red to near-infrared bands on a multispectral image can be used to estimate chlorophyll concentration and, therefore, to map biomass and see where interventions such as fertilization are needed after weather or pest damage, for example. When French agricultural technology company Airinov, which offers this type of drone survey, partnered with a French farming cooperative, they found that over a period of 3 years, in 627 fields of oilseed rape ( Brassica napus ), farmers used on average 34 kilograms less nitrogen fertilizer per hectare than they would without the survey data. This saved on average €107 (US$115) per hectare per year.

Bonirob ( pictured ) — a car-sized robot originally developed by a team of scientists including those at Osnabrück University of Applied Sciences in Germany — can measure other indicators of soil quality using various sensors and modules, including a moisture sensor and a penetrometer, which is used to assess soil compaction. According to Arno Ruckelshausen, an agricultural technologist at Osnabrück, Bonirob can take a sample of soil, liquidize it and analyse it to precisely map in real time characteristics such as pH and phosphorous levels. The University of Sydney's smaller RIPPA robot can also detect soil characteristics that affect crop production, by measuring soil conductivity.

Soil mapping opens the door to sowing different crop varieties in one field to better match shifting soil properties such as water availability. “You could differentially seed a field, for example, planting deep-rooting barley or wheat varieties in more sandy parts,” says Maurice Moloney, chief executive of the Global Institute for Food Security in Saskatoon, Canada. Growing multiple crops together could also lead to smarter use of agrichemicals. “Nature is strongly against monoculture, which is one reason we have to use massive amounts of herbicide and pesticides,” says van Henten. “It is about making the best use of resources.”

Mixed sowing would challenge an accepted pillar of agricultural wisdom: that economies of scale and the bulkiness of farm machinery mean vast fields of a single crop is the most-efficient way to farm, and the bigger the machine, the more-efficient the process. Some of the heaviest harvesters weigh 60 tonnes, cost more than a top-end sports car and leave a trail of soil compaction in their wake that can last for years.

But if there is no need for the farmer to drive the machine, then one large vehicle that covers as much area as possible is no longer needed. “As soon as you remove the human component, size is irrelevant,” says van Henten. Small, autonomous robots make mixed planting feasible and would not crush the soil.

In April, researchers at Harpers Adams began a proof-of-concept experiment with a hectare of barley. “We plan to grow and harvest the entire crop from start to finish with no humans entering the field,” says Green. The experiment will use existing machinery, such as tractors, that have been made autonomous, rather than new robots, but their goal is to use the software developed during this trial as the brains of purpose-built robots in the future. “Robots can facilitate a new way of doing agriculture,” says van Henten. Many of these disruptive technologies may not be ready for the prime time just yet, but the revolution is coming.

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King, A. Technology: The Future of Agriculture. Nature 544 , S21–S23 (2017). https://doi.org/10.1038/544S21a

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