Contributing Author: Katherine Walla
On fields across the world, phones, tablets, drones, and other technologies are changing how food is grown. Through these devices, artificial intelligence (AI)—technology able to perform tasks that require human intelligence—may help farmers use the techniques they already know and trust on a bigger scale. And Big Data—data sets that reveal telling patterns about growth, yield, weather, and more—may help farmers make better decisions before crises strike.
According to the reportreleased in 2018, may help produce more food, use less water, limit resource consumption, redirect food waste, and lower food prices—all while improving the lives and incomes of farmers and food producers. “Recent advances have the potential for big breakthroughs in the ways we grow, store, transport, distribute, and consume food,” says the Refresh Report. “From production to consumption, this digital transformation, in tandem with new ecological services, will prove critical to reducing greenhouse gasses, addressing the multiple causes of food insecurity, and feeding the planet in the 21st century.”
But AI and Big Data may also present new challenges and risks for farmers, says former Secretary of Agriculture Tom Vilsack. Data gathering may presentif only certain farmers have the connectivity and funding to collect and comprehend the data. AI presents , as private ownership and development in AI may equip entrepreneurs, innovators, and companies with the power to control who owns, uses, and benefits from these technologies—for or against equity in the food system.
While AI and Big Data may present challenges for farmers, the regulatory system controlling tech development may also let farmers down: as regulation over general AI and Big Data slowly opens its gates for innovation, farmers may lack access to agriculture-specific technologies at crucial times for their farms and businesses. “To the extent that we can advance the regulatory conversation, we need to be far more specific—we need to get below the layer of talking about AI in just a general sense. We need to start talking about real applications and solutions,” says Andrew Kim, Manager of Government Affairs and Public Policy at Google.
Food Tank is highlighting 20 tools to recognize innovations changing agriculture and improving technology access worldwide through AI and Big Data.
Agua para Riego (AGRI), or Irrigation Water, helps farmers find water sources for their irrigation systems. Initially developed for use in western Honduras, AGRI combines information about climate, soils, land cover, and hydrology to create texture class maps which display close water sources and sites for building reservoirs. Currently, the ’s deploys AGRI tools to restore deforested and degraded land across Latin America.
aWhere provides agricultural information and insight to farmers and growers globally. Now a Certified B Corporation, aWhere includes services such as Ag-Weather, which provides real-time and historical data on weather variables, and Agronomics, which helps farmers make predictions based on data about precipitation, growth stages, and crop stress. The company provides its services not only to farmers and businesses, but also to governments and NGOs that help small-holder farmers maintain healthier yields.
Blue River Technology’s See & Spray machines use computer vision and machine learning to spray weeds with precision. Aiming to deter the growth of herbicide resistance around the world, the tech limits herbicide broad-cast spraying by identifying weeds amongst crops and plants and deploying a treatment for each weed. Acquired by John Deere, Blue River Technology equips farmers to limit their herbicide spraying by up to 90 percent.
Connectera’s IDA uses TensorFlow, Google’s machine learning framework, to collect data about the behavior of cows and help farmers learn more about their herds’ health, habits, and life. TensorFlow is an open-source library of data and information that is open to anyone. Connectera’s IDA collects information and tracks activities like eating, drinking, resting, fertility, temperature, and more. Using the information to make predictions about problems like digestive disorders, Connectera hopes farmers can use IDA to increase production and protect their herds.
The Dynamic Research Evaluation for Management python version 2.1 (DREAMpy) measures the economic impact of global agricultural development projects. Developed by the IFPRI and Vitamin Software for the Program for Biosafety Systems’ Biotechnology & Biosafety Rapid Assessment and Policy Platform, allows users to plug in data to Excel sheets that simulate various economic models and scenarios.Pre-implementation, development program directors can predict economic factors that may change in a community, including technological development, tax rates, and price elasticity. In June 2018, DREAMpy launched publicly for free use world-wide.
The Ecological Productivity Management Information System (EcoProMIS) helps rice and oil palm producers in Columbia estimate their yields and greenhouse gas emissions—nearly in real-time. Using space technology like satellites, EcoProMIS tracks how crops perform in various conditions and joins the aerial data with data from farmers themselves, demonstrating their farms’ crop production and biodiversity. EcoProMIS aims to not only help farmers improve their environmental and financial efficiency, but also develop their skills and understanding of crop management’s effects on income, productivity, and sustainability.
FARMWAVE’s AI data models help farmers make crucial decisions to maintain and preserve their farms. With the app-based tools, farmers can identify pest damage and disease through photos, create easy field reports that automatically include information like weather and location, and even count maize kernels rapidly with photo scans to estimate yield. With the technology, FARMWAVE says farmers can reduce crop destruction and increase yields by 20–30 percent.
Gender-Responsive and Climate-Resilient Agriculture for Nutrition (GCAN) from IFPRI aims to make the decision to adopt Climate Smart Agriculture (CSA) practices easier for farmers by providing data showing a connection between CSA practices and positive farming and nutrition outcomes. By making the connection between gender, nutrition, and CSA practices, GCAN will recommend technologies and approaches to help women and young farmers surmount barriers to adopting CSA practices—like poor access to information and resources to adopt desired practices.
The Global Agricultural Research Data Innovation & Acceleration Network (GARDIAN) provides data for the CGIAR’s Platform for Big Data. Data provided by GARDIAN equips experts all over the world to tackle agricultural challenges from Africa and Asia to Latin America and the Caribbean. As part of the platform’s mission to create an innovation space for agriculture and erase world hunger through agricultural science, CGIAR will democratize all of GARDIAN’s data to make it available to every innovator, farmer, and decision-maker in every country and every sector of the food system.
Hello Tractor uses artificial intelligence to improve farmer access to smarter, better maintained, and more profitable tractors in Nigeria. Powered by ’s AI and blockchain technology, Hello Tractor allows farmers to request tractor service via an app: tractor owners can then provide an available tractor and complete the service, monitored by the farmer on the app. Hello Tractor partnered with IBM Research to use machine learning with image recognition to predict the quality of cultivation and harvest. The app also organizes banks financing tractors and dealers that service them.
HerdDogg’s technology monitors pasture-raised livestock using smart ear tags and mobile receivers. The tags store and send data like herd count, changes in location, patterns of animal behavior, and even heat alerts to help ranchers monitor their livestock. The technology helps farmers access data anytime and anywhere, whereas farmers using traditional tags must approach each animal to perform similar tracking and analysis.
’s Sustainable Modernization of Traditional Agriculture project, helps conduct collaborative breeding projects with farmers to improve native maize seed in Mexico. Using conventional technology, CIMMYT aims to develop a hybrid maize breed that helps achieve objectives like raising Mexico’s production of rainfed maize and promoting the development of the maize seed industry in Mexico. MasAgro’s improved maize seeds are tested in collaboration with the local seed sector to ensure that the tech-breeded maize seeds benefit food security in Mexico., a component of CIMMYT
The Nutrition Early Warning System (NEWS) processes data relevant to food and nutrition in sub-Saharan Africa in an effort to improve nutrition. The tool’s data not only provides an early warning system to alert decision-makers to nutrition threats before crises strike, but the data also strengthens the tool’s intelligence, locating patterns and trends that can help speed up nutrition-improving responses globally. NEWS’s surveillance system also helps accumulate a profile of proven solutions worldwide that national and regional leaders can consult for guidance.
Picture-Based Insurance (PBI) helps farmers access, afford, and understand crop insurance. Equipped with a free app on their smartphones, farmers can upload photos of their crops every day from sowing to harvest. After harvest, local agronomists analyze each photo to determine the extent to which farmers suffered crop damage, verify losses, and deliver insurance payouts directly to farmers’ bank accounts. The tool not only makes crop insurance more attractive and accessible to small farmers, but also opens up opportunities to reach farmers with advice for sustainable practices and managing local weather or agriculture-related events.
by PEAT GmbH
Branded as a mobile crop doctor, the Plantix app aims to help farmers, agricultural workers, and consultants increase their productivity. Using the app, farmers can take pictures of their crops and receive information about the plant—and any potential diseases it may face. The app also connects farmers to a community of experts and databases collecting tips to increase yields and treat disease.
PlantVillage Nuru helps farmers diagnose crop diseases, even without an internet connection. Developed at Penn State University with the International Institute of Tropical Agriculture (IIAT) and the United Nations Food and Agriculture Organization (FAO), the app uses Google’s Tensorflow machine learning tool to diagnose crops like cassava and potato. While the app currently helps farmers in Africa identify fall armyworm infections, the app continues to learn how to diagnose the most pressing diseases around the world like lanternfly pests in Pennsylvania.
Smart Ag develops autonomously operated tractor technology, compatible with any brand of equipment, to help farmers limit the time and effort needed to grow the same amount of crops. Smart Ag’s AutoCart allows users to operate grain carts remotely and enables users to set the speed, unloading locations, and more. And Smart Ag’s SmartNX kit connects any machine to other machines and the cloud, adding the machine’s performance and findings to a farm’s overall data set.
Sustainable Water and Innovative Irrigation Management (SWIIM), developed with the help of the U.S. Department of Agriculture (USDA), provides water use data that may help farmers or landowners manage their agricultural water use. The technology monitors water flows, water consumption levels, and precipitation and weather data to help users understand their water expenses. With data collected over 60 times an hour for growers, SWIIM may help users make decisions related to water overuse quickly.
Taranis addresses crop loss due to insects, crop disease, weeds, and nutrient deficiencies by helping land managers and producers monitor their fields. Combining imagery from satellites, planes, and drones, Taranis contributes to weather forecasting, disease predicting, scouting, and more. The international startup also assembles data into maps, reports, graphs, and insights to help users understand their data visually.
“trained” to understand normal patterns of change in greenness. The system then marks areas where land-cover dramatically changes so that people worldwide can envision the costs of continuing environmentally unfriendly practices.tracks human-caused land-cover changes across the world, from Honduras to Vietnam. Knowing that natural vegetation follows a predictable pattern of changes in greenness in certain environmental conditions, CIAT joined with partners like The Program on Forestry, Trees, and Agroforestry; and The Nature Conservancy to develop a network
Trace Genomics helps farmers optimize their fields’ potential by analyzing the soil. Farmers send soils, and the tech quantifies microbes in the soil, which Trace Genomics then decodes to help farmers understand the untapped potential of their soil. Trace Genomics has mapped over 150,000 acres, forming a comprehensive database of soils in the United States. Addressing concerns over data ownership and use, Trace Genomics keeps information anonymous.