From Farm to Cloud: Precision Agriculture

Big data is helping farming become more efficient and waste less with specific crop management recommendations. But with little to no regulation, farmers are concerned that their data could be used against them.  

In a digital age, privacy has become a growing concern. Big data has helped social media companies tailor the content that appears on your screen, determine those at risk for certain health conditions, and optimize manufacturing performance. At the same time is has generated concern over wrongful manipulation of consumers through leveraging collected data. Agriculture is no exception. A notable example of the double-edge of big data becomes evident in precision agriculture. With a need for crop yield to keep up with population growth and the creation of more farmland, it becomes necessary to find ways to increase productivity with less land. Precision agriculture has the power to increase economic and environmental sustainability, but there are some concerns.

Precision agriculture, also called site-specific crop management or even smart farming, treats agricultural land as a collection of microsites instead of an aggregate data point. What that means is that instead of using the same amount of water, fertilizer, pesticide on every crop, treatments are individualized so that only the amount necessary for the crop is used. An area with more moist soil will need less water than one with drier soil, and that decision is made using data collected at each microsite. This information is typically collected in field with sensors on machinery like tractors or harvesters. The type of data collected can include crop yield, soil moisture, soil fertility, and number of seeds planted for every crop. With that information, machinery can adjust seed or fertilizer distribution and target pesticide use in a fully automated process.

The benefits are obvious—more efficient use of herbicides, pesticides, water, fertilizer, and fuel typically lead to less waste. Less excess fertilizer will runoff into ground and surface waters if they are not overused. In conjunction with several other environmental and agricultural groups, the Association of Equipment Manufactures reported that with the current levels of precision agriculture two million acres of deforestation was avoided, 100 million fewer gallons on fossil fuel was used, 750,000 Olympic-sized swimming pools of water was saved, and thirty million fewer pounds of herbicide was used. The precision agriculture market will continue to grow, expecting to reach $11,106.7 million by 2025.

For a while, the data collected on a farm was kept on the farm. Predictions and measurements of soil fertility were only compared to data points from the previous harvest on the same farm. However, there is a new opportunity for big data; data from several places started to be aggregated in the cloud by large agriculture machine companies to make more accurate predictions. Although this has the power to increase profitability, there is a growing concern over farmer data privacy. In 2013, a couple of the largest agriculture machine companies, Monsanto and John Deere, started offering this service. Farm owners were concerned that their data would be sold to competitors, seed distributors, chemical companies, and even commodity traders. With such a wealth of information, one could predict the future of the market and manipulate prices of agricultural inputs, disadvantaging farmers.

Currently, there is no regulatory system in the United States targeted specifically at data collection in the agriculture industry—current systems only look at industry trends or the food product itself. An agricultural technology company would not typically be the target of the Federal Trade Commission’s data privacy enforcement, so there is less incentive to be diligent in respecting farmer data ownership. There have been a few attempts at self-regulation. This includes the Privacy and Security Principles for Farm Data established by the American Farm Bureau Federations and other stakeholders; it establishes a standardized way of collecting and sharing data. Also came the development of Ag Data Transparent, an independent group that gives a seal of approval indicating that certain data privacy standards have been met by certain companies.

Alongside the widespread adoption of precision agriculture, it is necessary to address farmer’s privacy concerns. Although, this blog focused on how big data is creating vulnerabilities within the agriculture industry, the same is true across our economy. Big data can improve efficiency, but it also comes with a dark side that must be carefully considered as we look for solution to complex challenges like food security and climate change.  

This insight is a part of our Undergraduate Seminar Fellows’ Student Blog Series. Learn more about the Undergraduate Climate and Energy Seminar.

Linda Wu

Undergraduate Seminar Fellow
Linda Wu is pursuing a dual degree in Wharton and in the College of Arts and Sciences. Wu is also a 2022 Undergraduate Student Fellow.