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With the world’s population forecast by the United Nations to reach 9.8 billion by 2050, increasing agricultural productivity of available farmland is vital. At the same time, industrialized agriculture has resulted in depleted soil carbon and degraded soil health, requiring farmers to increase the use of fertilizers, chemical herbicides, and pesticides to maintain productivity.

Lawrence Berkeley National Lab scientists Ben Brown and Haruko Wainwright have been working with the University of Arkansas and Glennoe Farms on a pilot project called the “AR1K Smart Farm” project to improve sustainability in agriculture – increasing the yields while reducing chemical inputs and improving soil health. At the 1,000 acre farm near Stuttgart, Arkansas, the scientists are deploying a diverse array of sensors – including drones – that can monitor critical plant, soil, and weather properties, including carbon and nitrogen content, plant health, plant disease, and leaf chemistry. The scientists are also using surface geophysical techniques to map soil electrical properties in 3-D, providing additional information on soil health and structure. This amount and level of data has not been previously available to farmers.

Machine learning is used to tie all the data together to provide actionable intelligence to the farmer. In the 2019 season, chemical inputs were reduced by 60% with no statistically significant impacts on yield – ameliorating environmental impacts of agriculture, including harmful algal blooms, while increasing net income for the farmer. The combination of machine learning and sophisticated sensors and techniques will create an unparalleled level of decision support for farmers, and eventually may enable researchers to engineer microbial communities to enhance soil productivity. These technologies can increase crop yields and value, reduce chemical fertilizer use, while de-risking agriculture for farmers – all in a way that is beneficial to the environment. Ultimately, the scientists hope to develop microbial amendments to replace the carbon, phosphorus, and other lost soil nutrients.

This farm in Arkansas my soon be the most scientifically advanced farm in the world. Credit Jay McEntire

Artificial Intelligence Enables Smart Farming

Lawrence Berkeley National Laboratory |
University of Arkansas (Arkansas)
Glennoe Farms (Arkansas)
Publication Date
Feb 28, 2020
Agreement Type
Material Transfer Agreement (MTA), Cooperative Research and Development Agreement (CRADA)