periodiCALS, Vol. 9, Issue 1, 2019
Garrett Miller ’07 moves deliberately through the dairy barn, looking for specific new and expectant mothers after an alert on his computer indicated signs of illness.
As with human mothers, pregnancy can stress bovine health. Previously, cows at Oakwood Dairy in Auburn, New York, were examined daily by farmers. Now, the more than 1,200 animals at the dairy wear collars equipped with sensors that provide constant health monitoring, which translates into individual care.
“The sensors catch cows so quick sometimes we don’t know what’s wrong with them. Sometimes they look fine, and then have a disease,” said Miller, who manages the herd at Oakwood. “My job has changed to provide overall higher levels of care. I grew up on a 200-cow dairy; I love cows, and it’s why I chose to farm. We’re working to feed the world.”
These types of rapid and radical changes are happening across agriculture as digital technology expands a farmer’s capacity to produce high-quality, nutritious food. The stakes are high: Global population is expected to increase by more than 25 percent in the coming decades, reaching nearly 10 billion people by 2050.
“Critical resources needed to meet this challenge are already strained,” said Susan McCouch, Ph.D. ’90, the Barbara McClintock Professor of Plant Breeding and Genetics. “Globally, most arable land is in production. The planet’s supplies of freshwater and energy are being tested, and food security is being jeopardized by climate change, harvest loss and food waste. The world is at a precarious point.”
To address some of the most critical issues affecting the future of the global food supply, the Cornell Initiative for Digital Agriculture (CIDA) was created by faculty to leverage interdisciplinary research strengths across the university. More than 100 faculty have partnered on projects that integrate information and data science, engineering, and food and agricultural systems. These collaborations are creating disruptive and cutting-edge technologies and fostering a pipeline of practical innovations that improve real-time decision making throughout the food system.
McCouch, who directs CIDA, said now is the time to re-envision global agriculture, including food production, processing and distribution; how natural resources are used and conserved; and the ways social and agricultural systems interact to support healthy individuals, communities and the environment.
“Cornell, with its prestigious Ivy League researchers and Land-Grant mission to serve, is uniquely positioned to transform collaborative insights from the lab into applied solutions in the field. The combined passions and talents of our faculty, staff and students manifest into creative approaches and solutions needed to tackle these intractable challenges and to do it sustainably,” she said.
The work is diverse and vast: Researchers in one project are working on real-time sensors to provide up-to-the-minute weather forecasting predictions for farms, while elsewhere engineers collaborate with plant scientists to develop soft-touch robots that count vineyard grape clusters and predict yield.
Cornell research is revolutionizing the 10,000-year history of plant breeding, as robots, artificial intelligence (AI) and machine learning are deployed to measure plant traits in real time. Mike Gore, Ph.D. ’09, associate professor of plant breeding and genetics in the School of Integrative Plant Science, and his team are developing AI for autonomous vehicles that can count individual plants, measure plant height and check individual leaves for disease. The data inform breeding decisions, which can speed release of new plant varieties by years.
Maricelis Acevedo, associate director for science for the Delivering Genetic Gain in Wheat project, managed by International Programs at Cornell CALS, is collaborating to develop forecasting and prediction models that guide decisions on fungicide use and resistant wheat varieties with near-real-time data. Multispectral cameras, drones and sensors are being used to help plant breeders select better wheat germplasm for variety development.
Freely available shareware, apps and databases created on campus are expanding Cornell’s outreach. Kristan Reed, assistant professor in the Department of Animal Science, is creating an open-source model that looks at the farm, from crops to cows, as a whole system. The model simulates flows of carbon, nitrogen and phosphorus to identify how to improve farm production efficiency and minimize environmental impacts.
At Oakwood and other dairy farms, Julio Giordano, St. John Family Sesquicentennial Faculty Fellow in Dairy Cattle Management in the Department of Animal Science, is combining sensor data with AI machine learning to improve disease diagnosis and predict future performance.
These and other digital agriculture technologies offer cost-effective solutions for farms of all sizes. For small enterprises, reducing labor-intensive tasks can open room for growth. For large operations, enhancing or replacing hard-to-find labor can ensure financial stability.
“There is a great need for agriculture and food systems at large to be resilient, efficient and equitable,” said Jan Nyrop, associate dean and director of the Cornell University Agricultural Experiment Station and Cornell AgriTech. “Digital agriculture is not just about solving current issues; it’s also about anticipating the challenges and designing the future farm to meet them.”
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