Talon Becker is a University of Illinois Extension Commercial Agriculture Educator working with the Data-Intensive Farm Management (DIFM) project to help farmers conduct their own on-farm trials throughout Illinois.
What seeding rate and/or fertilizer rate will result in the best possible yield for my field? This is one of the many questions that farmers ask themselves every year and that researchers and agronomists have been trying to answer for decades.
Numerous environmental and genetic hybrid or variety factors, either on their own or through interaction with each other, influence the actual optimum seeding and fertilizer rates for a given field or section of a field.
This is not a new concept. The influence of genetic and environmental variation and the interaction of these two major factors, often denoted as “GxE,” have been recognized since the early days of modern agronomic research.
Until recently, the best tools at the disposal of agronomists and agricultural researchers for estimating and accounting for the influence of these sources of variation in the estimation of optimal levels of a given agronomic input, such as seeding rate, have been multi-site and multi-year replicated trials.
The Data-Intensive Farm Management Project was featured in the recent February edition of The Furrow.
Precision ag technology is spurring a dramatic change in agricultural research. It’s replacing the time-consuming test plot techniques of the past – the marking flags, tape measures, weigh wagons, and grad students – with today’s automated computer files, variable-rate controllers, and yield monitors. These new tools are empowering growers to easily and economically generate data that makes on-farm research a reality.
“This new approach is a real game-changer,” says David Bullock, agricultural economist at the University of Illinois. “The future could see farmers conducting experiments on their fields as routinely as they now take soil samples. The result will be management recommendations based on field data, rather than a ‘rule of thumb’ recommendation.”
Take a look at this upcoming workshop hosted by the Center for Digital Agriculture on the University of Illinois campus. A great opportunity for anyone interested in data science and Central Illinois agriculture.
The American Society of Agronomy, the Crop Science Society of America, and the Soil Science Society of America hosted the2019 International Annual Meeting, “Embracing the Digital Environment,” on November 10-13, 2019, in San Antonio, Texas.
Rodrigo Trevisan, graduate student in Crop Sciences, gave two presentations titled, Understanding the Spatial Variability of Optimum Nitrogen Rates Using Remote Sensing and on-Farm Precision Experimentation and Using Deep Learning to Predict Optimum Crop Management Decisions.
A data management research team, which includes University of Illinois researchers, is helping farmers leverage their existing precision technology to conduct on-farm trials and enhance their management, according to David Bullock, U of I agricultural and consumer economics professor.
Bullock, who spoke Thursday at U of I Agronomy Day, leads the Data Intensive Farm Management (DIFM) research team that generates and analyzes agronomic data to improve how the world fertilizes crops. DIFM is in the fourth year of a $4 million research project funded by the USDA National Institute of Food and Agriculture. -FarmWeekNow
Click here to read the full article by FarmWeekNow.
Congratulations to DIFM’s German Mandrini, recipient of the Agricultural and Consumer Economics “Outstanding M.S. Thesis” 2018 award for his thesis titled, “Using Crop Simulation to Optimize Variable Rate Experimentation.” Mandrini studies under Dr. David Bullock.
Pictured above is German Mandrini receiving his award with Dr. Bullock at the Award Ceremony.
Rodrigo Goncalves Trevisan is a new graduate student in crop sciences under Professor Nicolas Martin who is focused on harnessing the power of new analytical methods to improve the decision-making process in agricultural systems. Trevisan received a baccalaureate degree in agronomy from the Federal University of Mato Grosso, and his master’s degree in agricultural systems engineering from the Luis de Queiroz College of Agriculture at the University of Sao Pãulo. He is the precision agriculture coordinator in one of the largest agriculture companies in Brazil, and is co-founder and the head of research and development of technological solutions for agribusiness at Smart Agri. Trevisan has participated in events as speaker and organizer and is a founding member of the Brazilian Association of Precision Agriculture. He is experienced in agricultural planning, precision agriculture, on-farm experimentation, remote sensing, geographic information systems, data analysis, and artificial intelligence.