The American Society of Agronomy, the Crop Science Society of America, and the Soil Science Society of America hosted the 2019 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.
View the presentation materials below:
- Understanding the Spatial Variability of Optimum Nitrogen Rates Using Remote Sensing and on-Farm Precision Experimentation
- Using Deep Learning To Predict Optimum Crop Management Decisions – Trevisan (Abstract)
- Using Deep Learning to Predict Optimum Crop Management Decisions (Poster)
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In August 2018, graduate student Brendan Kuhns traveled to Columbia to assess the technical viability of conducting data-intensive farm management trials with rural farmers in corn, rice, soybeans, and most importantly, cotton. While there, Kuhns attended field days for small farmers, and met with large-scale producers, university officials, researchers, equipment dealers, and technical school instructors.
Following this trip, Kuhns concluded that the majority of Colombian farmers currently lack the ability to run DIFM trials. However, demonstration trials will begin at Servicio Nacional de Aprendizaje (SENA), a technical school in Colombia, with hopes of passing the practice on to farmers as equipment is upgraded.
Members of the Data-Intensive Farm Management project has since submitted a grant to CGIAR to develop low-cost sensing technology for these farmers, that would allow them to participate in our trials. The detailed results of the trip is available to DIFM researchers upon request.