Project Overview
Information Products
Commodities
- Agronomic: canola, corn, cotton, wheat
Practices
- Crop Production: fertilizers, seed saving
Abstract:
Digital agriculture integrates technology, big data, analytics, computer science, machinery, automation, and decision-support systems. Innovation with these tools is at the forefront of optimizing inputs and financial resources while reducing environmental impacts in agricultural production. However, adoption of digital agriculture by farms in the western states are far behind. One major reason is lack of variable rate recommendations provided by land grant universities. To develop such recommendations, large amount of field-scale on-farm data collected from many years is required. On-farm precision experimentation (OFPE) is a cost-effective method to generate such required data. The OFPE is also an effective extension tool since farmers and consultants are heavily involved in all aspect of research. However, the OFPE is not widely used in the land grant universities in the western states. The objective of this project is to increase adoption of OFPE, which in turn leads to development of digital agriculture-enabled variable rate recommendations using on-farm data. The ultimate objective is to increase adoption of digital agriculture. We are proposing a training project (a 2-day in-person workshop and a 3-hour online work session) that leverages three multimillion dollar projects: multistate Data-Intensive Farm Management (DIFM) led by University of Illinois, On-Farm Precision Experiment Framework (MT-OFPE) led by Montana State University, and multistate project recently funded by NRCS-CIG-On-farm Trials (CIG-OFPE). Scientists and consultants involved in these three projects have been conducting hundreds of OFPEs and developed various automated tools, which will be taught in this proposed training workshop. We anticipate the outputs of this project is to increase involvement of land grant universities to boost OFPE trials on the western states farms, which leads to development of decision-support systems for digital agriculture-enabled variable rate recommendations. Farmers and consultants will be empowered to answer their own nutrient management questions using data from their own farms.
Project objectives:
Objective 1: Increase knowledge of digital agricultural technology and how to use it to collect on-farm data.
Objective 2: Increase capacity to conduct OFPE trials using digital agriculture technology, awareness of new tools and software available for OFPE design, methods for data cleaning and analysis, and reporting.
Objective 3: Empower land grant universities in western states to develop digital agricultural-enabled variable rate recommendations.