Improving soybean production, seed quality and soil health using digital agriculture technologies
Sustainable Production
Global ImagerySoil health
Parent Project:
This is the first year of this project.
Lead Principal Investigator:
Jianfeng Zhou, University of Missouri
Co-Principal Investigators:
Project Code:
Contributing Organization (Checkoff):
Institution Funded:
Brief Project Summary:
With current USB support, we have implemented a wireless soil sensor network and taken soil health measurements at four fields of different treatments. By 2022, we will develop soil health prediction models and high-resolution soil health maps using the data collected. With data in 2023, we will improve and optimize the proposed soil health mapping tool and provide evidence on correlation between soil health, farming practice and soybean seed quality (protein, amino acids, etc.). We expect to develop recommendations for farming practices and soil management that will benefit soil health and improve soybean seed quality, profitability, sustainability and resilience.
Information And Results
Project Summary

Project Objectives

Project Deliverables

Progress Of Work

Final Project Results

This project aims to discover the knowledge and practices to improve soil health, soybean seed quality and production using digital agriculture technologies. We proposed and tested a method to quickly quantify soil health using drone imagery and soil sensor data that are analyzed using machine learning. The project is expected to result in a tool to acquire high-resolution soil health map in a scaled field. We hope to identify improved management practices to improve soil health, soybean seed nutrition quality and sustainability. The proposed key deliverables include: (1) a fast soil health mapping tool using drone imaging and machine learning technology, (2) a validated correlation between soil health and management practices of soil and crop, and (3) Knowledge about the correlation of soil health and soybean seed quality. The milestones of the project include: (1) Development of an optimized data acquisition system to collect field data of soil, crop and climate; (2) establishment of a training data set for modeling in years of 2022 and 2023 soybean seasons; (3) development of a data analysis and modeling pipeline; and (4) Reach out stakeholders through field days and presentations.

Benefit To Soybean Farmers

1. Aim to grow body of evidence of the usefulness of digital agriculture technology on US soybean production through on-farm research. 2. Identify new farming practices through data-driven approach using digital tools, such as drones, and sensors. 3. Improve international competition of US soybean farmers.

The United Soybean Research Retention policy will display final reports with the project once completed but working files will be purged after three years. And financial information after seven years. All pertinent information is in the final report or if you want more information, please contact the project lead at your state soybean organization or principal investigator listed on the project.