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Iowa Soybean Research Center

in collaboration with the Iowa Soybean Association

In-Field Soybean Seed Pod Analysis on Harvest Stocks Using 3D Imaging and Machine Learning

By Lie Tang, professor of agricultural and biosystems engineering, ISU

Progress Report

Soybean seed pods directly contribute to the yield and their morphologic characteristics represent important traits for soybean breeding. Traits such as number of total pods, number of seeds in each pod and the corresponding pod grouping, and the distribution of pods over the plant are all of great interest to soybean breeders and plant scientists, but have been difficult to collect in an automated and high-throughput fashion, particularly under field conditions. With the advancement of 3D sensing technologies and the deep convolutional neural networks, the Agricultural Robotics and Automation Lab at Iowa State University has made some breakthroughs in field-based plant phenotyping for plants like maize and sorghum. In this project, the PI’s research team will investigate how these technologies and innovations can be extended into field-based soybean plant phenotyping.

Selected for funding October 2020