Asheesh Singh:
Soybean yield improvement strategies with digital technologies (Invited Talk)

Dr. Asheesh K Singh (Danny) is a Professor of Agronomy and Soybean Breeder at the Iowa State University. Upon completion of PhD from the University of Guelph in 2007, he worked as a durum wheat breeder in Agriculture and Agri-Food Canada. In 2013, he joined ISU as an assistant professor. In his career, he has helped develop >75 varieties and germplasm lines with wide uptake by farmers in production fields. He has published more than 150 research articles on topics related to plant breeding, genetics, phenomics, and utilization of machine learning for plant breeding applications. He recently authored “Plant Breeding and Cultivar Development” textbook.

Machine learning is opening new doors to generate insights previously inconceivable, enhancing decision-making capabilities of plant breeders leading to an improved crop improvement pipeline. It is also helping automate tasks which were previously considered too difficult or inconceivable in plant breeding pipelines. To demonstrate the capability of machine learning based application in plant breeding and cultivar development, few examples from our cultivar development program will be included focused on integrated yield estimation, weather-genetics for yield predictions, water and heat stress tolerance, and root system architecture traits, which lead to a cyber-enabled crop breeding.