What is it about?
Improving soybean seed yield through the measurement and analysis of key yield components. Using machine learning algorithms to predict yield and also developed a model for an ideal genotype with maximized yield potential. It provides insights that could be used to develop cultivars with improved genetic yield potential in soybean.
Featured Image
Photo by Jelleke Vanooteghem on Unsplash
Why is it important?
Soybean is a major food crop that provides a significant amount of protein and oil for human and animal consumption worldwide. As the global population continues to grow, there is a need to increase crop yields to meet the rising demand for food. The study provides a new approach to predicting soybean yield and developing soybeans with maximized yield potential.
Perspectives
The study aims to provide a better understanding of the relationships between soybean yield and its components and to offer a new avenue for increasing soybean yield through targeted breeding efforts.
Milad Eskandari
University of Guelph
Read the Original
This page is a summary of: Application of machine learning and genetic optimization algorithms for modeling and optimizing soybean yield using its component traits, PLoS ONE, April 2021, PLOS,
DOI: 10.1371/journal.pone.0250665.
You can read the full text:
Contributors
The following have contributed to this page
