Application of Machine Learning Algorithms in Plant Breeding: Predicting Yield From Hyperspectral Reflectance in Soybean

Application of Machine Learning Algorithms in Plant Breeding: Predicting Yield From Hyperspectral Reflectance in Soybean

Recent substantial advances in high-throughput field phenotyping have provided plant breeders with affordable and efficient tools for evaluating a large number of genotypes for important agronomic traits at early growth stages. Nevertheless, the implementation of large datasets generated by high-thr...

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Bibliographic Details
Main Authors: Mohsen Yoosefzadeh-Najafabadi, Hugh J. Earl, Dan Tulpan, John Sulik, Milad Eskandari
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-01-01
Series:Frontiers in Plant Science
Subjects:
artificial intelligence
data-driven model
ensemble methods
high-throughput phenotyping
random forest
recursive feature elimination
Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2020.624273/full

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https://www.frontiersin.org/articles/10.3389/fpls.2020.624273/full

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