Machine Learning Approach for Prescriptive Plant Breeding

Volume: 9, Issue: 1
Published: Nov 20, 2019
Abstract
We explored the capability of fusing high dimensional phenotypic trait (phenomic) data with a machine learning (ML) approach to provide plant breeders the tools to do both in-season seed yield (SY) prediction and prescriptive cultivar development for targeted agro-management practices (e.g., row spacing and seeding density). We phenotyped 32 SoyNAM parent genotypes in two independent studies each with contrasting agro-management treatments (two...
Paper Details
Title
Machine Learning Approach for Prescriptive Plant Breeding
Published Date
Nov 20, 2019
Volume
9
Issue
1
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