Enhancing Genomic Prediction Models for Forecasting Days to Maturity in Soybean Genotypes Using Site-Specific and Cumulative Photoperiod Data

Enhancing Genomic Prediction Models for Forecasting Days to Maturity in Soybean Genotypes Using Site-Specific and Cumulative Photoperiod Data

Genomic selection (GS) has revolutionized breeding strategies by predicting the rank performance of post-harvest traits via implementing genomic prediction (GP) models. However, predicting pre-harvest traits in unobserved environments might produce serious biases. In soybean, days to maturity (DTM)...

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Bibliographic Details
Main Authors:	Reyna Persa, George L. Graef, James E. Specht, Esteban Rios, Charlie D. Messina, Diego Jarquin
Format:	Article
Language:	English
Published:	MDPI AG 2022-04-01
Series:	Agriculture
Subjects:	genomic selection days to maturity genomic prediction predictive ability daylength
Online Access:	https://www.mdpi.com/2077-0472/12/4/545

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