Leveraging Multi-Omics Data with Machine Learning to Predict Grain Yield in Small vs. Big Plot Wheat Trials

Leveraging Multi-Omics Data with Machine Learning to Predict Grain Yield in Small vs. Big Plot Wheat Trials

Accurate grain yield (GY) prediction is essential in wheat breeding to enhance selection and accelerate breeding cycles. This study explored whether high-throughput phenotyping (HTP) data collected from small plot (SP) trials can effectively predict GY outcomes in later-stage big plot (BP) trials. G...

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Bibliographic Details
Main Authors: Jordan McBreen, Md Ali Babar, Diego Jarquin, Yiannis Ampatzidis, Naeem Khan, Sudip Kunwar, Janam Prabhat Acharya, Samuel Adewale, Gina Brown-Guedira
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Agronomy
Subjects:
grain yield
wheat breeding
genomic prediction
high-throughput phenotyping
hyperspectral imaging
UAV phenotyping
Online Access:https://www.mdpi.com/2073-4395/15/6/1315
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