Integration of physiological and remote sensing traits for improved genomic prediction of wheat yield

Genomic selection is an extension of marker-assisted selection by leveraging thousands of molecular markers distributed across the genome to capture the maximum possible proportion of the genetic variance underlying complex traits. In this study, genomic prediction models were developed by integrating phenological, physiological, and high-throughput phenotyping traits to predict grain yield in bread wheat (Triticum aestivum L.) under three environmental conditions: irrigation, drought stress, and terminal heat stress. Model performance was evaluated using both five-fold cross-validation and leave-one-environment-out (LOEO) schemes. Under five-fold cross-validation, the model incorporating vegetation indices derived from spectral datasets from the grain-filling phase achieved the highest accuracy. In LOEO validation, the model that included days to heading performed best under irrigation, whereas under drought stress, the model utilizing vegetation indices from the vegetative stage showe..., , # Data from: Integration of physiological and remote sensing traits for improved genomic prediction of wheat yield

Dataset DOI: [10.5061/dryad.rbnzs7hqq](10.5061/dryad.rbnzs7hqq)

## Description of the data and file structure

Dataset used in the publication \"Integration of physiological and remote sensing traits for improved genomic prediction of wheat yield\". 

The data was collected at the Campo Experimental Norman E. Borlaug (CENEB) Field station from the International Maize and Wheat Improvement Center (CIMMYT), Ciudad Obregon, Sonora, Mexico in the growth season 2022-2023. We collected agronomic, physiological and remote sensing traits to predict wheat yield using genomic prediction in three environments: irrigation, drought stress and terminal heat stress. Raw data and BLUEs for grain yield, grain filling percentage, grain filling rate, plant height, days to heading, stomatal conductance, transpiration, quantum yield of photosystem II and high-throughput traits in the MOLPAN whe...,