Evaluation of the Impact of Near-Infrared Spectroscopy on Genomic Prediction Accuracy for Hybrid Rice Traits

Near-infrared spectroscopy (NIRS) has emerged as a powerful, non-destructive tool for rapid evaluation of rice crop traits, including grain quality, variety identification, and genetic screening. While numerous studies have validated its effectiveness in predicting characteristics such as glycemic index, amylose content, and protein levels in rice varieties, little research has explored its application in hybrid rice. This study addresses that gap by applying NIRS to predict phenotypic traits in 1,488 seed samples from 191 hybrid rice lines across four locations in the Mid-South and Gulf Coast regions of the United States. Using the Antaris™ II FT-NIR Analyzer, both whole and milled rice grain samples were analyzed. Phenotypic data from NIRS were integrated with genomic marker data to build predictive models, which were evaluated using 5-fold cross-validation. Surprisingly, the results indicated that NIRS data alone did not outperform either marker-only or combined data models for most measured traits. The marker-only model demonstrated a 55% higher prediction accuracy than that of the NIRS model, on average. The moderate accuracy from the combined model suggests that data integration may introduce noise despite the added predictive information. These findings demonstrate the potential of NIRS as a high-throughput, cost-effective phenotyping technology that can guarantee capturing prediction accuracy information and improve efficiency in hybrid rice breeding programs.

Name thesis:degree_name

Master of Science

Discipline thesis:degree_discipline

Plant Breeding

Grantor

Texas A&M University

Year dc:date.issued

2025

Author dc:creator

• Benitez, Marvin 1994-

Advisor dc:contributor.advisor

• Septiningsih, Endang

Committee members dc:contributor.committeemember

• Zhou, Xin-Gen (Shane)
• Wang, Jianlin

• Agriculture, Agronomy
• Biology, Genetics

Language dc:language.iso

English

Handle dc:identifier.uri

https://hdl.handle.net/1969.1/1599756

OAI record oai:identifier

https://oaktrust.library.tamu.edu/server/oai/request?verb=GetRecord&metadataPrefix=dim&identifier=oai%3Aoaktrust.library.tamu.edu%3A1969.1%2F1599756