Improving Wheat Yield Prediction Using Secondary Traits and High-Density Phenotyping Under Heat-Stressed Environments

Area of Science:

• Agricultural Science
• Plant Breeding
• Remote Sensing

Background:

• Grain yield is a key target for wheat (Triticum aestivum) improvement, but traditional selection methods are limited by time and environmental variability.
• Secondary traits, such as spectral reflectance and canopy temperature (CT), offer rapid, repeatable measurements throughout the growing season.
• High-throughput proximal sensing platforms provide valuable data, but their effective utilization in breeding programs remains a challenge.

Purpose of the Study:

• To monitor wheat growth and predict grain yield in breeding trials under terminal heat stress using high-density proximal sensing data.
• To evaluate the effectiveness of combining secondary traits for more accurate grain yield prediction.
• To optimize phenotypic prediction models for robust and rapid selection in wheat breeding.

Main Methods:

• Analysis of normalized difference vegetation index (NDVI) and CT measurements over five growing seasons in elite wheat breeding lines.
• Application of variable reduction and regularization techniques to combined secondary traits for yield prediction.
• Utilizing univariate and multivariate models, including stepwise regression, with cross-fold validation to assess prediction accuracy.

Main Results:

• Multivariate models demonstrated higher prediction accuracies for grain yield compared to univariate models.
• Stepwise regression models performed comparably to or better than other models in yield prediction.
• Incorporating all secondary traits into models achieved high prediction accuracies (0.58-0.68) across five seasons.

Conclusions:

• Optimized phenotypic prediction models effectively leverage secondary traits for accurate wheat grain yield prediction.
• The study demonstrates the potential for rapid and robust selection in wheat breeding programs using proximal sensing data.
• This approach is particularly valuable for breeding under challenging conditions like terminal heat stress common in regions such as Bangladesh.