Date of Award:
5-2025
Document Type:
Thesis
Degree Name:
Master of Science (MS)
Department:
Plants, Soils, and Climate
Committee Chair(s)
Paul Johnson
Committee
Paul Johnson
Committee
Margaret Krause
Committee
Alex Hernandez
Committee
Earl Creech
Abstract
In small grains breeding programs, breeders aim to develop better varieties by selecting for important traits like grain yield. However, it takes many years before yield can be measured because several generations of selection are required to fix lines and increase sufficient seed for yield measurements. This process can be slow and expensive
High-throughput phenotyping (HTP) is a modern approach that can increase breeding efficiency by leveraging technology to quickly measure secondary traits which can be used to indirectly select for important traits in crop plants. For example, researchers can use cameras on unmanned aerial vehicles (UAVs, i.e., drones) to capture images that can be utilized to characterize plant health on the basis of pixel color and light reflection. Previous studies have shown that these measurements (i.e., vegetation indices) can help predict crop yield.
This study tested whether using UAV imagery and chlorophyll measurements can be used to predict crop yield at earlier stages (i.e., headrows) in the breeding process. Yield and HTP data were collected from three crop trials – dryland wheat, irrigated wheat, and irrigated barley – and statistical models were used to calculate metrics (e.g., heritability and trait correlations) to determine whether these secondary traits may be useful in the indirect selection for grain yield.
High heritabilities suggested that the HTP traits are under genetic control and may be useful as selection criteria at the early stages of breeding programs. There were also high correlations between the HTP traits measured at headrow stage and grain yield measured in replicated yield trials. This suggests that indirect selection using these HTP traits at the headrow stage may lead to improvements in grain yield. In summary, using UAVs, imaging, and other technologies to measure crop traits at early breeding stages may improve selection accuracy for grain yield, helping breeders to develop higher-yielding varieties more efficiently.
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Recommended Citation
Jones, Dalton, "High-Throughput Phenotyping of Early Generation Small Grains Breeding Lines to Indirectly Select for Grain Yield" (2025). All Graduate Theses and Dissertations, Fall 2023 to Present. 393.
https://digitalcommons.usu.edu/etd2023/393
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