Integrating Genomic and Phenomic Breeding Selection Tools with Field Practices to Improve Seed Composition Quality Traits in Soybean
| dc.contributor.author | Singer, William Monte | en |
| dc.contributor.committeechair | Zhang, Bo | en |
| dc.contributor.committeemember | Holshouser, David L. | en |
| dc.contributor.committeemember | Raubenstine, Scott | en |
| dc.contributor.committeemember | Mian, Rouf | en |
| dc.contributor.committeemember | Huang, Haibo | en |
| dc.contributor.department | Crop and Soil Environmental Sciences | en |
| dc.date.accessioned | 2021-12-01T09:00:28Z | en |
| dc.date.available | 2021-12-01T09:00:28Z | en |
| dc.date.issued | 2021-11-30 | en |
| dc.description.abstract | Despite soybean's widespread recognition as a versatile and valuable crop due to many end-use purposes, breeders seek to develop varieties with improved nutritional and functional components that capture added-value for producers. Additionally, producers seek to maximize profits by utilizing field practices to augment crop value. Therefore, this dissertation had two main objectives of maximizing soybean value: 1) to evaluate accelerated selection methods by soybean breeders for methionine content and test weight, and 2) to identify sulfur fertilization impact on soybean seed composition including amino and fatty acid profiles. First, a genome-wide association study (GWAS) analyzed genomic influence on proteinogenic methionine in soybean seeds which identified 23 single nucleotide polymorphisms (SNPs). Utilizing a SNPs subset identified by GWAS, genomic selection (GS) exhibited average prediction accuracies ranging from 0.41-0.62. Secondly, a novel phenomic selection (PS) method using near-infrared reflectance spectroscopy (NIRS) was evaluated for predictive ability of soybean test weight. PS cross-validations exhibited average predictive accuracies of 0.75, 0.59, and 0.16 when incorporating all environments, between locations, and between years, respectively. Finally, sulfur fertilizer rates and sources were assessed across two years and six locations in relation to seed composition. Notably, ammonium sulfate (AMS) was found to have a significant impact (P < 0.05) on methionine content in soybean seed. These outcomes will have positive impacts on plant breeding and soybean production for seed composition and quality traits using contemporary breeding and fertilization. | en |
| dc.description.abstractgeneral | Despite soybean's widespread recognition as a versatile and valuable crop due to a myriad of end-use purposes, breeders seek to develop varieties with improved nutritional and functional components that captured value for producers. Additionally, producers seek to maximize their profits by utilizing field practices that increase crop value. Therefore, this dissertation had two main objectives of maximizing soybean value: 1) to evaluate accelerated selection methods by soybean breeders for methionine content and test weight, and 2) to identify sulfur fertilization impact on soybean seed protein and oil composition. The overall objective was to create a comprehensive toolset for soybean breeders to develop Mid-Atlantic soybean varieties with improved seed composition traits and to determine fertilization impacts for use by producers. Genetic controls for protein-bound methionine in soybean seed were identified and could be used for variety development. Additionally, a new prediction method that uses light reflectance to represent genetic information and environmental effects was shown to have high accuracy for soybean test weight. It was also found that sulfur fertilizer with high availability in the soil positively impacted methionine content. These outcomes will have positive impacts on plant breeding and soybean production for seed composition and quality traits using contemporary breeding and fertilization. | en |
| dc.description.degree | Doctor of Philosophy | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:33117 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/106789 | en |
| dc.language.iso | en | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | soybean | en |
| dc.subject | methionine | en |
| dc.subject | amino acids | en |
| dc.subject | fatty acids | en |
| dc.subject | genome-wide association | en |
| dc.subject | genomic selection | en |
| dc.subject | phenomic selection | en |
| dc.title | Integrating Genomic and Phenomic Breeding Selection Tools with Field Practices to Improve Seed Composition Quality Traits in Soybean | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Crop and Soil Environmental Sciences | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Doctor of Philosophy | en |
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