Jonathan Concepcion: Final Dissertation Defense

March 26, 2025 11:00AM - 12:00PM 11:00-12:00

Food Toxicology Building room 162

INTEGRATING PHENOMICS AND GENOMICS TOWARDS

ACCELERATING GENETIC GAIN IN SOFT WINTER WHEAT

 

Members of the Examining Committee and their Department:

  1. Dr. Eric Olson - Plant, Soil and Microbial Sciences
  1. Dr. Addie Thompson – Plant, Soil and Microbial Sciences
  1. Dr. David Douches – Plant, Soil and Microbial Sciences
  2. Dr. Gustavo de los Campos – Epidemiology and Biostatistics

 

ABSTRACT

 

Accelerating genetic gain in plant breeding demands increased selection intensity, enhanced selection accuracy, broader genetic diversity, and a shortened breeding cycle. As phenomic platforms and genomic resources continue to evolve, integrating phenomics and genomics offers an unprecedented opportunity to improve breeding pipelines. This dissertation explores multiple approaches to incorporating phenomic information into wheat breeding alongside genomic data, aiming to increase prediction accuracy and selection intensity, and identify genomic regions for economically important traits in soft winter wheat. Infrared thermal imaging enabled high-resolution differentiation of Fusarium head blight-resistant and susceptible genotypes at the single-spike level. However, field-scale implementation requires careful consideration due to uncontrolled factors under field conditions. Hyperspectral imaging demonstrated superior predictive ability over genomic prediction alone for deoxynivalenol (DON) content prediction. Integrating phenomic and genomic prediction further enhanced prediction accuracy, allowing for genotype clustering-based selection on predicted DON content. Additionally, multiple strategies for leveraging UAV-derived vegetation indices (VIs) were evaluated to improve genomic prediction accuracy, with varying degrees of success depending on the type of UAV-derived information used as fixed effect or secondary trait, as well as training set composition. Beyond enhancing prediction, phenomic data facilitated the identification of key genomic regions associated with DON content and grain yield, underscoring its potential as a phenotypic input in genome-wide association studies. Collectively, these findings support the potential application phenomics-genomics integration in improving wheat breeding. However, careful consideration is essential when implementing combined phenomic-genomic approaches to ensure robust, field-applicable results. Results from this work show potential advancements in predictive breeding, aiming to improve genetic gain in soft winter wheat.

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