This thesis explores the genetic architecture of malting quality within the Virginia Tech barley breeding program, and discusses implications for imposing selection on complex traits that are difficult to phenotype. Malting quality measures are destructive, and can not be performed before selection must be made for advancement of breeding lines in winter barley. A growing body of evidence suggests that malt quality is influenced by malting regime, growing environment, line genotype, and the interactions between them. We aim to better understand the genetic effect on malt quality in two manners: first, as it relates to the genetic architecture regulating malt quality parameters, and second the relationship between genetic growth patterns to end-use malting traits. This study included two years of breeding trial data of two and six-row winter malt barley across two locations. Results of a genome-wide association scan and genomic prediction of malt quality traits indicated that they are largely quantitative traits with complex inheritance. Previous studies have identified quantitative trait loci and genes regulating malt quality traits in markedly different germplasm. Heritability of traits ranged from 0.27 to 0.72, while mean predictive abilities ranged from 0.45 to 0.74. Thus, selection on genomic estimated breeding values (gEBVs) should perform similarly to selection on single phenotypic observations of quality, but can be done within the same season. This indicates that genomic selection may be a viable method to accelerate genetic improvement of malting quality traits. The use of gEBVs requires that lines be genotyped with genome-wide markers, somewhat limiting the number of candidate individuals. Selection on growth and development traits genetically correlated with quality measures could allow for selection among a much greater number of candidates if high-throughput phenotypes can be collected on many ungenotyped indivduals. Growth and development was quantified by the near-infrared vegetation index (NDVI) extracted from aerial images captured from multiple time points throughout the growing season. Estimates of genetic correlation identified time points throughout the season when quality traits are related to growth and development. We demonstrated that aerial imagery can discern growth patterns in barley and suggest ways it can be incorporated into the breeding pipeline. / Master of Science / Malt barley (Hordeum vulgare) is the preferred source of fermentable sugar used to brew beer. Currently, the majority of malt barley used in the United States is grown in the upper mid-west or imported from Europe. The east coast could become a producing region if high quality, disease resistant varieties were available to growers. The Virginia Tech small grains breeding program began breeding locally adapted malt barley in 2010. This project aims to improve the breeding process by incorporating information from genomic sequencing, malt quality and aerial imagery. Malt barley differs from that used for animal feed or human food because specific quantities of starches, proteins, and enzymes are necessary in the brewing process. The quantity of these molecules are determined through lab analysis and determine the grain's suitability for particular brewing styles. This analysis is timeconsuming and costly because it involves a three-step process of malting the grain, brewing with the malt, and analyzing the wort. The wort is the liquid sugar solution which is produced by heating the malt with water to a high temperature in a process called 'mashing'.
Lab quality analysis for the thousands of lines evaluated in a breeding program in any given year is unfeasible. However, by understanding the genetic regulation of malt quality traits, breeders can employ techniques like genomic selection to improve these traits in a shorter amount of time. Additionally, this work identifies relationships between growth and quality.
The grain is the result of the plant's growth throughout the entirety of the season. Measuring growth repeatedly through time was previously difficult until the advent of aerial imagery.
Images captured from drones have been used to quantify growth in a variety of plants, but is not extensively done in malt barley. Relating growth to quality will help breeders understand genetic patterns of growth and development which may be advantageous in the production of high quality malt barley.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/115512 |
| Date | 26 June 2023 |
| Creators | Loeb, Amelia |
| Contributors | Crop and Soil Environmental Sciences, Santantonio, Nicholas, O'Keefe, Sean F., Shafian, Sanaz |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International, http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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