Date of Graduation

5-2015

Document Type

Thesis

Degree Name

Master of Science in Crop, Soil & Environmental Sciences (MS)

Degree Level

Graduate

Department

Crop, Soil & Environmental Sciences

Advisor/Mentor

Richard E. Mason

Committee Member

Larry Purcell

Second Committee Member

Edward Gbur

Third Committee Member

Kristofor Brye

Keywords

Normalized difference vegetative index, Quantitative trait loci mapping, Spectral reflectance, Wheat, Yield

Abstract

Wheat is the most widely cultivated cereal crop, being grown on 17% of the global crop land and as such must be adapted to an array of environmental stresses. In order to become a variety, wheat breeding lines must be tested across a range of environments for both high productivity and stability. Quantitative trait loci (QTL) mapping and indices are tools that can aid plant breeders in the selection of superior lines. Soft red winter wheat accounts for 20% of the total wheat production in the United States, being grown in the southeastern U.S. predominantly along the Mississippi River. However, there are currently no reports of QTL associated with grain yield and test weight in U.S. soft red winter wheat. The objective of this study was to identify QTL associated with grain yield, test weight and related traits to aid breeders in the southeastern U.S to better understand the genetic control of adaption to this region that can lead to higher production and producer return. This study was also aimed to assess the ability of normalized difference vegetative index (NDVI) to monitor changes in crop development over the growing season as well as to identify QTL influencing these changes. A recombinant inbreed line (RIL) population derived from a cross between two elite cultivars, `Pioneer 26R61' and `AGS 2000', was grown in six different testing sites from 2011-2014 for a total of twelve site-years. A randomized complete block design was used with two replications per location. Mean grain yield for the RILs ranged from 339 g m-2 to 716 g m-2 and test weight from 69 kg hl-1 to 80 kg hl-1. A total of 42 QTLs were detected for yield, test weight, heading date and height. Eleven yield QTL were identified, explaining from 1.8 to 8.5% of the phenotypic variation and contributed by both of the parental lines. Yield QTL explaining the most variance were located on chromosome 5B and were also associated with the favorable allele from AGS2000 for early heading. Eight QTL were identified for test weight, with the largest effect locus on 5D explaining 7.1% of the phenotypic variance. For the NDVI study, NDVI measurements were repeated on multiple days throughout the growing season with at least one measurement taken during vegetative and grain-filling stages at seven Arkansas site-years. Based on the accumulated growing degree days, NDVI measurements were grouped into seven development stages. In addition, vegetative biomass samples were harvested during early plant development and biomass at maturity was estimated from 50 tillers harvested at ground level prior to whole plot harvest. Genetic variation and heritability of NDVI increased throughout the growing season as did correlations between NDVI and biomass or yield. Significant correlations ranged from r = -0.32 to 0.37 for NDVI development stages with yield, biomass at maturity and vegetative biomass. For individual environments, particularly those that had low production, correlations were found to be as high as r = 0.72 for late season measurements of NDVI and yield. QTL for NDVI were found to be highly pleiotropic and were clustered in 14 genome regions across 11 of the 21 wheat chromosomes. Six of the 14 regions co-localized for both NDVI and biomass, with individual QTL explaining up to 14.7% of the phenotypic variation for NDVI. Results presented here can aid breeders in future development of high yielding cultivars through marker assisted breeding and in targeting growth and development to meet the demands of a diverse range of growing environments.

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