Selection of Dry Bean Genotypes Adapted for Drought Tolerance in the Northern Great Plains
Autor: | Linares, Angela M. |
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Rok vydání: | 2013 |
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Druh dokumentu: | text/dissertation |
Popis: | Drought stress is a production constraint that growers face in the Northern Great Plains. This research was conducted to (1) assess the differences in seed yield due to drought within each one of the three most important dry bean market classes grown in the region (pinto, navy, and black), (2) estimate the genetic gain and progress over time due to the use of improved dry bean cultivars from 1981 to 2011, (3) evaluate the `Buster'/SER 22 recombinant inbred line population under drought conditions and identify loci associated with drought tolerance that could be used in Marker Assisted Selection (MAS) in the future. Results showed that, on average, drought stress can reduce seed yield by 35% in North Dakota. Seed yield in black cultivars can be reduced as much as 36% in dryland when compared to irrigated conditions, followed by navy and pinto with 35 and 32% of seed yield reduction, respectively. Data over 26 years showed yield gains of 15, 14, and 11kg ha-1 yr-1 for pinto, black, and navy beans under dryland conditions, respectively, while yield reductions were observed under irrigated conditions. Results will help to design strategic plans toward the genetic improvement of dry beans for the region. On the other hand, quantitative trait loci (QTL) were detected for seed yield, 100-seed weight, days to maturity, days to flower, and leaf temperature. The genetic map had a length of 778.4 cM and was based on 378 single nucleotide polymorphism (SNP) markers. Transgressive segregation was also observed for all phenotypes under study. Some of the QTL identified could be useful for selection purposes under optimal, irrigated, and drought conditions. USDA-CSREES-HSI Fellowship (Award No. 2006-38422-17106) Northarvest Bean Growers Association North Dakota State University (NDSU) Dry Bean Breeding Program Royalties |
Databáze: | Networked Digital Library of Theses & Dissertations |
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