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Quantitative trait loci analysis for net ginning energy requirements in upland cotton (<Emphasis Type="Italic">Gossypium hirsutum</Emphasis> L.)
Authors:Efrem Bechere  David D Fang  Hirut Kebede  IV" target="_blank">Robert G HardinIV  Md S Islam  Ping Li  Jodi Scheffler
Institution:1.USDA-ARS Crop Genetics Research Unit,Stoneville,USA;2.USDA-ARS Cotton Fiber Bioscience Unit,New Orleans,USA;3. Crop Genetics Research Unit,Stoneville,USA;4.USDA-ARS Cotton Ginning Research Unit,Stoneville,USA
Abstract:Cotton cultivars with reduced fiber-seed attachment force have the potential to be ginned faster with less energy. The objective of this study was to identify quantitative trait loci (QTL) for net ginning energy requirement (NGE), and its relationship with other fiber quality traits in upland cotton. Two cotton lines, TAM 182-34 ELS and AR 9317-26, with significant differences in NGE and fiber-seed attachment force, were crossed and 285 F2 plants derived from a single F1 plant were planted in the field and leaf samples collected for DNA marker analysis (Population A). Individual F3 plants and the two parents were planted in replicated progeny rows. The cotton was ginned on a 10-saw laboratory gin stand. Electrical power used by the gin was measured and recorded with a Yokogawa CW121 power meter. Fiber quality attributes were measured using a high volume instrument. A total of 455 SSR marker loci were used to construct a linkage map. Two QTLs were identified for NGE on chromosomes 12 and 20, associated with markers CIR148 and DPL0600, explaining 14 and 8.8% of the phenotypic variation, respectively. NGE shared the same genomic region with fuzz percent on chromosome 12. Population B, consisting of 260 F2 progeny from the reciprocal cross AR 9317-26 X TAM 182-34 ELS, was used to confirm these QTLs by analyzing SSR markers mapped on Chrs 12 and 20. These QTLs (qNGE-c12 and qNGE-c20) were confirmed and appeared stable. Further validation of significantly associated markers on different populations is necessary prior to implementation in marker-assisted selection.
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