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摘要:Soybean(Glycine max) meal is used largely for livestock feed rations in developed countries,therefore soybean varieties with relatively high protein concentration are desirable to improve the crop value.However,over the last several decades there has been a reduction of protein concentration and improvement of oil content in soybeans varieties,mainly due to the selection of higher seed yield potential.The objectives of this research are to a) characterize and estimate the phenotypic correlations among seed composition traits in unique bi-parental populations,b)estimate seed yield and seed composition phenotypic correlations,and c) develop and validate genomic prediction models for efficient selection for all measured traits.We evaluated 794 RIL’s derived from seven unique G.max by 6.soja bi-parental populations during 2015 in Columbia,MO.Maturity,lodging,shattering and disease incidence were collected in the field and seed protein,oil and sucrose concentrations were estimated using a FOSS Rapid Content Analyzer near-infrared spectrometer.The genotyping analysis is being conducted using the 6K SNP Infinium chip.The range in protein concentration was from 31.3%to 45.7%,oil ranged from 10.5%to 20%and sucrose from 0.6%to 6.3%.Pearson’s correlation coefficient revealed that protein concentration is negatively associated with oil content(-0.65,P < 0.001) and sucrose(-0.57,P < 0.001).Also,we found a positive correlation between oil content and sucrose(0.27,P < 0.01).The highest mean values for protein were found in the populations Williams 82× PI 458536 and Williams 82 × Pl 464890 B,for oil populations Williams 82 ×Pl 522226 and Williams 82 x Pl 549046,and for sucrose populations Osage x Pl 479751,Osage x PI 593983,and Williams 82 x PI 522226.Currently,we are genotyping the bi-parental populations and conducting yield trials across four locations in Missouri during 2016,to develop and validate genomic prediction models to enhance genetic gain in wild x elite populations.
会议名称:

第七届国际作物科学大会

会议时间:

2016-08-14

会议地点:

中国北京

  • 专辑:

    农业科技

  • 专题:

    农作物

  • 分类号:

    S565.1

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