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Chinese Agricultural Science Bulletin ›› 2023, Vol. 39 ›› Issue (33): 25-32.doi: 10.11924/j.issn.1000-6850.casb2022-0821

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Shading-Tolerant Spring Soybean: Genotypes Screening and Identification of Shade Tolerance Indexes

ZHAO Zhixin1,2,3(), FU Mengmeng1,2,3, LI Shuguang1,2,3, WANG Yaqi1,2,3, YU Xiwen1,2,3, ZHANG Hongmei4, CHEN Huatao4, XU Haifeng1,2,3()   

  1. 1 Huaiyin Institute of Agricultural Sciences of Xuhuai Region in Jiangsu, Huai’an, Jiangsu 223001
    2 Key Laboratory of Germplasm Innovation in Lower Reaches of the Huaihe River, Huai’an, Jiangsu 223001
    3 Huaian Key Laboratory of Agricultural Biotechnology, Huai’an, Jiangsu 223001
    4 Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Nanjing 210014
  • Received:2022-09-26 Revised:2023-01-15 Online:2023-11-25 Published:2023-11-22

Abstract:

In order to study the effect of shading stress on spring soybean in the Huanghuaihai region, and to screen the identification indexes and mathematical evaluation model of spring soybean shade tolerance, the shade tolerance coefficients of 10 indicators of soybean were used to measure the shade tolerance of individual indicators, and the comprehensive shade tolerance evaluation value of 25 soybean genotypes was calculated by principal component analysis, membership function method and stepwise regression method. The results showed that different soybean genotypes responded differently to shading stress. The plant height, the node of main stem and average internode length increased to different degrees under shade conditions, and the degree of variation increased, while the pods per plant, grains per plant, grain-stem ratio, grain weight per plant and grain per pod decreased significantly. Based on the cluster analysis of shade tolerance evaluation value (D), the 25 test soybean genotypes were divided into five categories: strong shade-tolerant, more shade-tolerant, moderate shade-tolerant, shade-intolerant and extremely shade tolerant. A mathematical model for the evaluation of shade tolerance of spring soybeans in the Huanghuaihai region was established: D=-0.149 + 0.202X01-0.054X04+ 0.233X05 + 0.233X07 (R2=0.963), and the prediction accuracy reached 82%. In summary, four indexes, including the plant height, the height of lower pods, the average internode length and grains per plant, were screened as the identification indexes of Huanghuaihai shade-tolerant spring soybean, and six strong shade-tolerant soybean materials were identified.

Key words: soybean, shading stress, shade tolerance evaluation, principal components analysis, membership function method, comprehensive evaluation