Welcome to Chinese Agricultural Science Bulletin,

Chinese Agricultural Science Bulletin ›› 2021, Vol. 37 ›› Issue (32): 15-19.doi: 10.11924/j.issn.1000-6850.casb2021-0397

Special Issue: 玉米

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The Regression Model and Correlation Analysis Between Maize Yield and Planting Density

Zhang Zheng1,2(), Dong Chunlin1,3(), Yang Rui1,2, Chang Jianzhong1,2, Zhang Yanqin1,2   

  1. 1Shanxi Institute of Organic Dry Land Farming, Shanxi Agricultural University, Taiyuan 030031
    2National Local Joint Engineering Laboratory of Water-saving Techniques for Dry Farming in the Eastern Loess Plateau, Taiyuan 030031
    3Organic Dry Farming of Shanxi Province Key Laboratory, Taiyuan 030031
  • Received:2021-04-14 Revised:2021-07-28 Online:2021-11-15 Published:2022-01-07
  • Contact: Dong Chunlin E-mail:25332305@qq.com;cl_dong@126.com

Abstract:

To explore the relationship between maize planting density and yield, and the relationship between actual yield and standard yield among different planting densities, ‘Bingdan 16’ was used as the material, six planting densities were set, which were 52500、56250、60000、63750、67500、71250 plant/hm2, and the SPSS was applied to analyze the linear regression of the standard yield and main agronomic traits like spike length, spike diameter, bald tip length, rows per spike, grains per row, 100-grain weight, seed rate, planting density and actual yield, and then the regression analysis model was constructed. The regression model of actual yield, planting density and standard yield was y=403.997-0.15×planting density+0.558×actual yield. The regression model between standard yield and traits was y=-123.292-0.037×density-34.237× ear diameter-55.099×ear length+31.950 row number+23.801 row number+7.023×bald tip length+10.649×grain water content-3.006×100 grain weight+9.193 seed yield-0.204×actual yield; the regression model constructed by actual yield, planting density and standard yield was more significant.

Key words: standard yield, regression model, planting density, agronomic traits, correlation

CLC Number: