Multiple Regression Analysis and Path Analysis of the Main Agronomic Traits of Summer Maize
Feng Xiao-xi
Abstract
Feng Xiao-xi
Abstract
The relationship between main agronomic traits (plant height , ear position, growth period , ear length , ear diameter , row number of per ear , kernel number of per row , cod diameter, kernel weight per ear, grain production rate, 1000 kernels weight) and yield per plot of maize were studied with multiple regression and path analysis by using Statistica DPS3.01 software.. The results indicated that yield per plot was significantly correlated with plant height , ear position, ear length , ear diameter , row number of per ear , kernel number of per row , cod diameter, grain production rate,1000 kernels weight). The relative importance of the eight agronomic traits correlated with yield per plot of maize was in order of 1000 kernels weight row number of per ear plant height ear diameter cod diameter ear position kernel number of per row grain production rate. The yield per plot of maize had signifi- cant linear relationship with the eight agronomic traits.
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The relationship between main agronomic traits (plant height , ear position, growth period , ear length , ear diameter , row number of per ear , kernel number of per row , cod diameter, kernel weight per ear, grain production rate, 1000 kernels weight) and yield per plot of maize were studied with multiple regression and path analysis by using Statistica DPS3.01 software.. The results indicated that yield per plot was significantly correlated with plant height , ear position, ear length , ear diameter , row number of per ear , kernel number of per row , cod diameter, grain production rate,1000 kernels weight). The relative importance of the eight agronomic traits correlated with yield per plot of maize was in order of 1000 kernels weight row number of per ear plant height ear diameter cod diameter ear position kernel number of per row grain production rate. The yield per plot of maize had signifi- cant linear relationship with the eight agronomic traits.
Key concepts: Mathematics, Path analysis (statistics), Yield (engineering), Agronomy, Kernel (algebra), Grain yield, Path coefficient, Linear regression