Construction and Application of the Suitability Index Model for Topping Tobacco Plants
Topping tobacco plants is an important part of theprocess in cultivation of tobacco.By topping tobacco plants,it is possible to artificially intervene the growth process of tobacco plant,change the delivery destination of nutrients in tobacco plant,and alter the growth and de-velopment status of tobacco leaves,thereby increasing the tobacco yield and income for tobacco farmers.This study analyzed the growth status data of tobacco leaves corresponding to tobacco bead topping,statistically analyzed the growth status of tobacco plants after topping,studied the key factors affecting tobacco topping,and constructed a tobacco topping suitability index model.BP neural network was used to study the topping model of tobacco plants.The main fac-tors affecting the topping of tobacco plants have been determined to be the number of leaves,the distance from the flower bud to the topmost leaf of the tobacco plant,and the degree of flower bud opening.The accuracy of the BP neural network analysis model validation set was 78.33％,R2=0.82,MSE=0.59.An application for the tobacco topping suitability index model was developed using the J2EE platform Spring framework.According to on-site verification,the average goodness of fit of modelin actual production was 79.32％.This study provides a reason-able judgment basis for the agricultural operation of tobacco bead topping,and provides scientif-ic support for the digitization and scientific management of tobacco planting.
topping of tobacco plantsinfluencing factorsexponential modelapplication plat-form
万方数据
维普
