Predictive Modelling for Whitefly Control in Cotton: Evaluating Sprayer Efficiency using PLS Regression and ANN Techniques
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Authors
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SANTOSH KUMAR
PUNJAB AGRICULTURAL UNIVERSITY-Ludhiana-141004 India
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Apoorv Prakash
PUNJAB AGRICULTURAL UNIVERSITY-Ludhiana-141004 India
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Anand Gautam
PUNJAB AGRICULTURAL UNIVERSITY-Ludhiana-141004
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Vijay Kumar
ICAR-Central Institute of Agricultural Engineering, Bhopal-462038
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Mandeep Pathania
PUNJAB AGRICULTURAL UNIVERSITY-Ludhiana-141004 India
Abstract
Cotton, a vital fiber cash crop in India, is facing challenges from various pests, i.e., whiteflies, which pose a significant threat. A study was conducted to select the right spraying technology for pest control in the cotton crop. An experiment was conducted to evaluate seven sprayers, including high clearance boom sprayer, air-assisted drop-up boom sprayer, auto-rotate gun, air-assisted electrostatic sprayer, engine-powered knapsack, manually operated knapsack, and UAV sprayers, based on droplet density, size, coverage, spray volume deposition, and bio-efficacy. These insights aid farmers in adopting suitable commercially available technologies for effective pest management in cotton crops. From the experimental results, it was found that the electrostatic sprayer was most effective against whiteflies. An economic analysis considered costs, and PLSR/ANN models predicted whitefly populations, with ANN showing superior accuracy (MSE=8.31, R²=0.74), recommending engine-powered gun sprayers for optimal control. Field assessments favored high clearance boom and drone sprayers, offering cost efficiencies. Eventually, the optimal choice of a sprayer should align with the specific needs and circumstances of the farm.
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References
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