Predictive modelling for whitefly (Bemisia tabaci) control in cotton (Gossypium spp.): Evaluating sprayer efficiency using PLS regressionand ANN techniques

SANTOSH KUMAR; APOORV  PRAKASH; ANAND  GAUTAM; VIJAY  KUMAR; MANDEEP  PATHANIA

doi:10.56093/ijas.v96i6.166850

Authors

SANTOSH KUMAR Punjab Agricultural University, Ludhiana, Punjab 141 004, India
APOORV PRAKASH Punjab Agricultural University, Ludhiana, Punjab 141 004, India
ANAND GAUTAM Punjab Agricultural University, Ludhiana, Punjab 141 004, India
VIJAY KUMAR ICAR-Central Institute of Agricultural Engineering, Bhopal, Madhya Pradesh, India
MANDEEP PATHANIA Regional Research Station (Punjab Agricultural University, Ludhiana, Punjab), Ballowal Saunkhri, Punjab, India

https://doi.org/10.56093/ijas.v96i6.166850

Keywords:

ANN, Drone sprayer, High clearance sprayer, PLSR, UAVs

Abstract

Cotton (Gossypium spp. L.), a vital fibre cash crop in India, faces challenges from various insect-pests among which whiteflies pose a significant threat. A study was carried out in 2022 at Abhor district of Punjab 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. From the experimental results, it was found that the electrostatic sprayer was most effective against whiteflies. An economic analysis considered costs, ANN and PLSR models predicted whitefly populations, with ANN showing superior accuracy, recommending engine-powered gun sprayers for optimal control. Field assessments favoured 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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