Modelling regional level spatial distribution of aphid (Lipaphis erysimi) growth in Indian mustard using satellite-based remote sensing data

Abstract

We developed a procedure for preparing a model for mapping spatially distributed zones of aphid pest (Lipaphis erysimi) outbreaks at a regional level. This study employed near-surface meteorological parameters derived from National Oceanic and Atmospheric Administration (NOAA) Television and Infra-Red Operational Satellites (TIROS) Operational Vertical Sounder (TOVS) data and field observations of disease infestation. The study area comprised three sites representing semi-arid and sub-humid regions of dominant Indian mustard (Brassica juncea L.)-growing regions of India. A model based on TOVS-derived cumulative surface air temperature and minimum specific humidity (SpH) was developed to estimate the date of ‘aphid onset’ (first appearance), date of peak infestation and location of severity with respect to aphid population density. Aphid population growth rate during the linear growth phase between aphid onset to peak was computed using SpH-weighted temperature and dates of sowing of the crop (crop age). Sowing dates of mustard crop, of northwest India, were obtained from spectral growth profiles derived from time series remote sensing (RS) products of the SPOT-4 VEGETATION sensor. Estimated dates of peak aphid infestation and peak population showed a strong match with the observed data. The location of peak aphid population density was depicted in each spatial grid of 25×25 km2 for parts of northwest India. The simulated aphid population build-up and date of peak population density was validated with observed data for an unknown site in the Sriganganager district, Rajasthan state, India. Comparison of predicted dates of attaining peak aphid population with observations showed a deviation of ±7 days. After validation, the regional level model was applied over a large area of a mustard-growing region for varying dates of sowing, surface air temperature and specific humidity, to show the spatial distribution of aphid growing severity zones (population density) and to predict dates of severe aphid infestation (peak population) at each grid level in the region.