Bhattacharya, BK; Chattopadhyay, C (2013). A multi-stage tracking for mustard rot disease combining surface meteorology and satellite remote sensing. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 90, 35-44.
Disease forecasting forms an integral part of crop protection for ensuring quality and quantity of production. In this paper, a new method of multi-stage tracking of Sclerotinia rot (Sclerotinia sclerotiorum) disease in a large mustard growing region over 5 km x 5 km (27.00-27.25 degrees N; 77.25-77.50 degrees E) in Bharatpur district of Rajasthan state of North-West India is demonstrated. In addition to surface weather data, post-facto analysis of 5-year (2003-2007) satellite-based data of surface reflectances in red (R), near infrared (NIR) and shortwave infrared (SWIR) bands, land surface temperature (LST) from Moderate Resolution Imaging Spectroradiometer (MODIS) AQUA at day (1:30 pm) and night time (1:30 am) LST, were done to characterize disease outbreak (stage-I) and persistence (stage-II). While stage-I evaluation was based on anomaly in minimum air temperatures and night time LST, stage-II evaluation was carried out using quadrant-based trapezoidal clusters between soil and canopy dryness indicators. Hyperspectral data on two dates from Hyperion sensor at EO-1 platform were used for two-step spectral discrimination to select bands and disease indices specific to rot. Among all the hyperspectral indices, a three-band rot index (ROTI) was found to be the better one in field scale rot discrimination (stage-III evaluation). The reduction in fractional canopy cover in diseased patches in 2005 as compared to a normal year (2007) indirectly validated the disease effect. (c) 2012 Elsevier B.V. All rights reserved.