A multi-stage tracking for mustard rot disease combining surface meteorology and satellite remote sensing
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 5km5km (27.0027.25N; 77.2577.50E) in Bharatpur district of Rajasthan state of North-West India is demonstrated. In addition to surface weather data, post-facto analysis of 5-year (20032007) 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 (1:30pm) and night time (1:30am) 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.
sclerotinia sclerotiorum india modis hyperspectral brassica juncea