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- W2037293731 abstract "► Persistent low temperature in second fortnight of January triggered Sclerotinia rot. ► Regular night time thermal infrared satellite observations helped issue advisories. ► Quadrant-based cluster in TVDI - NDWI trapezoidal space aided minimize crop damage. ► Stage-III evaluation relates to damage assessment. 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 × 5 km (27.00–27.25°N; 77.25–77.50°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." @default.
- W2037293731 created "2016-06-24" @default.
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- W2037293731 date "2013-01-01" @default.
- W2037293731 modified "2023-10-14" @default.
- W2037293731 title "A multi-stage tracking for mustard rot disease combining surface meteorology and satellite remote sensing" @default.
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- W2037293731 doi "https://doi.org/10.1016/j.compag.2012.10.001" @default.
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