Alternaria blight is destructive disease of rapeseed- mustard caused by Alternaria brassicae (Berk) Sacc. and A. brassicicola (Schw). The field experiments were conducted during 2013-14 and 2014-15, with 200 genotypes for evaluation of their resistance to Alternaria blight, as well as to develop effective management strategies for this disease. None of the genotypes were found disease free or highly resistant, only 7 genotypes namely (DLSC-1, DRMR-261, DRMR-270, GSC-101, GSL-1, NPC-20 and PHR-2) were found resistant, 15 genotypes were rated as moderately resistant. Rest of the genotypes was either recorded susceptible or highly susceptible.For disease management, newly molecules of 6 fungicides were evaluated with 13 treatments combinations for their effectiveness. Propiconazole 25% EC @ 0.10% was found most effective in reducing the disease severity followed by same fungicide @ 0.05%. It was followed by Hexaconazole 5% SC @ 0.010%. Maximum test weight and yield was also recorded with the sprays of Propiconazole 25% EC @ 0.10% followed by same fungicide @ 0.05%. In comparison to other fungicides, the maximum B:C ratio was recorded with three sprays of Hexaconazole 5% SC @ 0.05% followed by Propiconazole 25% EC @ 0.05%.

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For the purpose of deriving spatiotemporal estimates of soil moisture, the triangle method is one of the most widely used approaches today utilizing remote sensing data. Generally, those techniques are based on the physical relationships that exist when a satellite-derived land surface temperature (Ts) is plotted against a spectral vegetation index (VI). The present study proposes an improvement in the triangle method in retrieving soil moisture over heterogeneous areas. In particular, it proposes a new approach in robustly identifying the extreme points required for the technique’s implementation. Those extreme points are then used in calculating fractional vegetation cover (Fr) and scaled Ts. Furthermore, the study proposes a new approach for calculating the coefficients required to develop the relationships between surface soil moisture (SSM) and Fr/Ts, which is implemented using a model and field data. As a case study, an agricultural field in the Varanasi district in India has been used, on which the triangle method is implemented using ECOSTRESS and Sentinel-2 data. The much-improved spatial resolution satellite data of ~70 m from ECOSTRESS allowed deriving more vivid results of SSM spatial variability for the study area. Comparisons between field soil moisture calculated using the proposed method returned an RMSE of 0.03 and R2 value of 0.84, which are considered very satisfactory. The methodology proposed herein and the results obtained are of significant value with regards to the triangle method, contributing to ongoing efforts at present examining its use for operational product development at a global scale.

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