Abstract

The present study was conducted aiming to evaluate the individual and combined impact of temperature and rainfall on mustard yield through detrended production index for five districts of West Bengal viz., Hooghly, Nadia, Burdwan, Mursidabad and South 24 Parganas. The crop data and weather information were collected from various stations of those five locations. The selected study areas belong to different agroclimatic zones of the state, namely old alluvial zone, new alluvial zone and coastal saline zone. Mustard growing season in these districts starts from middle of October and continues upto middle of January (Rabi season). The detailed information on yield for 18 years (1997 to 2014) was collected from Government of West Bengal and weather data were collected from India Meteorological Department. The entire growing season of mustard was divided into vegetative and reproductive stages for convenience of the study. Although a definite trend among them existed. Moreover, when all the five locations are considered, overall increase in the year-wise yield was significant with R2 value 0.63. Some R square had poor values. Higher values of R2 indicated the significance of technological trend in case of Hooghly (R2 = 0.46), Nadia (R2 = 0.65) and South 24 Parganas (R2 = 0.73) districts where as it was not significant for Burdwan and Mursidabad. A gradual decrease in yield was observed with temperature increment from 0.50C to 2.00C. The results indicated a reduction of 0.36%, 0.72%, 1.01% and 1.4% in mustard yield in 0.50C, 10 C, 1.50C and 20C increased temperature condition, respectively. Declined yield of mustard will be 908 kg ha-1 in the study location at 20C more temperature condition. Yield reduction is more if higher temperature coincides with the vegetative stage. Time of sowing should be adjusted so that vegetative stage can escape the high temperature period. But all other required management practices should be performed along with the mentioned one. Otherwise several other biotic and abiotic stresses may lower down the yield too. Thus, the results of this work strongly support the idea of engaging DPI to evaluate the impacts of prime weather parameters on crop production and generate yield forecasting models based on that

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