Cotton is the main source of commercial fiber. In India's economy, it is one of the most important cash crops. This study used secondary data to look at the growth in cotton crop area, production, and productivity in the Ballari district of Karnataka over the last 46 years (1970–2016).The findings demonstrated that the cotton crop's area, production, and productivity increased significantly over the study period. In terms of area (2.8 per cent), production (3.3 per cent), and productivity, the Ballari district increased significantly (3.0 per cent). To know more about cotton crop acreage, production, and productivity trends in the Karnataka district of Ballari, The quartic model was determined to be the best fit among the various polynomial models fitted for the acreage, production, and productivity of the cotton crop in the Ballari district, with an RMSE of 12.9 and an adj.R2 value of 0.8. The best fit for production was a quartic model with an RMSE of 18.7 and an adj.R2 value of 0.87, while the best fit for productivity was a cubic model with an RMSE of 50.6 and an adj.R2 value of 0.8.
The El Niño-Southern Oscillation (ENSO) is a recurring climate pattern involving changes in the temperature of waters in the central and eastern tropical Pacific Ocean. The three phases of the El Niño–Southern Oscillation (ENSO) namely the neutral phase, El Niño and La Niña oscillations. El Niño refers to the above-average sea-surface temperatures that periodically develop across the east-central equatorial Pacific. It represents the warm phase of the ENSO cycle. La Niña refers to the periodic cooling of sea-surface temperatures across the east-central equatorial Pacific. The state of Karnataka is located on a table land in the angle where the Western and Eastern Ghat ranges converge into the Nilgiri hill complex. 41 year (1980-2020) average annual rainfall of Karnataka collected from the rain gauge station located under the farm universities of Karnataka and, SST and SOI data collected from NOAA were used to study the rainfall variability while ENSO events. The El Niño events will deviate the rainy winds towards eastern pacific region causing lesser rainfall on Indian sub-continent or draughts in some years, but when it comes to Karnataka El Niño events have given above average rainfall. There were 8 episodes of excess rainfall and 6 episodes of deficient rainfall during the 14 El Niño episodes, and 3 episodes of excess rainfall and 8 episodes of deficient rainfall during the 11 La Niña episodes. The remaining 16 episodes were neutral years, with 10 episodes having excessive rainfall and the remaining 6 having deficient rainfall. Hence the El Niño episodes is good when compared to La Niña episodes over Karnataka.
Rainfall is one of the important weather factors deciding the economy, food habits, industries and work force of the area. Distribution of rainfall throughout the year further decides cropping pattern, variety to be cultivated and duration of the crop and management practices for efficient rainfall utility. In this regard 51 year past rainfall data (1970-2020) of Dharwad district of Karnataka was collected from Main Agricultural Research Station (MARS), UAS, Dharwad for analysing seasonal, annual and monthly variabilities. From the analysis we found that the rainfall varied in the range of 417 to 1316 mm with the average of 748 mm and with the variation of 22 per cent. Five years moving rainfall average showed declining trend. July month recorded highest average rainfall of 136 mm with the lowest variation (39 per cent). Though January month recorded lowest rainfall (one mm), the highest variation was observed in February. Southwest (Jun-Sept), Northeast (Oct-Dec), Winter (Jan-Feb) and Post monsoon (March-May) contributed 65 per cent, 19 per cent, 1per cent and 15 per cent, respectively of the annual rainfall of Dharwad district. The lowest variation in rainfall over the years was observed in Southwest monsoon (27 per cent) while winter season showed highest variation. Farmers can be advised to take long duration crops like Cotton and Maize in kharif because of nearly even distributed rainfall for the months from June- October and early sowing in case of rabi to harness the more moisture for better yield. Summer sowing should be avoided because of more uncertainty in rainfall.
Climate smart agriculture (CSA) is a strategy for guiding the transformation and reorientation of agricultural production in light of the new realities of climate change. CSA manage the climate risks by adapting and building resilience of agricultural and food security system to climate change at multiple levels. CSA involves dissemination of the advance weather information to the farmers through different state of art information technology (SMS, apps and e-mail) are being taken to control and minimize of loss of crop due to pest and diseases incidences. Increase agricultural productivity and incomes; adapt to and build resilience to climate change; and reduce or eliminate greenhouse gas emissions from agriculture are the three pillars of the CSA. Under the Gramin Krishi Mausam Sewa (GKMS) scheme, the Agrometeorological Advisory Service (AAS) of the India Meteorological Department (IMD), Ministry of Earth Sciences (MoES), collects and organises climate/weather, soil, and crop information and combines it with weather forecast to assist farmers in making management decisions. Gramin Krishi Mausam Sewa (GKMS), District Agro-Met Units (DAMUs), and the IMD Mausam Website are examples of CSA projects. They deliver crop-specific alerts to farmers using meteorological parameters and a variety of print, visual, radio, and IT-based media, including short message service (SMS) and Interactive Voice Response Service (IVRS). This CSA will assist farmers in anticipating the occurrence of pests and illnesses, allowing for the scientific and sensible scheduling of preventative actions.
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