Agricultural practises such as tilling, sowing, cropping and harvesting along with land-use patterns in any agrarian economy depend on climate. Therefore any adverse climatic conditions can seriously affect the production or yield of the crops. Increased temperature enhances the susceptibility of crops to pests and various plant-diseases. Weeds are also known to multiply rapidly and decrease the nutritive value of soil in turn negatively affecting crop production. Our present study was designed to address similar problems faced by the farming community in the South-24 Parganas district of West Bengal, India and in turn suggest several probable technological solutions. Importantly, West Bengal is included under one of the six agro-climatic zones. Major crops from this study site are rice, wheat, maize, jute, green gram, black gram, pigeon pea, lentils, sugarcane, pulses, rapeseed, mustard, sesame, linseed and vegetables. Significantly cultivable land area has decreased in comparison to overall crop area in this region. Reduced interest in agriculture, irrigation problems, increased profit in non-agricultural economy, rapid conversion of agricultural land for commercial purposes (construction of plots, hatcheries for fishing practices) along with uncertainties associated with rainfall patterns and frequent cyclones are matters of grave concern in this study site. Agricultural scientists, researchers, environmentalists, local bodies and government organizations are suggesting alternatives for benefitting farmers. Thus Precision Agriculture or Crop Management is required to recognise site-specific variables within agricultural lands and formulate strategies for improving decision making regarding crop sowing, appropriate use of herbicides, weedicides, precision irrigation along with innovative harvesting technologies. Thus the present paper would provide a vision to the farming community of our study site to overcome their traditional practices and adopt different techniques of precision agriculture to increase flexibility, performance, accuracy and cost-effectiveness. Usage of soil temperature, humidity and moisture monitoring sensors could be beneficial. Precision soil management, precision irrigation, crop disease management, weed management along with harvesting technologies are the different modules being considered for discussion in this paper. Machine Learning algorithm such as Linear regression, Decision Tree, K-nearest neighbour (KNN), Gaussian Naïve Bayes (GNB) and Support Vector Machine (SVM) could prove helpful for progressive farmers. Usage of AI powered weeding machines, drones, UAVs for rapid weed removal, localised application of herbicides, pesticides could also improve the accuracy and efficiency of agriculture. Utilizing drones fitted with high resolution cameras could help in gathering precision field images in turn proving quite helpful in crop monitoring and crop health assessment. Unmanned driverless tractors, harvesting machines using robotics integrated with data from GPS/GIS sensors or radars could also be considered as an effective and time-saving option. Thus Machine Learning along with innovative agricultural technologies could probably contribute towards improving the livehood of the farming fraternity.
