An Analysis on Factors Influencing the Adoption of Cultivation Practices among ELS Cotton Growers in Karnataka, India

Aim: The present study was conducted to analyse the adoption behavior of ELS cotton cultivation practices and to identify the factors influencing the adoption behavior of ELS cotton cultivation among the farmers. Place and Duration of Study: The study was conducted during 2022 in Chamarajanagar district of Karnataka, one of the important regions cultivating Extra Long Staple (ELS) cotton. Methodology: A total of 200 respondents were selected for the study using the Simple Random Sampling technique to ensure adequate representation of the farming population. To assess adoption behaviour, eleven key recommended practices related to ELS cotton cultivation were selected. Each respondent was presented with these practices individually and asked to indicate their level of adoption. Results: High adoption was observed in land preparation (summer ploughing and harrowing), seed rate and depth management, hand weeding, crop rotation, and chemical control based on ETL. Harvesting related practices such as frequent picking, selecting well burst bolls, and shade drying were also widely followed. Many recommended practices were adopted by ELS cotton farmers, though several were implemented with practical modifications to suit field realities, labour constraints, and resource availability. Key adjustments were observed in spacing, organic manure use, NPK top dressing, refuge crop planting, ridges & furrow planting, and morning harvesting. In contrast, practices that required higher technical skill, greater cost, or specialized knowledge showed poor adoption. These included micronutrient and foliar nutrition, growth regulators, terminal growth arresting, seed treatment, trap cropping, bio-control agents, pheromone traps, and irrigation at critical stages. Conclusion: Overall, practices that were simple, low cost and clearly linked to immediate price benefits had high adoption, whereas those requiring additional labour, time, infrastructure, or specialized knowledge had lower adoption among farmers.