Application of Artificial Intelligence in Coffee Plantation in India

Abstract

India's coffee plantation sector has many difficulties, such as unpredictable weather patterns, pest infestations, and wasteful use of resources. In order to address these problems and improve the productivity, sustainability, and profitability of coffee growing, this study investigates the use of artificial intelligence (AI).

Evaluation of artificially intelligent machines potential for resource optimization, yield forecast improvement, early disease and pest detection, and climate change adaptation are the main goals. Additionally, the project seeks to determine whether implementing AI technology in India is feasible, especially for small and marginal farmers.

By gathering information from published research papers, industry and government reports, and datasets from reliable sources like the Coffee Board of India. To evaluate the real-world effects of AI, suitable case studies are reviewed. The results are then combined to offer suggestions for expanding the use of AI in Indian coffee farms.

The findings show that systems powered by AI greatly increased resource efficiency, resulting in a 20% decrease in water usage and a 30% increase in early identification of insects. Coffee bean quality shown a noticeable improvement, and yield estimations were more accurate, supporting supply chain planning. On average, farmers that used AI technology reported a 15% boost in profitability.

The study comes to the conclusion that artificial intelligence could transform Indian coffee farming, therefore strengthening its sustainability and resilience. Collaborative efforts involving farmers, technology providers, and policymakers are essential to scale AI adoption and overcome challenges such as high costs and limited technical expertise.