Applying deep learning and machine learning to the study of coconut palm disease

CSE

Deep learning methodologies are being integrated into coconut cultivation to enhance disease control, increase productivity, and extend crop lifespan. These technologies can mechanize the detection process and provide farmers with more control, minimizing losses, and stimulating the agricultural sector. The Coconut Development Board (CDB) was established by the Indian government to promote coconut culture and offer financial incentives to growers. Tamil Nadu, the top state in coconut cultivation, accounts for 33.84 percent of the country's annual output, covering an area of 4.65 lakh hectares. Coimbatore is the most productive coconut-producing district, with an annual cultivation rate of 1200 million coconuts. Coconuts are versatile crops with applications in food, beverage, and artisanal products sectors. The agriculture industry is the primary contributor to India's GDP, but its contribution is decreasing. The objective is to accelerate the process of improving sustainability, diversity, productivity, and competitiveness in agriculture. Insufficient knowledge about illnesses and financial constraints can prevent farmers from seeking medical attention when necessary, leading to complex and costly procedures.

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