Noval Approach using Image Detection to Identify Diseases in Fruit Plants (Apple)

In the face of the critical imperative to feed a projected global population of 9 billion people by 2050, India, harboring one of the world's largest populations, grapples with formidable challenges in food production, exacerbated by substantial crop losses. An alarming statistic reveals that approximately 30 percent of India's agricultural yield succumbs to various factors, including pests, diseases, and post-harvest inefficiencies. This staggering loss not only poses a severe threat to India's food security but also contributes significantly to the broader global food crisis. Traditional solutions, often reliant on chemical pesticides, not only fall short in effectively addressing these challenges but also incur adverse environmental impacts, further exacerbating the sustainability dilemma. In response to this pressing issue, a groundbreaking research project emerges, advocating for innovative approaches that seamlessly integrate advanced technology, data-driven insights, and inclusivity to forge a resilient and sustainable agricultural ecosystem. This transformative initiative specifically targets the identification of plant diseases in apple trees, recognizing the potential ripple effects on broader agricultural practices. By leveraging cutting-edge technology like CNN and CAE the research introduces a comprehensive methodology that not only efficiently identifies and manages plant diseases but also holds the promise of sustainable crop management and economic stability.