Artificial Intelligence on Sericulture

Abstract

Artificial Intelligence (AI) is revolutionizing sericulture, the cultivation of silkworms for silk production, by addressing key challenges and enhancing efficiency, productivity, and sustainability. This document explores the diverse applications of AI in sericulture, including automated disease detection in silkworms, precision feeding, and environmental control in rearing houses. Al-powered image processing and machine learning models enable early identification of diseases like flacherie and muscardine, reducing crop losses. IoT-integrated systems monitor and optimize environmental conditions such as temperature and humidity, ensuring optimal silkworm growth. Predictive analytics forecast silkworm development and yield, aiding in better resource allocation. AI also enhances mulberry plantation management through drone-based surveillance and nutrient analysis, improving leaf quality for silkworm nutrition. Additionally, robotics and automation streamline silk processing, from reeling to weaving, ensuring high-quality output. Al-driven pest management systems detect and control infestations, reducing chemical use and promoting eco-friendly practices. These advancements not only reduce labor dependency but also improve silk quality and yield, making sericulture more sustainable and economically viable. As AI technology evolves, its integration into sericulture promises to further modernize the industry, ensuring resilience against environmental and market challenges.