Deep learning based robust analysis of laser biospeckle data for detection of fungal infected soybean seeds

Abstract

The agricultural sector holds significant global importance as it serves as a foundation for various industries, plays a crucial role in ensuring food security, and acts as a catalyst for economic growth. In India, agriculture assumes paramount significance by providing livelihood opportunities, making substantial contributions to the country’s gross value added (GVA), and providing crucial economic sustenance to the low-income population. However, seed-borne pathogens, including bacteria, fungi, and viruses, significantly challenges crop production. These pathogens adversely affect seed germination and seedling establishment, resulting in low crop yields and reduced productivity. Soybean, a crucial crop worldwide, serves various purposes such as food security, animal feed, biofuel production, and sustainable agriculture. Seed-borne diseases in soybeans are transmitted through infected seeds and pose threats to plant health, vigor, and overall productivity. Enhancing productivity and satisfying global food demands depend on addressing these challenges and ensuring healthy and high-quality seeds.