MULBERRY DATASETS OF SERICULTURE DEPARTMENT GOVERNMENT OF ANDHRA PRADESH

About Dataset

The Mulberry Leaf Quality Dataset has been developed by the Department of Sericulture to facilitate data-driven approaches in improving silk productivity. Mulberry leaves serve as the primary feed for silkworms, and their quality significantly influences larval growth, survival rate, and cocoon yield. This dataset includes high-resolution smartphone images of mulberry leaves captured under field conditions along with structured metadata such as leaf variety, harvest age, plot identification, and rearing stage. Additionally, it integrates cocoon yield parameters including average cocoon weight, shell ratio, and Effective Rearing Rate (ERR%), enabling correlation analysis between leaf quality and production outcomes. The dataset supports development of machine learning models for: • Leaf quality classification (Good / Medium / Poor) • Cocoon yield prediction at batch level • Advisory generation for optimal harvesting and feeding practices It is designed to function in low-connectivity rural environments using minimal inputs, ensuring scalability and usability for field staff and farmers.