Developing Algorithms to Determine the Similarity Levels of Plant Varieties Based on Important Traits

This study focuses on developing algorithms for assessing the similarity levels of various plant varieties based on critical traits. Identifying and analyzing these traits is essential for effective classification and breeding practices. By employing various similarity measures and clustering techniques, we aim to establish a comprehensive framework that quantifies the relationships between plant varieties. The proposed methodology includes data collection, trait selection, calculation of similarity scores, and validation of results. The findings will not only enhance our understanding of plant diversity but also provide valuable insights for agricultural practices and conservation efforts.