Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource An optimized method for mulberry silkworm, Bombyx mori (Bombycidae:Lepidoptera) sex classification using TLBPSGA-RFEXGBoost Subject The topic of the resource Accelerated HOG; Classification; RFEXGBoost; Seed production; Sericulture; TLBPSGA Description An account of the resource Silkworm seed production is vital for silk farming, requiring precise breeding techniques to optimize yields. In silkworm seed production, precise sex classification is crucial for optimizing breeding and boosting silk yields. A non-destructive approach for sex classification addresses these challenges, offering an efficient alternative that enhances both yield and environmental responsibility. Southern India is a hub for mulberry silk and cocoon farming, with the high-yielding double-hybrid varieties FC1 (foundation cross 1) and FC2 (foundation cross 2) being popular. Traditional methods of silkworm pupae sex classification involve manual sorting by experts, necessitating the cutting of cocoons a practice with a high risk of damaging the cocoon and affecting yield. To address this issue, this study introduces an accelerated histogram of oriented gradients (HOG) feature extraction technique that is enhanced by block-level dimensionality reduction. This non-destructive method allows for efficient and accurate silkworm pupae classification. The modified HOG features are then fused with weight features and processed through a machine learning classification model that incorporates recursive feature elimination (RFE). Performance evaluation shows that an RFE-hybridized XGBoost model attained the highest classification accuracy, achieving 97.2% for FC1 and 97.1% for FC2. The model further optimized with a novel teaching learning-based population selection genetic algorithm (TLBPSGA) achieved a remarkable accuracy of 98.5% for FC1 and 98.2% for FC2. These findings have far-reaching implications for improving both the ecological sustainability and economic efficiency of silkworm seed production. 2024. Published by The Company of Biologists Ltd. Creator An entity primarily responsible for making the resource Thomas S.; Thomas J. Source A related resource from which the described resource is derived Biology Open, Vol-13, No. 7 Publisher An entity responsible for making the resource available Company of Biologists Ltd Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1242/bio.060468" target="_blank" rel="noreferrer noopener">https://doi.org/10.1242/bio.060468</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201219175&amp;doi=10.1242%2Fbio.060468&amp;partnerID=40&amp;md5=a48cb54af93e58ec25d1b6444cbb4914" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201219175&amp;doi=10.1242%2fbio.060468&amp;partnerID=40&amp;md5=a48cb54af93e58ec25d1b6444cbb4914</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Relation A related resource ISSN: 20466390 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Thomas S., Department of Computer Science and Engineering, Christ University, Bangalore, 560029, India; Thomas J., Department of Computer Science and Engineering, Christ University, Bangalore, 560029, India