Applications of Artificial Intelligence in Sericulture
Rubi Sut, Bidisha Kashyap, Toko Naan
Advances in Research · pp. 430–438 · Published 8 Aug 2024
10.9734/air/2024/v25i41122Abstract
The Sericulture industry is one of the major cottage industries producing higher income with lower input. The industry requires critical inputs like quality seed, quality feed, skilled labour with optimum environmental conditions for smooth running and higher production. Most of these input processes involve only manual assesment of phenotypic traits and are human-centric. In the current environment, producing high-quality silk is crucial to reaching sustainability by 2030. The identification of the barriers preventing the increase of silkworm production is limited by the traditional technique. With the development of artificial intelligence, it is providing many benefits to sectors like sericulture where expert systems are being used to solve many problems like disease and pest, gender classification, changing environmental conditions in both host plant as well as silkworm. For the sericulture industry to thrive amidst a changing world, it must keep pace with evolving challenges. This necessitates emphasizing the integration of intelligent tools. There are various advanced tools like Artificial Intelligence, advanced mechanisations etc. and their use is limited to some extent. As the use of AI is gaining momentum, the sericulture industry is also bound to use them to some extent even though they are not very much popular. This article underscores the importance of leveraging technology for a prosperous future and economy.
Cited by 0
No indexed citations yet.
Related research
- The Impact/Role of Artificial Intelligence in Anesthesia: Remote Pre-Operative Assessment and Perioperative — shares topic coverage
- Detecting Dental Caries through Captured Images Using the Machine Learning Technology Teachable Machine — shares topic coverage
- Harnessing Artificial Intelligence in Healthcare Analytics: From Diagnosis to Treatment Optimization — shares topic coverage
- Diagnostic Accuracy of Artificial Intelligence for Breast Cancer Detection: A Systematic Review — shares topic coverage
- Artificial Intelligence in the Analysis of the Fetal Genome in Utero: A Critical Review of Current Paradigms, Clinical Utility and Future Horizons — shares topic coverage
Article metrics
Real usage data collected on this platform.
0
Page views
0
PDF downloads
0
Outbound clicks
0
Citations
Views by country
Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".
No views recorded yet.
Traffic sources
Referring site, by host.
No traffic recorded yet.
Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.