Sign inSubmit
computersciencejournal.org is not ours. This journal is published only at thescipub.com/jcs. Report a suspicious emailcomputersciencejournal.org is not ours · Report
ArticleMetrics
Review Article · Open access · Published 17 June 2025

Review on Different Algorithms and Techniques Used in Classification of Gender in Silkworm

Jyoti Sharma1 & Pradeep Chouksey1

Journal of Computer Science, Volume 21, Issue 6, pp. 1354–1363 · doi.org/10.3844/jcssp.2025.1354.1363

4,031 accesses2,220 downloads3 citations (Crossref)Metrics
Cite Check for updates

Abstract

Silkworm seed is the key factor for the success of sericulture industry. Silk seed production process at grain ages centre mainly involve procuration of seed cocoon, cutting of seed cocoon for pupae, separation of male and female pupae, emergence of moth, coupling of silk moth and further egg laying by female moth. Separation of male and female is very much crucial and vital step in silk seed production which usually occurs at pupal stage and requires highly skilled and trained workers with good eyesight, but there are chances of error which may lead to poor quality silk seed production. There is also wastage of silk due to cutting of cocoon for obtaining pupa. It is also a fact that male cocoon silk is of finer quality as compared to female cocoon silk, so it is of great importance to detect the sex of pupa without cutting of cocoon so as to minimize the damage caused to silk by cutting of cocoon. In this review study various techniques including both destructive and non-destructive methods regarding the gender detection are discussed with their future scope and limitations. A variety of techniques were investigated, including optical penetration techniques, fluorescence spectrometry, DNA, X-ray imaging, MRI, hyper spectral imaging, near infrared spectroscopy, physical observations, multisensory systems, and computer vision etc. According to recent studies, relatively few non-destructive techniques have been noticed to classify silkworm's gender which is very much essential in dealing with living material in connection to that present review study is conducted.

Licence and reuse

Open access. This article is licensed under a Creative Commons Attribution 4.0 International Licence (CC BY 4.0), as printed on the article, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original authors and the source. No permission is needed.

How to reuse this article

Responses (0)

Have a comment on this research? Sign in to respond. Responses are moderated and published with your name and affiliation; the authors are invited to reply. How we use your dataWrite a response

About this article

Cite this article

Sharma, J. & Chouksey, P. (2025). Review on Different Algorithms and Techniques Used in Classification of Gender in Silkworm. Journal of Computer Science, 21(6), 1354–1363. https://doi.org/10.3844/jcssp.2025.1354.1363

Licence
CC BY 4.0
Issue
Volume 21, Issue 6
Policies
Editorial independenceUse of generative AIData availabilityAppeals and complaints
Version
Version of record
Review on Different Algorithms and Techniques Used in Classification of Gender in SilkwormJournal of Computer Science · Volume 21, Issue 6 · pp. 1354–1363 · CC BY 4.0Download