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A Review on Existing Methods and Classification Algorithms Used for Sex Determination of Silkworm in Sericulture

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Intelligent Systems Design and Applications (ISDA 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1351))

Abstract

India is one of the major producers and exporters of silk across the world. Sericulture is the term used for the cultivation of silkworms for the production of silk. It includes farming of mulberry, rearing of silkworm, reeling, and twisting to make raw silk. Sericulture is a part of Indian culture especially in the southern states of India are famous for the mulberry silks. Seeds for the production of silkworms are produced in reeling units by mating male and female moths. This requires separation of male and females based on gender. Segregating males and females is a tedious task and this is done in the pupa stage of the silkworm life cycle. In other stages classification is very difficult. The conventional method of gender classification in grainage centers is by expert employees with physical observation. Due to the long hours of work and human errors misclassification occurs and which affects quality seed production. Also for the physical observation cutting of cocoon is needed to take the pupa out and this will damage silk filament as well as sometimes the pupa. Classification of silkworm cocoon has another advantage as male cocoons produce finer silk than females so classification will help to reduce the mixing of silk with different quality. In this review article, the existing methods for the automation of the silkworm classification such as hyperspectral imaging technology, near-infrared spectroscopy, fluorescence characteristics, X-ray, MRI, optical penetration, DNA, computer vision, and the present physical observation methods were explored.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India

    Sania Thomas & Jyothi Thomas

  2. Department of Computer Science and Engineering, Saintgits College of Engineering, Kottayam, India

    Sania Thomas

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  1. Sania Thomas
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  2. Jyothi Thomas
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Correspondence to Sania Thomas .

Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Department of Computer Science, Università degli Studi di Milano, Milan, Milano, Italy

    Vincenzo Piuri

  3. Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Niketa Gandhi

  4. Campus Centre de Créteil, Université Paris-Est Créteil, Créteil, France

    Patrick Siarry

  5. Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, Vilnius, Lithuania

    Arturas Kaklauskas

  6. School of Engineering, Instituto Superior de Engenharia do Porto, Porto, Portugal

    Ana Madureira

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Thomas, S., Thomas, J. (2021). A Review on Existing Methods and Classification Algorithms Used for Sex Determination of Silkworm in Sericulture. In: Abraham, A., Piuri, V., Gandhi, N., Siarry, P., Kaklauskas, A., Madureira, A. (eds) Intelligent Systems Design and Applications. ISDA 2020. Advances in Intelligent Systems and Computing, vol 1351. Springer, Cham. https://doi.org/10.1007/978-3-030-71187-0_52

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