A novel method for online sex sorting of silkworm pupae (Bombyx mori) using computer vision combined with deep learning

IF 3.5 2区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY Journal of the Science of Food and Agriculture Pub Date : 2025-02-12 DOI:10.1002/jsfa.14177

Feng Guo, Wei Qin, Xinglan Fu, Dan Tao, Chunjiang Zhao, Guanglin Li

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Abstract

BACKGROUND

Silkworm pupae (SP), the pupal stage of an edible insect, have strong potential in the food, medicine, and cosmetic industries. Sex sorting is essential to enhance nutritional content and genetic traits in SP crossbreeding but it remains labor intensive and time consuming. An intelligent method is needed urgently to improve efficiency and productivity.

RESULTS

To address the problem, an automatic SP sex-separation system was developed based on computer vision and deep learning. Specifically, based on gonad features, a novel real-time SP sex identification model with cascaded spatial channel attention (CSCA) and G-GhostNet (GPU-Ghost Network) was developed, which can capture regions of interest and achieve feature diversity efficiently. A new loss function was proposed to reduce model complexity and avoid overfitting in the training. In comparison with benchmark methods on the test set, the new model achieved superior performance with an accuracy of 96.48%. The experimental sorting accuracy for SP reached 95.59%, validating the effectiveness of the novel gender-separation strategy.

CONCLUSION

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一种基于计算机视觉和深度学习的家蚕蛹在线性别分类新方法。

背景：蚕蛹是一种可食用昆虫的蛹阶段，在食品、医药和化妆品行业具有很强的潜力。性别分选是提高SP杂交中营养成分和遗传性状的重要手段，但其劳动强度大，耗时长。迫切需要一种智能的方法来提高效率和生产率。结果：针对这一问题，开发了基于计算机视觉和深度学习的SP性别自动分离系统。具体而言，基于性腺特征，建立了一种基于级联空间通道注意（CSCA）和G-GhostNet （GPU-Ghost Network）的实时SP性别识别模型，该模型能够有效地捕获感兴趣区域并实现特征多样性。提出了一种新的损失函数，降低了模型的复杂度，避免了训练中的过拟合。与测试集上的基准方法相比，新模型取得了更好的性能，准确率达到96.48%。SP的实验分选准确率达到95.59%，验证了该方法的有效性。结论：本研究提出了一种实用的在线SP性别分离方法，可能有助于高质量SP的生产。©2025 Society of Chemical Industry。

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来源期刊

Journal of the Science of Food and Agriculture 工程技术-农业综合

CiteScore

8.10

自引率

4.90%

发文量

634

审稿时长

3.1 months

期刊介绍： The Journal of the Science of Food and Agriculture publishes peer-reviewed original research, reviews, mini-reviews, perspectives and spotlights in these areas, with particular emphasis on interdisciplinary studies at the agriculture/ food interface. Published for SCI by John Wiley & Sons Ltd. SCI (Society of Chemical Industry) is a unique international forum where science meets business on independent, impartial ground. Anyone can join and current Members include consumers, business people, environmentalists, industrialists, farmers, and researchers. The Society offers a chance to share information between sectors as diverse as food and agriculture, pharmaceuticals, biotechnology, materials, chemicals, environmental science and safety. As well as organising educational events, SCI awards a number of prestigious honours and scholarships each year, publishes peer-reviewed journals, and provides Members with news from their sectors in the respected magazine, Chemistry & Industry . Originally established in London in 1881 and in New York in 1894, SCI is a registered charity with Members in over 70 countries.