Non-destructive silkworm pupa gender classification with X-ray images using ensemble learning  

作　　者：Sania Thomas Jyothi Thomas 

机构地区：[1]Department of Computer Science and Engineering,Christ(Deemed to be University),Bangalore,India

出　　处：《Artificial Intelligence in Agriculture》2022年第1期100-110,共11页农业人工智能（英文）

基　　金：funded by the Department of Science&Technology(DST)with grant reference number:SEED/WS/2019/135.

摘　　要：Sericulture is the process of cultivating silkworms for the production of silk.High-quality production of silk without mixing with low quality is a great challenge faced in the silk production centers.One of the possibilities to overcome this issue is by separating male and female cocoons before extracting silk fibers from the cocoons as male cocoon silk fibers are finer than females.This study proposes a method for the classification of male and female cocoons with the help of X-ray images without destructing the cocoon.The study used popular single hybrid varieties FC1 and FC2 mulberry silkworm cocoons.The shape features of the pupa are considered for the classification process and were obtained without cutting the cocoon.A novel point interpolation method is used for the computation of the width and height of the cocoon.Different dimensionality reduction methods are employed to enhance the performance of the model.The preprocessed features are fed to the powerful ensemble learning method AdaBoost and used logistic regression as the base learner.This model attained a mean accuracy of 96.3%for FC1 and FC2 in cross-validation and 95.3%in FC1 and 95.1%in FC2 for external validation.

关 键 词：SERICULTURE Gender classification Stratified k-fold cross-validation Machine learning ADABOOST 

分 类 号：S88[农业科学—特种经济动物饲养] TP39[农业科学—畜牧兽医]