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Discrimination of Cocoon Sex Using Middle-Infrared Spectroscopy with the Aid of Chemometrics

机译：借助化学计量学，使用中红外光谱区分茧性

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Study on method of discriminating cocoon sex on basis of middle-infrared spectroscopy.Cocoon was cut to identify cocoon sex through examining its pupa, and male and female sex was set to values of 1 and 0 respectively. It were acquired that the attenuated total reflectance spectra of cocoon samples from wavenumber 4 000 cm-1 to 600 cm-1. After one odd spectrum was rejected through principal component cluster analysis, twenty-seven samples were selected randomly as calibration set and the other 13 were as test set. It was analyzed that the influence of Savitzky-Golay convolution smooth (window points was 3, 5, 7, 9, 11 and 13) and different principle components (1-10) on prediction accuracy. Establish PLS model and artificial neural networks model. Results indicated that 100 percent prediction accuracy for both calibration and prediction sets could be achieved when 3 principle components and 3 window points for Savitzky-Golay convolution smooth were adopted in PLS model, or 2 principle components and 5 window points for Savitzky-Golay convolution smooth. It indicated that MIR spectroscopy can be used for prediction of cocoon sex.
机译：基于中红外光谱法鉴别茧性的方法的研究。将茧切去以通过检查其来鉴定茧性，将男女分别设置为1和0。测得茧样品从波数4000 cm-1到600 cm-1的衰减全反射光谱。通过主成分聚类分析剔除一个奇数光谱后，随机选择27个样品作为校准集，其他13个样品作为测试集。分析了Savitzky-Golay卷积平滑度（窗口点为3、5、7、9、11和13）和不同的主成分（1-10）对预测精度的影响。建立PLS模型和人工神经网络模型。结果表明，在PLS模型中采用Savitzky-Golay卷积平滑的3个主成分和3个窗点，或对于Savitzky-Golay卷积平滑采用2个主成分和5个窗点，则校准和预测集的预测精度都可以达到100％ 。这表明MIR光谱可用于预测茧性。

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