Food and Fermentation Industries >

2022 , Vol. 48 >Issue 12: 275 - 280

DOI: https://doi.org/10.13995/j.cnki.11-1802/ts.028608

Origin discrimination of transgenic soybean based on near infrared spectroscopy and chemometrics

  • LEI Yuanxiong ,
  • XIA Alin ,
  • HUANG Wei ,
  • HOU Taidong ,
  • WANG Hong
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  • 1(College of Food Science and Chemical Engineering, Shaoyang University, Shaoyang 422000, China)
    2(Suzhou Leaoptics Technology Co.Ltd., Suzhou 215000, China)

Received date: 2021-07-09

  Revised date: 2021-07-29

  Online published: 2022-07-15

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Abstract

In order to develop a nondestructive, rapid and accurate method to identify the origin of transgenic soybeans, 260 samples of transgenic soybeans from four different countries were selected in this study, and these four kinds of transgenic soybeans were analyzed by NIR spectroscopy combined with chemometrics. The original spectra of 260 samples were collected by NIR spectrometer, and the NIR spectra were preprocessed by smoothing +standard normal variate transformation (SNV) method. 240 samples of transgenic soybeans from Argentina, Brazil, America, Canada and Uruguay were selected for modeling. The Kennard-Stone (KS) algorithm divided the training set and the prediction set, principal component analysis (PCA), partial least squares-discriminate analysis (PLS-DA) and back-propagation artificial neural network (BP-ANN) were used to analyze the preprocessed spectral data. The experimental results showed that the preprocessing method of smoothing +SNV can effectively reduce the noise in the NIR spectrum. The PCA method could identify three of the four transgenic soybeans, while Argentina transgenic soybeans and Canada transgenic soybeans could not be identified simultaneously. The accuracy of PLS-DA method in identifying transgenic soybeans in training set was 93.9%, and that of the prediction set was 88.3%. The BP-ANN method was able to identify four kinds of transgenic soybeans accurately with the discrimination accuracy of 100%. The PLS-DA method model and BP-ANN method model were verified with four kinds of transgenic soybeans not involved in the modeling as the verification set. The discrimination accuracy of PLS-DA method model was 90.0%, and that of BP-ANN method model was 100%. Therefore, the combination of NIR spectroscopy and chemometrics could provide a good technical support for the origin discrimination of transgenic soybeans.

Key words： near infrared spectroscopy; stoichiometry; transgenic soybean; traceability

Cite this article

LEI Yuanxiong , XIA Alin , HUANG Wei , HOU Taidong , WANG Hong . Origin discrimination of transgenic soybean based on near infrared spectroscopy and chemometrics[J]. Food and Fermentation Industries, 2022 , 48(12) : 275 -280 . DOI: 10.13995/j.cnki.11-1802/ts.028608

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