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  • Title: [Methods of analyzing soybean meal adulteration in fish meal based on visible and near infrared reflectance spectroscopy].
    Author: Shi GT, Han LJ, Yang ZL, Liu X.
    Journal: Guang Pu Xue Yu Guang Pu Fen Xi; 2009 Feb; 29(2):362-6. PubMed ID: 19445204.
    Abstract:
    The present study investigated the feasibility of visible and near infrared reflectance spectroscopy (NIRS) method for the detection of fish meal adulteration with vegetable meal. Here the authors collected fish meal and soybean meal (representative vegetable meal) which were common used in our country. Fish meal was adulterated with different proportion of soybean meal and then the doping test samples were prepared. Qualitative discriminant analysis and quantitative analysis were studied with representative fish meal adulterated with soybean meal. Two hundred and six calibration samples and 103 validation samples were used in the qualitative discriminant analysis. The effects of different spectrum pre-treatment methods and spectrum regions were considered when the qualitative discriminant analysis model was established. Based on the smallest standard error of cross validation (SECV) and the correct rate, the spectrum region of visible and NIR was chosen as the best region. The eventually established pre-treatment methods were the standard multi-scatter correction (Std MSC) combined with the second derivative (2, 4, 4, 1). Then the independent external validation set was used to test the model, and there was no false positive samples and false negative samples. The correct discriminant rate was 96.12%. In quantitative analysis, 130 fish meal samples adulterated with soybean meal were used as calibration set. The calibration model was established by partial least squares (PLS). Furthermore, the effect of different spectrum pre-treatment methods and the spectrum region were considered. The results showed that the best pre-treatment method was the standard normalized variate (SNV) combined with the second derivative (2, 4, 4, 1). The coefficient of determination (R2) and the standard errors of calibration (SEC) were 0.989 0 and 1.539 0 respectively between the predictive value and the actual value. Sixty five fish meal samples adulterated with soybean meal were used as independent validation set. The coefficient of determination (R2) and the standard errors of prediction (SEP) were 0.988 8 and 1.786 0 respectively, and the ratio of standard deviation of reference data in prediction sample set to the standard errors of prediction (RPD) was 8.61. The results showed that the NIRS could be used as a method to detect the existence and the content of soybean meal in fish meal.
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