Rapid quantification of goat milk adulteration with cow milk using Raman spectroscopy and chemometrics

被引:0
作者
Li, Wangfang [1 ]
Huang, Wei [1 ]
Fan, Desheng [1 ]
Gao, Xuhui [1 ]
Zhang, Xian [1 ]
Meng, Yaoyong [1 ,2 ]
Liu, Timon Cheng-yi [3 ]
机构
[1] South China Normal Univ, Coll Biophoton, MOE Key Lab Laser Life Sci & Lab Photon Chinese Me, Guangzhou 510631, Peoples R China
[2] South China Normal Univ, Anal & Testing Ctr, Guangzhou 510631, Peoples R China
[3] South China Normal Univ, Lab Laser Sports Med 3, Guangzhou 510631, Peoples R China
基金
美国国家科学基金会;
关键词
IDENTIFICATION; ALPHA(S1)-CASEIN;
D O I
10.1039/d2ay01697d
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
As goat milk has a higher economic value compared to cow milk, the phenomenon of adulterating goat milk with cow milk appears in the market. In this study, the potential of Raman spectroscopy along with chemometrics was investigated for the authentication and quantitation of liquid goat milk adulterated with cow milk. First, the results of principal component analysis (PCA) showed that there were differences between the Raman spectra of cow and goat milk, which made quantitative experiments possible. For quantification, three different brands of cow milk and goat milk were selected randomly and adulterated goat milk with cow milk at the proportion of 5-95%. 342 samples were used for the construction of the partial least squares regression (PLSR) model with 80% for the calibration set and 20% for the prediction set. The PLSR model showed excellent performance in quantifying the level of adulteration, for the prediction set, with a coefficient of determination (R-2) of 0.9781, root mean square error (RMSE) of 3.82%, and a ratio of prediction to deviation (RPD) of 6.8. The results demonstrated the potential of Raman spectroscopy as a rapid, low cost and non-destructive analytical tool for detecting adulteration in goat milk.
引用
收藏
页码:455 / 461
页数:7
相关论文
共 40 条
[1]   Raman spectroscopy based analysis of milk using random forest classification [J].
Amjad, Arslan ;
Ullah, Rahat ;
Khan, Saranjam ;
Bilal, Muhammad ;
Khan, Asifullah .
VIBRATIONAL SPECTROSCOPY, 2018, 99 :124-129
[2]  
Azad T., 2016, International Journal of Food Contamination, V3, DOI DOI 10.1186/S40550-016-0045-3
[3]   Goats' milk of defective αs1-casein genotype decreases intestinal and systemic sensitization to β-lactoglobulin in guinea pigs [J].
Bevilacqua, C ;
Martin, P ;
Candalh, C ;
Fauquant, J ;
Piot, M ;
Roucayrol, AM ;
Pilla, F ;
Heyman, M .
JOURNAL OF DAIRY RESEARCH, 2001, 68 (02) :217-227
[4]  
Bian XH, 2020, ANAL METHODS-UK, V12, P3499, DOI [10.1039/d0ay00285b, 10.1039/D0AY00285B]
[5]   Rapid identification of milk samples by high and low frequency unfolded partial least squares discriminant analysis combined with near-infrared spectroscopy [J].
Bian, Xihui ;
Zhang, Caixia ;
Liu, Peng ;
Wei, Junfu ;
Tan, Xiaoyao ;
Lin, Ligang ;
Chang, Na ;
Guo, Yugao .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2017, 170 :96-101
[6]   Freezing point osmometry of milk to determine the additional water content -: an issue in general quality control and German food regulation [J].
Buettel, Britta ;
Fuchs, Markus ;
Holz, Birger .
CHEMISTRY CENTRAL JOURNAL, 2008, 2 (1)
[7]   Quantification of cow milk adulteration in goat milk using high-performance liquid chromatography with electrospray ionization mass spectrometry [J].
Chen, RK ;
Chang, LW ;
Chung, YY ;
Lee, MH ;
Ling, YC .
RAPID COMMUNICATIONS IN MASS SPECTROMETRY, 2004, 18 (10) :1167-1171
[8]   Alphas1-casein, milk composition and coagulation properties of goat milk [J].
Clark, S ;
Sherbon, JW .
SMALL RUMINANT RESEARCH, 2000, 38 (02) :123-134
[9]   Quantification of whey in fluid milk using confocal Raman microscopy and artificial neural network [J].
da Rocha, Roney Alves ;
Paiva, Igor Moura ;
Anjos, Virgilio ;
Moreira Furtado, Marco Antonio ;
Valenzuela Bell, Maria Jose .
JOURNAL OF DAIRY SCIENCE, 2015, 98 (06) :3559-3567
[10]   DNA-based approach for species identification of goat-milk products [J].
Di Pinto, Angela ;
Terio, Valentina ;
Marchetti, Patrizia ;
Bottaro, Marilisa ;
Mottola, Anna ;
Bozzo, Giancarlo ;
Bonerba, Elisabetta ;
Ceci, Edmondo ;
Tantillo, Giuseppina .
FOOD CHEMISTRY, 2017, 229 :93-97