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Characterization of Near-Infrared Spectral Variance in the Authentication of Skim and Nonfat Dry Milk Powder Collection Using ANOVA-PCA, Pooled-ANOVA, and Partial Least-Squares Regression
Author(s) -
James M. Harnly,
Peter de B. Harrington,
Lucy Botros,
Joseph E. Jablonski,
Claire Chang,
Marti Mamula Bergana,
Paul Wehling,
Gerard Downey,
Alan R. Potts,
Jeffrey C. Moore
Publication year - 2014
Publication title -
journal of agricultural and food chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.203
H-Index - 297
eISSN - 1520-5118
pISSN - 0021-8561
DOI - 10.1021/jf5013727
Subject(s) - partial least squares regression , analysis of variance , mathematics , principal component analysis , zoology , one way analysis of variance , linear regression , coefficient of variation , food science , interaction , statistics , coefficient of determination , regression analysis , chemistry , biology
Forty-one samples of skim milk powder (SMP) and nonfat dry milk (NFDM) from 8 suppliers, 13 production sites, and 3 processing temperatures were analyzed by NIR diffuse reflectance spectrometry over a period of 3 days. NIR reflectance spectra (1700-2500 nm) were converted to pseudoabsorbance and examined using (a) analysis of variance-principal component analysis (ANOVA-PCA), (b) pooled-ANOVA based on data submatrices, and (c) partial least-squares regression (PLSR) coupled with pooled-ANOVA. ANOVA-PCA score plots showed clear separation of the samples with respect to milk class (SMP or NFDM), day of analysis, production site, processing temperature, and individual samples. Pooled-ANOVA provided statistical levels of significance for the separation of the averages, some of which were many orders of magnitude below 10⁻³. PLSR showed that the correlation with Certificate of Analysis (COA) concentrations varied from a weak coefficient of determination (R²) of 0.32 for moisture to moderate R² values of 0.61 for fat and 0.78 for protein for this multinational study. In this study, pooled-ANOVA was applied for the first time to PLS modeling and demonstrated that even though the calibration models may not be precise, the contribution of the protein peaks in the NIR spectra accounted for the largest proportion of the variation despite the inherent imprecision of the COA values.

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