Journal
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
Volume 62, Issue 32, Pages 8060-8067Publisher
AMER CHEMICAL SOC
DOI: 10.1021/jf5013727
Keywords
pooled-ANOVA; milk powder; near-infrared spectroscopy; partial least-squares regression; ANOVA-PCA
Funding
- Agricultural Research Service of the U.S. Department of Agriculture
- Office of Dietary Supplements of the National Institutes of Health
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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 (R-2) 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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