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Detection and quantification of corn starch and wheat flour as adulterants in milk powder by near- and mid-infrared spectroscopy coupled with chemometric routines

Edwin R. Caballero‐Agosto, Nobel O. Sierra-Vega, Yashira Rolon-Ocasio, Samuel P. Hernández‐Rivera, Ricardo A. Infante-Degró, Miriam Fontalvo Gómez, Leonardo C. Pacheco‐Londoño, Ricardo Infante‐Castillo

2023Food Chemistry Advances27 citationsDOIOpen Access PDF

Abstract

Adulterating foods, such as milk powder (MP), is a common practice in countries with no rigid policy on food quality control. This study employs Fourier transform near-infrared and mid-infrared (FT-NIR, FT-MIR) spectroscopy and chemometric analysis to detect milk powder adulteration with corn starch (CS) and wheat flour (WF) from 0.00 to 30.00% w/w concentrations. Partial least square regression (PLSR) models were developed, optimized, and compared to quantify corn starch and wheat flour adulterations. According to the results, the root mean square error prediction (RMSEP) for FT-NIR and FT-MIR in corn starch was 0.74 and 1.69% w/w and 0.82 and 2.63% w/w for wheat flour, respectively. FT-NIR spectroscopy, rather than FT-MIR coupled with the appropriate chemometrics models represents a more valuable tool for simple, rapid, and nondestructive detection of adulterants in milk powder. The recent availability of portable instruments, combined with suitable chemometric tools, makes it possible to discriminate adulterated food samples in situ.

Topics & Concepts

ChemometricsStarchPartial least squares regressionWheat flourFood scienceCorn starchChemistryFourier transform infrared spectroscopyNear-infrared spectroscopySpectroscopyMathematicsAnalytical Chemistry (journal)Materials scienceChromatographyStatisticsChemical engineeringEngineeringQuantum mechanicsPhysicsSpectroscopy and Chemometric AnalysesIdentification and Quantification in FoodSpectroscopy Techniques in Biomedical and Chemical Research