Effective detection and quantification of chemical adulterants in model fat-filled milk powders using NIRS and hierarchical modelling strategies

Abstract

Skimmed milk powder can be blended with indigenous vegetable oils to formulate fat-filled milk powder (FMP) to satisfy the growing demand of low-income consumers for dairy proteins in the developing countries where food control systems may be fragmented. Unscrupulous manufacturers may adulterate FMP with melamine or urea to give the false impression that it contains sufficient protein. This study investigated, for the first time, the efficacy of near infrared spectroscopy to detect and quantify melamine and urea (0.01–16.00%) in FMP formulated with 4 different vegetable oils (i.e., coconut, palm, soya-bean and sunflower). Multilevel analyses were able to detect, confirm and differentiate the adulterations with an efficiency ranging from 89.8 to 100.0%. The partial least square regression models yielded satisfactory predictions (R2p ≥0.96, RSR ≤0.19) at adulteration levels ≥1.00%. This study provides appropriate guidelines for cost-efficient screening of FMP products for adulterants to protect public health.