4.4 Article

APPLICATION OF FT-RAMAN SPECTROSCOPY AND CHEMOMETRIC ANALYSIS FOR DETERMINATION OF ADULTERATION IN MILK POWDER

Journal

ANALYTICAL LETTERS
Volume 45, Issue 17, Pages 2589-2602

Publisher

TAYLOR & FRANCIS INC
DOI: 10.1080/00032719.2012.698672

Keywords

Adulteration; Milk powder; Partial least square; Raman; Starch; Whey

Funding

  1. CNPq
  2. FAPEMIG
  3. CAPES
  4. FINEP

Ask authors/readers for more resources

In this work, FT-Raman spectroscopy is explored as a rapid technique for the assessment of the milk powder quality. Based on information provided by Raman spectra of samples adulterated with starch and whey, a quantitative method is developed to identify the fraud, using Partial Least Squares regression (PLS). In regression models using PLS the results are satisfactory, and such models can be used to identify and quantify samples presenting whey and starch in milk powder at concentrations of 2.32% and 1.64% (w/w), respectively. In the whey determination, the obtained values in the PLS model of the new samples are compared with those obtained by the spectrophotometric method of acid ninhydrin. This result shows that there is no significant difference with the 95% level of confidence between the values provided by the PLS regression method and the acid ninhydrin. The present work shows Raman spectroscopy as an analytical tool which can be used in quality control of milk powder, even in fraud processes, and the calculated figures of merit such as sensitivity, accuracy, limit of detection and limit of quantification clearly demonstrate this potential use. Although the multivariate models developed are not strictly quantitative, especially for low concentrations, they can be used as screening methods for routine analysis, as showed by this work.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.4
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available