Use of Fourier transform infrared spectroscopy and multi-variant analysis for detection of butter adulteration with vegetable oil

Abstract

ABSTRACTDuring butter manufacturing, adulteration of animal and plant fats is one of the major issues in dairy industries. In dairy products, there is a huge potential in spectroscopic techniques such as Fourier transform infrared spectroscopy (FTIR) for the rapid determination of various adulterants. These spectroscopic techniques are reliable, rapid, and accurate as compared to traditional methods. Therefore, the aim of this study was to measure the potential of FTIR spectroscopy along with mathematical modeling for the detection of vegetable oil in butter samples. In this study, different levels of vegetable oil were added to the butter. FTIR spectra of different samples were collected and processed using principal component analysis (PCA) as well as partial least square (PLS) regression. PCA results postulated that 98% of the total variance was accounted by the first two principal components (PC) with a predominance of PC 1 (85%). PLS regression analysis showed values of R2 for calibration as 0.95 and R2 for validation as 0.90 which described good prediction efficiency of vegetable oil adulteration through FTIR data. The present work summarized that Fourier transform infrared spectroscopy along with multivariate analysis can be used to measure the adulteration in butter.

Keywords

• Butter adulteration
• FTIR spectroscopy
• Multivariate analysis
• PCA
• PLS regression