Near-infrared spectroscopy with chemometrics for identification and quantification of adulteration in high-quality stingless bee honey

Abstract

This study presents a simple, rapid, and non-destructive approach of combining near-infrared spectroscopy (NIRS) with chemometrics for the evaluation of adulteration levels in stingless bee honey (SBH). Three high-quality SBH samples were directly obtained from the northern part of Malaysia and then adulterated with water (W) and apple cider vinegar (AC) at an adulteration range of 4.76%–50%. The NIRS analysis was performed at the spectral region of 700–1100 ​nm. The chemometric tools used include principal component analysis (PCA), hierarchical cluster analysis (HCA), principal component analysis-linear discriminant analysis (PCA-LDA), and partial least squares regression (PLSR). Using the first three principal components (PCs) with a total of 97.95% of explained variance, a complete distinction between adulterants, pure, and adulterated samples was achieved. PCA-LDA model with 100% classification accuracy in prediction was able to discriminate each SBH adulterated with W and AC. A general PLSR model to quantify the level of adulteration was developed. The best prediction model used 7 factors with a high correlation coefficient ‘R’ and low root mean square error of prediction ‘RMSEP’ (RP ​= ​0.995 and RMSEP ​= ​1.350%). These results confirm the combined ability of NIRS at region 700–1100 ​nm and chemometrics to effectively discriminate and quantify adulterated SBHs.