Fusion of electronic tongue and NIRS for the detection of heat treatment of honey

Abstract

Honey is frequently heated during processing/packaging, often in an undeclared manner, leading to consumer misleading. Heating can induce undesirable changes above 50 °C, however, detection is not always simple, especially after exposition to lower temperatures or time periods. The aim of this study was to compare the applicability of near infrared spectroscopy (NIRS), electronic tongue (ET), and their fusion for the detection of heat treatment of honey. Acacia, sunflower and false indigo honeys were heated at 40, 60, 80 or 100 °C for 60, 120, 180 or 240 min. Physicochemical characteristics, color and melissopalynological analyses along with NIRS and ET measurements were performed. Principal component analysis coupled with linear discriminant analysis (PCA-LDA) was applied for the classification of temperature, time and heat treatment level discriminations individually and using a low-level data fusion of ET and NIRS data. Results of ET and NIRS provided good results for the discrimination of the heated samples from the controls, however overlapping occurred for higher heat treatment levels. The model of the fused dataset provided >98% average correct classification of the models and 100% correct classification of the control honeys. Fusion of these methods has a potential in the detection of low-level heat treatment of honey.