Detection of adulteration in honey by infrared spectroscopy and chemometrics: Effect on human health

Abstract

The geographical nature of Lebanon allows beekeepers to produce distinctive honey, which is amongst the most expensive in the world, and representing serious competition for foreign honey producers. The increased demand of consumers and the economic crisis are exacerbating fraudulent honey production, particularly sugar addition, which affect negatively its health benefits. In this study, infrared spectroscopy coupled with chemometrics was used to test honey authenticity, as a promising alternative quick, and cost‐efficient method. Six authentic Lebanese honey and 18 samples intentionally doped with 10%, 30%, and 50% of glucose, fructose, sucrose, and high syrup fructose corn syrup (HFCS), were analyzed by near and mid‐infrared (MIR) spectroscopy. Spectral data were processed using Principal Component Analysis. The results allowed for the classification of the samples in function of the adulterant sugars and made it able to define bands that are attributes of these sugars as well as a detection limit which fluctuates around 10%. It was also highlighted the advantage of the MIR over the near‐infrared, especially for fructose and HFCS adulteration. Novelty impact statement Infrared spectroscopy coupled with chemometrics was proven to be a promising tool for testing honey authenticity as it is perceived to be a quick, reliable, non‐polluting, and cost‐efficient method. The application of the Principal Components Analysis (PCA) on Mid and Near‐Infrared data can detect the adulteration of honey with respect to four adulterant sugars: glucose, fructose, sucrose, and high syrup fructose corn syrup. The results of PCA allowed for the classification of the samples in the function of the adulterant sugars and made it able to define bands that are attributes of these sugars with a detection limit of around 10%.

Rapid Detection of Thermal Treatment of Honey by Chemometrics-Assisted FTIR Spectroscopy

“…Moreover, PCA is the most promising tool to detect the adulteration of honey with respect to different adulterant sugars: glucose, fructose, sucrose, etc. [11,27]. From the figure it is evident that the composition of each honey is very different, moreover, the composition of eucalyptus honey changes a lot during the heating.…”

“…Commercial processing of honey is usually accompanied by filtering and heating in order to purify, filter, facilitate packaging, to inhibit microorganism growth, reduce moisture content to standard level, and to delay the crystallization process [7,8]. In earlier studies, Fourier-transform infrared (FTIR) spectroscopy was used with chemometrics to categorize honey and detect hydroxymethylfurfural (HMF) level and diastase activity [9][10][11]. Raw honey, containing more than 20% moisture, is easy to ferment, independent of the initial yeast count that affects the honey quality and shelf life [12].…”

Rapid analysis technologies with chemometrics for food authenticity field: A review

“…Syrup added to samples as an adulterant was also accurately identified. MIR recognized four types of adulterated syrups in honey (glucose, fructose, sucrose, and high syrup fructose corn syrup)with detection limits as low as 10% ( Skaff et al, 2022 ). The combination of MIR and K-nearest neighbor (KNN) identified syrup or water in Guava pulp with 100% classification accuracy ( Alamar et al, 2020 ).…”

Siamese network‐based computer vision approach to detect papaya seed adulteration in black peppercorns

“…Detecting adulterants in spices and herbs has involved chemical and physical separations, like spectroscopic methods, conventional optical microscopy (Toci et al., 2016), High‐Performance Liquid Chromatography (HPLC) (Song et al., 2019), chemometrics (Kucharska‐Ambrożej & Karpinska, 2020), figure‐printing techniques, and other screening tools. The easy to implement, green, and fast screening technique used is infrared spectroscopy (Skaff et al., 2021), keeping conventional microscopy as the reference method. Microscopy and Fourier‐transform infrared spectroscopy in mapping mode, in combination with Principle Component Analysis, was employed to get a one‐class, untargeted method formed on the spatial distribution of black pepper molecular structure and detects a wide range of mineral and organic adulterants in black pepper (Lafeuille et al., 2019).…”