Revealing the Effect of Heat Treatment on the Spectral Pattern of Unifloral Honeys Using Aquaphotomics.

Zsanett Bodor,Viktoria Zsom-Muha,Balkis Aouadi,Csilla Benedek,Zoltan Kovacs

doi:10.3390/molecules27030780

Abstract

In this study we aimed to investigate the effect of heat treatment on the spectral pattern of honey using near infrared spectroscopy (NIRS). For the research, sunflower, bastard indigo, and acacia honeys were collected from entrusted beekeepers. The honeys were not subject to any treatment before. Samples were treated at 40 °C, 60 °C, 80 °C, and 100 °C for 60, 120, 180, and 240 min. This resulted in 17 levels, including the untreated control samples. The 5-hydroxymethylfurfural (HMF) content of the honeys was determined using the Winkler method. NIRS spectra were recorded using a handheld instrument. Data analysis was performed using ANOVA for the HMF content and multivariate analysis for the NIRS data. For the latter, PCA, PCA-LDA, and PLSR models were built (using the 1300–1600 nm spectral range) and the wavelengths presenting the greatest change induced by the perturbations of temperature and time intervals were collected systematically, based on the difference spectra and the weights of the models. The most contributing wavelengths were used to visualize the spectral pattern changes on the aquagrams in the specific water matrix coordinates. Our results showed that the heat treatment highly contributed to the formation of free or less bonded water, however, the changes in the spectral pattern highly depended on the crystallization phase and the honey type.

Highlights

Honey, as a natural sweetener used since ancient times [1], is a perfect candidate for the increasing demand for unprocessed, natural, and “healthy” products
In the case of the honeys heated to 80 ◦C and 100 ◦C, the samples heat treated for 60 min had significantly lower HMF content compared to honeys heat treated for 120, 180, and 240 min
The aquagrams plotted at the water matrix coordinates for each honey type as predefined based on the subtraction spectra, the PCA loadings of the temperature (Figure 2a) and time visualization models (Figure 2b), as well as the most contributing wavelengths of the previously presented PCA-LDA models (Figure 3a,b) and Partial Least Square Regression (PLSR) regression models (Supplementary Figure S1b,d), are presented in Figure 4, Figure 5, and Figure 6

Summary

Introduction

As a natural sweetener used since ancient times [1], is a perfect candidate for the increasing demand for unprocessed, natural, and “healthy” products. Honey is composed of sugars (95% of the dry matter content [4]), water (

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