School of Physics, Universiti Sains Malaysia, Pulau Pinang 11800, Malaysia.
Aquaphotomics Research Department, Faculty of Agriculture, Kobe University, Kobe 658-8501, Japan.
Molecules. 2022 Apr 3;27(7):2324. doi: 10.3390/molecules27072324.
Honey is a natural product that is considered globally one of the most widely important foods. Various studies on authenticity detection of honey have been fulfilled using visible and near-infrared (Vis-NIR) spectroscopy techniques. However, there are limited studies on stingless bee honey (SBH) despite the increase of market demand for this food product. The objective of this work was to present the potential of Vis-NIR absorbance spectroscopy for profiling, classifying, and quantifying the adulterated SBH. The SBH sample was mixed with various percentages (10−90%) of adulterants, including distilled water, apple cider vinegar, and high fructose syrup. The results showed that the region at 400−1100 nm that is related to the color and water properties of the samples was effective to discriminate and quantify the adulterated SBH. By applying the principal component analysis (PCA) on adulterants and honey samples, the PCA score plot revealed the classification of the adulterants and adulterated SBHs. A partial least squares regression (PLSR) model was developed to quantify the contamination level in the SBH samples. The general PLSR model with the highest coefficient of determination and lowest root means square error of cross-validation (RCV2=0.96 and RMSECV=5.88 %) was acquired. The aquaphotomics analysis of adulteration in SBH with the three adulterants utilizing the short-wavelength NIR region (800−1100 nm) was presented. The structural changes of SBH due to adulteration were described in terms of the changes in the water molecular matrix, and the aquagrams were used to visualize the results. It was revealed that the integration of NIR spectroscopy with aquaphotomics could be used to detect the water molecular structures in the adulterated SBH.
蜂蜜是一种天然产物，被认为是全球最重要的食品之一。已经有许多关于蜂蜜真实性检测的研究使用了可见和近红外（Vis-NIR）光谱技术。然而，尽管市场对这种食品的需求不断增加，对无刺蜜蜂蜂蜜（SBH）的研究却很有限。本工作的目的是展示 Vis-NIR 吸收光谱在分析、分类和定量掺假 SBH 方面的潜力。SBH 样品与各种掺杂物（10-90%）混合，包括蒸馏水、苹果醋和高果糖糖浆。结果表明，与样品颜色和水分特性相关的 400-1100nm 区域可有效区分和定量掺假 SBH。通过对掺杂物和蜂蜜样品进行主成分分析（PCA），PCA 得分图揭示了掺杂物和掺假 SBH 的分类。建立了偏最小二乘回归（PLSR）模型来定量 SBH 样品中的污染水平。具有最高决定系数和最低交叉验证均方根误差（RCV2=0.96 和 RMSECV=5.88%）的通用 PLSR 模型被获得。利用三种掺杂物在短波近红外区域（800-1100nm）对 SBH 掺假进行水敏分析。根据水分子基质的变化描述了 SBH 因掺假而发生的结构变化，并使用水敏图来可视化结果。结果表明，将近红外光谱与水敏分析相结合，可以用于检测掺假 SBH 中的水分子结构。
