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 ($R_{CV}^2=0.96$ and $RMS{E}_{CV}=5.88 \%$) 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.

The coronavirus disease 2019 (COVID-19) pandemic is a worldwide health anxiety. The rapid dispersion of the infection globally results in unparalleled economic, social, and health impacts. The pathogen that causes COVID-19 is known as a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A fast and low-cost diagnosis method for COVID-19 disease can play an important role in controlling its proliferation. Near-infrared spectroscopy (NIRS) is a quick, non-destructive, non-invasive, and inexpensive technique for profiling the chemical and physical structures of a wide range of samples. Furthermore, the NIRS has the advantage of incorporating the internet of things (IoT) application for the effective control and treatment of the disease. In recent years, a significant advancement in instrumentation and spectral analysis methods has resulted in a remarkable impact on the NIRS applications, especially in the medical discipline. To date, NIRS has been applied as a technique for detecting various viruses including zika (ZIKV), chikungunya (CHIKV), influenza, hepatitis C, dengue (DENV), and human immunodeficiency (HIV). This review aims to outline some historical and contemporary applications of NIRS in virology and its merit as a novel diagnostic technique for SARS-CoV-2.