Mineral traditional Chinese medicines (TCMs) are natural minerals, mineral processing products, and some fossils of animals or animal bones that can be used as medicines. Mineral TCMs are a characteristic part of TCMs and play a unique role in the development of TCMs. Mineral TCMs are usually identified according to their morphological properties such as shape, color, or smell, but it is difficult to separate TCMs that are similar in appearance or smell. In this study, the feasibility of using Raman spectroscopy combined with support vector machine (SVM) for rapid identification of nine easily confused mineral TCMs, i.e., borax, gypsum fibrosum, natrii sulfas exsiccatus, natrii sulfas, alumen, sal ammoniac, quartz, calcite, and yellow croaker otolith, was investigated. Initially, two methods, characteristic intensity data extraction and principal component analysis (PCA), were performed to reduce the dimensionality of spectral data. The identification model was subsequently built by the SVM algorithm. The 3-fold cross validation (3-CV) accuracy of the SVM model established based on extracting characteristic intensity data from spectra pretreated by first derivation was 98.61&#x0025;, and the prediction accuracies of the training set and validation set were 100&#x0025;. As for the PCA-SVM model, when the spectra pretreated by vector normalization and the number of principal components (NPC) is 7, the 3-CV accuracy and prediction accuracies all reached 100&#x0025;. Both models have good performance and strong prediction capacity. These results demonstrate that Raman spectroscopy combined with a powerful SVM algorithm has great potential for providing an effective and accurate identification method for mineral TCMs.

Jing Ming

Long Chen

Yan Cao

Chi Yu

Bi-Sheng Huang

Ke-Li Chen

Rapid Identification of Nine Easily Confused Mineral Traditional Chinese Medicines Using Raman Spectroscopy Based on Support Vector Machine

Fourier transform infrared (FTIR) spectroscopy has been advocating a promising alternative for Karl Fischer titration method for quantification of moisture in oil. This study aims to integrate partial least squares regression (PLSR) approach on FTIR spectra for prediction of moisture in locally accessible transformer oil and lubricating oil. The oil samples spiked with known moisture concentrations were extracted with acetonitrile and subjected to analysis with an FTIR spectrophotometer. The PLSR model was built based on 100 training/test splits, and the prediction performance was measured with the percentage root mean squares error (&#x0025; RMSE). The range of concentration studied was between 0 and 5000&#x2009;ppm. The marker region of moisture was found at 3750&#x2013;3400 and 1700&#x2013;1600&#x2009;cm&#x2212;1 with the latter demonstrating a better predictive ability in both lubricating oil and transformer oil. The prediction of moisture in lubricating oil was characterized with lower &#x0025; RMSE. At concentration less than 700&#x2009;ppm, the prediction accuracy deteriorates suggesting poor sensitivity. The PLSR was implemented on IR spectra of a set of blind samples, verified with Karl Fischer (for transformer oil) method and Kittiwake (for lubricating oil) method. The prediction was encouraging at concentrations above 1000&#x2009;ppm; at lower concentrations, the prediction was characterized with high percent error. The algorithm, validated with 100 training/test splits, was converted into an executable program for prediction of moisture based on FTIR spectra. This program can be used for prediction of other substances given that the marker region is identified. FTIR can be used for prediction of moisture in oil nevertheless the sensitivity and precision is low for samples with low moisture concentration.

Siong Fong Sim

Amelia Laccy Jeffrey Kimura

Partial Least Squares (PLS) Integrated Fourier Transform Infrared (FTIR) Approach for Prediction of Moisture in Transformer Oil and Lubricating Oil

In this review, the application of the photoacustic spectroscopy (PAS) is presented as an option to evaluate the quality of food. This technique is a type of spectroscopy based on photothermal phenomena, which allow spectroscopic studies. According to the literature review, it was found that its application is increasing in several countries. Spectroscopic studies carried out by employing PAS in the food industry include, among others, fruit, vegetables, condiments, grains, legumes, flours, &#x201c;tortillas,&#x201d; milk, water, eggs, etc. Additionally, this technique has been used to evaluate adulterated, irradiated, and contaminated food and so on. The literature review has shown the applicability of PAS to one of the problems of the real world, i.e., food quality assessment. Therefore, PAS can contribute in the future with a wide potential for new applications in the food agroindustry.

Claudia Hern&#xe1;ndez-Aguilar

Arturo Dom&#xed;nguez-Pacheco

Alfredo Cruz-Orea

Rumen Ivanov

Photoacoustic Spectroscopy in the Optical Characterization of Foodstuff: A Review

Endodontic persistent infections are often mediated by bacterial biofilms. This mode of bacterial growth is characterized by the presence of a matrix mainly composed of extracellular polymeric substances (EPSs) that protect the encased microorganisms. To establish better control and disinfection protocols, elucidation of the main components of biofilm matrices present in endodontic infections is required. The aim of the present study was to characterize the principal components of E. faecalis, A. naeslundii, and dual-species biofilm matrices by means of Raman spectroscopy and confocal scanning laser microscopy (CSLM) techniques. The total biomass of biofilms was quantified via crystal violet assays, and the monospecies biofilms showed higher biomass than the dual-species biofilms. Raman spectroscopy and confocal laser scanning microscopy were used to identify the biochemical composition and structure of the biofilm matrices. Spectra originating from the biofilms of two endodontic pathogens show the presence of carbohydrates, proteins, fatty acids, and nucleic acids in all samples; however, variation in the levels of expression of these biomolecules allows spectroscopic differentiation of the biofilms using principal component analysis. This study is the first attempt to identify the composition of monospecies and dual-species biofilms of endodontic origin. Our data provides an important approach to the understanding of molecular dynamics of endodontic infections.

Tatiana Ramirez-Mora

Claudia D&#xe1;vila-P&#xe9;rez

Fernando Torres-M&#xe9;ndez

Grettel Valle-Bourrouet

Raman Spectroscopic Characterization of Endodontic Biofilm Matrices

Tea is known to be one of the most popular beverages enjoyed by two-thirds of the world&#x2019;s population. Concern of variability in tea quality is increasing among consumers. It is of great significance to control quality for commercialized tea products. As a rapid, noninvasive, and nondestructive instrumental technique with simplicity in sample preparation, near-infrared reflectance (NIR) spectroscopy has been proved to be one of the most advanced and efficient tools for the control quality of tea products in recent years. In this article, we review the most recent advances and applications of NIR spectroscopy and chemometrics for the quality control of tea, including the measurement of chemical compositions, the evaluation of sensory attributes, the identification of categories and varieties, and the discrimination of geographical origins. Besides, challenges and future trends of tea quality control by NIR spectroscopy are also presented.

Ming-Zhi Zhu

Beibei Wen

Hao Wu

Juan Li

Haiyan Lin

Qin Li

Yinhua Li

Jianan Huang

Zhonghua Liu

The Quality Control of Tea by Near-Infrared Reflectance (NIR) Spectroscopy and Chemometrics

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Journal of Spectroscopy publishes research into the theory and application of spectroscopy across all disciplines, including biology, chemistry, engineering, earth sciences, medicine, materials science, physics, and space science.

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Chief Editor&nbsp;Dr Daniel Cozzolino&nbsp;is based at the University of Queensland, Australia. His research focuses on the developments of chemometric and spectroscopic methods for use in agriculture and food applications.

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Journal of Spectroscopy - Table of contents 2019

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Journal of Spectroscopy publishes research into the theory and application of spectroscopy across all disciplines, including biology, chemistry, engineering, earth sciences, medicine, materials science, physics, and space science.

Journal of Spectroscopy