molecules-logo

Journal Browser

Journal Browser

Special Issue "Perspectives in Near Infrared Spectroscopy and Related Techniques"

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Analytical Chemistry".

Deadline for manuscript submissions: 31 October 2020.

Special Issue Editors

Prof. Dr. Christian Huck
Website SciProfiles
Guest Editor
Institute of Analytical Chemistry and Radiochemistry, CCB-Center for Chemistry and Biomedicine, Leopold-Franzens University, Innrain 80-82, 6020 Innsbruck, Austria
Interests: vibrational spectroscopy; separation science; enrichment techniques; mass spectrometry
Special Issues and Collections in MDPI journals
Dr. Krzysztof Bec
SciProfiles
Guest Editor
Institute of Analytical Chemistry and Radiochemistry, CCB-Center for Chemistry and Biomedicine, Leopold-Franzens University, Innrain 80-82, 6020 Innsbruck, Austria

Special Issue Information

Dear Colleagues,

Near-infrared (NIR) spectroscopy is one of the most rapidly advancing spectroscopic techniques. Mainly known as an analytical tool useful for sample characterization and content quantification, it is a potent tool used in various other fields, e.g. NIR imaging techniques in biophotonics, medical applications or in characterization of food products. Ongoing miniaturization and simplification of instrumentation brings the technique even to the ordinary consumer. NIR spectroscopy contributes to basic science and physical chemistry as well, e.g. by giving insights into the nature of molecular vibrations or intermolecular interactions. The technique has been developing in conjunction with advanced methods of data analysis; recent years have highlighted the potential in applying computational chemistry for improving interpretability of NIR spectra. However, one may also notice some adverse effects of such popularity. The growing diversity of the methods and applications related to NIR spectroscopy has led to a dispersion of the contributions among disparate scientific communities.

Following the success of the former Special Issue published in Molecules  ‘Advances in Near Infrared Spectroscopy and Related Computational Methods’ (https://www.mdpi.com/journal/molecules/special_issues/infrared_computational) we consider the present Special Issue as the continuation that will be further helpful in bringing together these distinct communities.

The Special Issue aims for reflecting the diversity of methods and applications in NIR spectroscopy. To suit this purpose, it additionally welcomes research topics not directly focused on NIR region, which however remain relevant by employing the methodologies essential for NIR spectroscopy. We believe such scope promotes the exchange of ideas with no artificial limits or strict categorization. We thus hope the Special Issue will create a formidable opportunity for Authors and Readers in pushing the frontier of this discipline of science.

Prof. Dr. Christian Huck
Dr. Krzysztof Bec
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Molecules is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Near-infrared spectroscopy (NIRS)
  • analytical spectroscopy
  • NIR imaging/mapping
  • hyperspectral image processing
  • hand-held/portable spectrometers
  • chemometrics and data analysis
  • theoretical spectroscopy
  • theoretical methods for spectra interpretation

Related Special Issue

Published Papers (6 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Open AccessArticle
A Novel Tool for Visualization of Water Molecular Structure and Its Changes, Expressed on the Scale of Temperature Influence
Molecules 2020, 25(9), 2234; https://doi.org/10.3390/molecules25092234 - 09 May 2020
Cited by 1
Abstract
Aquaphotomics utilizes water-light interaction for in-depth exploration of water, its structure and role in aqueous and biologic systems. The aquagram, a major analytical tool of aquaphotomics, allows comparison of water molecular structures of different samples by comparing their respective absorbance spectral patterns. Temperature [...] Read more.
Aquaphotomics utilizes water-light interaction for in-depth exploration of water, its structure and role in aqueous and biologic systems. The aquagram, a major analytical tool of aquaphotomics, allows comparison of water molecular structures of different samples by comparing their respective absorbance spectral patterns. Temperature is the strongest perturbation of water changing almost all water species. To better interpret and understand spectral patterns, the objective of this work was to develop a novel, temperature-scaled aquagram that provides standardized information about changes in water molecular structure caused by solutes, with its effects translated to those which would have been caused by respective temperature changes. NIR spectra of Milli-Q water in the temperature range of 20–70 °C and aqueous solutions of potassium chloride in concentration range of 1 to 1000 mM were recorded to demonstrate the applicability of the proposed novel tool. The obtained results presented the influence of salt on the water molecular structure expressed as the equivalent effect of temperature in degrees of Celsius. The temperature-based aquagrams showed the well-known structure breaking and structure making effects of salts on water spectral pattern, for the first time presented in the terms of temperature influence on pure water. This new method enables comparison of spectral patterns providing a universal tool for evaluation of various bio-aqueous systems which can provide better insight into the system’s functionality. Full article
(This article belongs to the Special Issue Perspectives in Near Infrared Spectroscopy and Related Techniques)
Show Figures

Graphical abstract

Open AccessArticle
Differentiation of South African Game Meat Using Near-Infrared (NIR) Spectroscopy and Hierarchical Modelling
Molecules 2020, 25(8), 1845; https://doi.org/10.3390/molecules25081845 - 16 Apr 2020
Cited by 1
Abstract
Near-infrared (NIR) spectroscopy, combined with multivariate data analysis techniques, was used to rapidly differentiate between South African game species, irrespective of the treatment (fresh or previously frozen) or the muscle type. These individual classes (fresh; previously frozen; muscle type) were also determined per [...] Read more.
Near-infrared (NIR) spectroscopy, combined with multivariate data analysis techniques, was used to rapidly differentiate between South African game species, irrespective of the treatment (fresh or previously frozen) or the muscle type. These individual classes (fresh; previously frozen; muscle type) were also determined per species, using hierarchical modelling. Spectra were collected with a portable handheld spectrophotometer in the 908–1676-nm range. With partial least squares discriminant analysis models, we could differentiate between the species with accuracies ranging from 89.8%–93.2%. It was also possible to distinguish between fresh and previously frozen meat (90%–100% accuracy). In addition, it was possible to distinguish between ostrich muscles (100%), as well as the forequarters and hindquarters of the zebra (90.3%) and springbok (97.9%) muscles. The results confirm NIR spectroscopy’s potential as a rapid and non-destructive method for species identification, fresh and previously frozen meat differentiation, and muscle type determination. Full article
(This article belongs to the Special Issue Perspectives in Near Infrared Spectroscopy and Related Techniques)
Show Figures

Graphical abstract

Open AccessArticle
Unified Classification of Bacterial Colonies on Different Agar Media Based on Hyperspectral Imaging and Machine Learning
Molecules 2020, 25(8), 1797; https://doi.org/10.3390/molecules25081797 - 14 Apr 2020
Abstract
A universal method by considering different types of culture media can enable convenient classification of bacterial species. The study combined hyperspectral technology and versatile chemometric algorithms to achieve the rapid and non-destructive classification of three kinds of bacterial colonies (Escherichia coli, [...] Read more.
A universal method by considering different types of culture media can enable convenient classification of bacterial species. The study combined hyperspectral technology and versatile chemometric algorithms to achieve the rapid and non-destructive classification of three kinds of bacterial colonies (Escherichia coli, Staphylococcus aureus and Salmonella) cultured on three kinds of agar media (Luria–Bertani agar (LA), plate count agar (PA) and tryptone soy agar (TSA)). Based on the extracted spectral data, partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM) were employed to established classification models. The parameters of SVM models were optimized by comparing genetic algorithm (GA), particle swarm optimization (PSO) and grasshopper optimization algorithm (GOA). The best classification model was GOA-SVM, where the overall correct classification rates (OCCRs) for calibration and prediction of the full-wavelength GOA-SVM model were 99.45% and 98.82%, respectively, and the Kappa coefficient for prediction was 0.98. For further investigation, the CARS, SPA and GA wavelength selection methods were used to establish GOA-SVM simplified model, where CARS-GOA-SVM was optimal in model accuracy and stability with the corresponding OCCRs for calibration and prediction and the Kappa coefficients of 99.45%, 98.73% and 0.98, respectively. The above results demonstrated that it was feasible to classify bacterial colonies on different agar media and the unified model provided a continent and accurate way for bacterial classification. Full article
(This article belongs to the Special Issue Perspectives in Near Infrared Spectroscopy and Related Techniques)
Show Figures

Figure 1

Open AccessArticle
Detection of Sulfite Dioxide Residue on the Surface of Fresh-Cut Potato Slices Using Near-Infrared Hyperspectral Imaging System and Portable Near-Infrared Spectrometer
Molecules 2020, 25(7), 1651; https://doi.org/10.3390/molecules25071651 - 03 Apr 2020
Cited by 1
Abstract
Sodium pyrosulfite is a browning inhibitor used for the storage of fresh-cut potato slices. Excessive use of sodium pyrosulfite can lead to sulfur dioxide residue, which is harmful for the human body. The sulfur dioxide residue on the surface of fresh-cut potato slices [...] Read more.
Sodium pyrosulfite is a browning inhibitor used for the storage of fresh-cut potato slices. Excessive use of sodium pyrosulfite can lead to sulfur dioxide residue, which is harmful for the human body. The sulfur dioxide residue on the surface of fresh-cut potato slices immersed in different concentrations of sodium pyrosulfite solution was classified by near-infrared hyperspectral imaging (NIR-HSI) system and portable near-infrared (NIR) spectrometer. Principal component analysis was used to analyze the object-wise spectra, and support vector machine (SVM) model was established. The classification accuracy of calibration set and prediction set were 98.75% and 95%, respectively. Savitzky–Golay algorithm was used to recognize the important wavelengths, and SVM model was established based on the recognized important wavelengths. The final classification accuracy was slightly less than that based on the full spectra. In addition, the pixel-wise spectra extracted from NIR-HSI system could realize the visualization of different samples, and intuitively reflect the differences among the samples. The results showed that it was feasible to classify the sulfur dioxide residue on the surface of fresh-cut potato slices immersed in different concentration of sodium pyrosulfite solution by NIR spectra. It provided an alternative method for the detection of sulfur dioxide residue on the surface of fresh-cut potato slices. Full article
(This article belongs to the Special Issue Perspectives in Near Infrared Spectroscopy and Related Techniques)
Show Figures

Figure 1

Open AccessArticle
Discrimination of Gentiana and Its Related Species Using IR Spectroscopy Combined with Feature Selection and Stacked Generalization
Molecules 2020, 25(6), 1442; https://doi.org/10.3390/molecules25061442 - 23 Mar 2020
Cited by 1
Abstract
Gentiana, which is one of the largest genera of Gentianoideae, most of which had potential pharmaceutical value, and applied to local traditional medical treatment. Because of the phytochemical diversity and difference of bioactive compounds among species, which makes it crucial to accurately [...] Read more.
Gentiana, which is one of the largest genera of Gentianoideae, most of which had potential pharmaceutical value, and applied to local traditional medical treatment. Because of the phytochemical diversity and difference of bioactive compounds among species, which makes it crucial to accurately identify authentic Gentiana species. In this paper, the feasibility of using the infrared spectroscopy technique combined with chemometrics analysis to identify Gentiana and its related species was studied. A total of 180 batches of raw spectral fingerprints were obtained from 18 species of Gentiana and Tripterospermum by near-infrared (NIR: 10,000–4000 cm−1) and Fourier transform mid-infrared (MIR: 4000–600 cm−1) spectrum. Firstly, principal component analysis (PCA) was utilized to explore the natural grouping of the 180 samples. Secondly, random forests (RF), support vector machine (SVM), and K-nearest neighbors (KNN) models were built while using full spectra (including 1487 NIR variables and 1214 FT-MIR variables, respectively). The MIR-SVM model had a higher classification accuracy rate than the other models that were based on the results of the calibration sets and prediction sets. The five feature selection strategies, VIP (variable importance in the projection), Boruta, GARF (genetic algorithm combined with random forest), GASVM (genetic algorithm combined with support vector machine), and Venn diagram calculation, were used to reduce the dimensions of the data variable in order to further reduce numbers of variables for modeling. Finally, 101 NIR and 73 FT-MIR bands were selected as the feature variables, respectively. Thirdly, stacking models were built based on the optimal spectral dataset. Most of the stacking models performed better than the full spectra-based models. RF and SVM (as base learners), combined with the SVM meta-classifier, was the optimal stacked generalization strategy. For the SG-Ven-MIR-SVM model, the accuracy (ACC) of the calibration set and validation set were both 100%. Sensitivity (SE), specificity (SP), efficiency (EFF), Matthews correlation coefficient (MCC), and Cohen’s kappa coefficient (K) were all 1, which showed that the model had the optimal authenticity identification performance. Those parameters indicated that stacked generalization combined with feature selection is probably an important technique for improving the classification model predictive accuracy and avoid overfitting. The study result can provide a valuable reference for the safety and effectiveness of the clinical application of medicinal Gentiana. Full article
(This article belongs to the Special Issue Perspectives in Near Infrared Spectroscopy and Related Techniques)
Show Figures

Figure 1

Open AccessArticle
Investigation of a Medical Plant for Hepatic Diseases with Secoiridoids Using HPLC and FT-IR Spectroscopy for a Case of Gentiana rigescens
Molecules 2020, 25(5), 1219; https://doi.org/10.3390/molecules25051219 - 09 Mar 2020
Cited by 1
Abstract
Secoiridoids could be used as a potential new drug for the treatment of hepatic disease. The content of secoiridoids of G. rigescens varied in different geographical origins and parts. In this study, a total of 783 samples collected from different parts of G. [...] Read more.
Secoiridoids could be used as a potential new drug for the treatment of hepatic disease. The content of secoiridoids of G. rigescens varied in different geographical origins and parts. In this study, a total of 783 samples collected from different parts of G. rigescens in Yunnan, Sichuan, and Guizhou Provinces. The content of secoiridoids including gentiopicroside, swertiamarin, and sweroside were determined by using HPLC and analyzed by one-way analysis of variance. Two selected variables including direct selected and variable importance in projection combined with partial least squares regression have been used to establish a method for the determination of secoiridoids using FT-IR spectroscopy. In addition, different pretreatments including multiplicative scatter correction (MSC), standard normal variate (SNV), first derivative and second derivative (SD), and orthogonal signal correction (OSC) were compared. The results indicated that the sample (root, stem, and leaf) with total secoiridoids, gentiopicroside, swertiamarin, and sweroside from west Yunnan had higher content than samples from the other regions. The sample from Baoshan had more total secoiridoids than other samples for the whole medicinal plant. The best performance using FT-IR for the total secoiridoid was with the direct selected variable method involving pretreatment of MSC+OSC+SD in the root and stem, while in leaf, of the best method involved using original data with MSC+OSC+SD. This method could be used to determine the bioactive compounds quickly for herbal medicines. Full article
(This article belongs to the Special Issue Perspectives in Near Infrared Spectroscopy and Related Techniques)
Show Figures

Figure 1

Back to TopTop