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Spectroscopic Techniques for Chemical Analysis

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A special issue of Chemosensors (ISSN 2227-9040). This special issue belongs to the section "Analytical Methods, Instrumentation and Miniaturization".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 7209

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Special Issue Editors

Dr. Leiming Yuan

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Guest Editor

College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou 325035, China
Interests: spectral analysis technology; machine learning; nondestructive testing; photoelectric sensing and its applications

Dr. Quansheng Chen

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Guest Editor

College of Ocean Food and Biological Engineering, Jimei University, Xiamen 361021, China
Interests: research on the rapid non-destructive determination of food and agricultural products; research on the nanobiosensor detection of food safety; research on the on-line monitoring technology of food processing

Special Issue Information

Dear Colleagues,

We are excited to announce a Special Issue on "Spectroscopic Techniques for Chemical Analysis". As the demand rises for rapid food quality control and safety, the need for rapid analysis methods is growing exponentially. Spectroscopic methods, such as UV, visible, NIR, MIR, and Raman spectroscopy, can quickly detect contaminants, assess fruit quality and nutrition, and ensure products meet standards, thus realizing gradation and boosting consumer confidence. Spectroscopic techniques, paired with machine learning or deep learning, provide a promising, rapid, non-destructive way to obtain accurate chemical fingerprints of food and agricultural products and other daily consumption goods.

This Special Issue aims to present novel advances in the broad field of spectroscopic analysis, from farm to fork, covering all aspects of edible food quality, monitoring, and improvement. It involves spectroscopic studies of nutritional, sensory, sanitary, and technological properties. New advances made in the laboratory, novel strategies for spectroscopic edible food analysis in farm or food processing, and inventive chemometrics and multi-variate and statistical data analysis approaches are strongly welcomed. In this Special Issue, we aim to publish original research results and review papers.

Dr. Leiming Yuan
Dr. Quansheng Chen
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 submissions that pass pre-check are 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. Chemosensors is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

spectroscopic techniques
chemometrics
machine/deep learning
chemical composition analysis
UV/VIS/NIR/MID spectroscopy
raman spectroscopy
quality control and safety
edible food
daily consumption of goods
non-destrucitve determination

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Published Papers (8 papers)

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Research

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17 pages, 2793 KB

Open AccessArticle

Full-Spectrum LED-Driven Underwater Spectral Detection System and Its Applications

by Yunfei Li, Jun Wei, Shaohua Cheng, Tao Yu, Hong Zhao, Guancheng Li and Fuhong Cai

Chemosensors 2025, 13(10), 359; https://doi.org/10.3390/chemosensors13100359 - 1 Oct 2025

Viewed by 376

Abstract

Spectral detection technology offers non-destructive, in situ, and high-speed capabilities, making it widely applicable for detecting biological and chemical samples and quantifying their concentrations. Water resources, essential to life on Earth, are widely distributed across the planet. The application of spectral technology to underwater environments is useful for wide-area water resource monitoring. Although spectral detection technology is well-established, its underwater application presents challenges, including waterproof housing design, power supply, and data transmission, which limit widespread application of underwater spectral detection. Furthermore, underwater spectral detection necessitates the development of compatible computational methods for sample classification or regression analysis. Focusing on underwater spectral detection, this work involved the construction of a suitable hardware system. A compact spectrometer and LEDs (400 nm–800 nm) were employed as the detection and light source modules, respectively, resulting in a compact system architecture. Extensive tests confirmed that the miniaturized design-maintained system performance. Further, this study addressed the estimation of total phosphorus (TP) concentration in water using spectral data. Samples with varying TP concentrations were prepared and calibrated against standard detection instruments. Subsequently, classification algorithms applied to the acquired spectral data enabled the in situ underwater determination of TP concentration in these samples. This work demonstrates the feasibility of underwater spectral detection for future in situ, high-speed monitoring of aquatic biochemical indicators. In the future, after adding UV LED light source, more water quality parameter information can be obtained. Full article

(This article belongs to the Special Issue Spectroscopic Techniques for Chemical Analysis)

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19 pages, 4940 KB

Open AccessArticle

Unraveling Seasonal Dynamics of Dissolved Organic Matter in Agricultural Ditches Using UV-Vis Absorption and Excitation–Emission Matrix (EEM) Fluorescence Spectroscopy

by Keyan Li, Jinfeng Ge, Qiaozhuan Hu, Wenrui Yao, Xiaoli Fu, Chao Ma and Yulin Qi

Chemosensors 2025, 13(9), 346; https://doi.org/10.3390/chemosensors13090346 - 10 Sep 2025

Viewed by 600

Abstract

Seasonal dynamics of dissolved organic matter (DOM) in agricultural ditches significantly impact carbon cycling and water quality in connected rivers. This study aimed to characterize seasonal variations in DOM composition and dynamics within hierarchical agricultural ditch systems in Tianjin, northern China. Surface water samples were collected from river channels, main ditches, branch ditches, lateral ditches, and field ditches during wet (June 2021) and dry (December 2021) seasons. DOM characteristics were analyzed using dissolved organic carbon (DOC) quantification, ultraviolet-visible (UV-Vis) absorption spectroscopy, and three-dimensional excitation–emission matrix spectroscopy (3D-EEMs) coupled with parallel factor analysis (PARAFAC). The concentration of DOC in ditch surface water exhibited significant seasonal variations, with significantly higher levels observed during the wet season (Huangzhuang: 6.72 ± 0.7 mg/L; Weixing: 13.15 ± 3.1 mg/L) compared to the dry season (Huangzhuang: 5.93 ± 0.3 mg/L; Weixing: 9.35 ± 2.6 mg/L). Both UV-Vis spectral and EEM-PARAFAC analysis revealed that DOM in ditch systems was predominantly composed of fulvic-like and tryptophan-like components, representing the portion of organic matter in water bodies that is highly biologically active, highly mobile, relatively “fresh”, or “not fully humified”. PARAFAC identified microbial humic-like (C1: wet season 40.36%, dry season 34.42%) and protein-like (C3: wet season 40.3%, dry season 49.87%) components as dominant. DOM sources were influenced by dual inputs from terrestrial and autochthonous origins during the wet season, while primarily deriving from autochthonous sources in the dry season. This study elucidates the advances of spectroscopic techniques in deciphering the composition, sources, and influencing factors of DOM in aquatic systems. The findings support implementing riparian buffer strips and optimized fertilizer management to mitigate seasonal peaks of bioavailable DOM in agricultural ditch systems. Full article

(This article belongs to the Special Issue Spectroscopic Techniques for Chemical Analysis)

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14 pages, 1443 KB

Open AccessArticle

Mid-Infrared Spectroscopy with Variable Selection for the Rapid Quantification of Amylose Content in Starch

by Jingyue Qiao, Hongwei Wang, Jianing Bai, Yimin Liu, Xiaocheng Liu, Yanyan Zhang and Leiming Yuan

Chemosensors 2025, 13(8), 287; https://doi.org/10.3390/chemosensors13080287 - 4 Aug 2025

Viewed by 602

Abstract

Amylose content significantly influences the technological, quality, and nutritional properties of starchy foods. This study developed a rapid, non-destructive method to quantify amylose content in starch using mid-infrared (MIR) spectroscopy combined with chemometric techniques. Manually prepared starch mixtures with varying amylose levels were scanned to obtain MIR spectra, which were preprocessed using smoothing and z-score normalization to reduce operational variability. Three variable selection methods, including bootstrap soft shrinkage (BOSS), competitive adaptive reweighted sampling (CARS), and uninformative variable elimination (UVE), were applied to select the useful spectra. A partial least square (PLS) model was then constructed to correlate selected spectral data with amylose content. The results revealed that the number and position of selected variables differed across different optimization methods, which influenced the model’s performance. It is worth noting that the optimized PLS model significantly reduced the root mean squared error of cross-validation (RMSECV) and improved prediction accuracy in 50 runs. In particular, the CARS-PLS model showed superior performance, achieving a correlation coefficient (R_p) of 0.964 and a root mean squared error of prediction (RMSEP) of 4.59, a 60% improvement over the original PLS model, which had an RMSEP of 11.56. These results highlight MIR spectroscopy’s potential, combined with optimized chemometric models, for accurate amylose quantification in food quality control. Full article

(This article belongs to the Special Issue Spectroscopic Techniques for Chemical Analysis)

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16 pages, 2901 KB

Open AccessArticle

SiO₂-Al₂O₃-ZrO₂-Ag Composite and Its Signal Enhancement Capacity on Raman Spectroscopy

by Jesús Alberto Garibay-Alvarado, Pedro Pizá-Ruiz, Armando Erasto Zaragoza-Contreras, Francisco Espinosa-Magaña and Simón Yobanny Reyes-López

Chemosensors 2025, 13(7), 266; https://doi.org/10.3390/chemosensors13070266 - 21 Jul 2025

Viewed by 559

Abstract

A ceramic–metal composite was synthesized using sol–gel and electrospinning methods to serve as a SERS substrate. The precursors used were tetraethyl orthosilicate, aluminum nitrate, and zirconium, and polyvinylpyrrolidone was added to electrospun nonwoven fibrous membranes. The membranes were sintered, decorated with silver nanoparticles. The enhancement substrates were made of fibers of cylindric morphology with an average diameter of approximately 190 nm, a smooth surface, and 9 nm spherical particles decorating the surface of the fibers. The enhancement capacity of the substrates was tested using pyridine, methyl orange, methylene blue, crystal violet, and Eriochrome black T at different concentrations with Raman spectroscopy to determine whether the size and complexity of the analyte has an impact on the enhancement capacity. Enhancement factors of 2.53 × 10², 3.06 × 10¹, 2.97 × 10³, 4.66 × 10³, and 1.45 × 10³ times were obtained for the signal of pyridine, methyl orange, methylene blue, crystal violet, and Eriochrome black T at concentrations of 1 nM. Full article

(This article belongs to the Special Issue Spectroscopic Techniques for Chemical Analysis)

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17 pages, 2940 KB

Open AccessArticle

Evaluation Methods for Stability and Analysis of Underlying Causes of Instability in Form I Atorvastatin Calcium Drug Substance

by Bo Chen, Zhilong Tang, Zhenxing Zhu, Yang Xiao, Guangyao Mei and Xingchu Gong

Chemosensors 2025, 13(7), 265; https://doi.org/10.3390/chemosensors13070265 - 21 Jul 2025

Viewed by 691

Abstract

Stability assessments of drug substances and the detection of crystalline forms are critical for ensuring drug quality and medication safety. Atorvastatin calcium drug substance samples were characterized using powder X-ray diffraction (PXRD) and differential scanning calorimetry (DSC). DSC results demonstrated a precise discrimination of the stability of samples. An analysis of PXRD characteristic peaks and DSC melting data suggested that instability likely stems from the presence of the amorphous phase. To validate this hypothesis, blended samples containing controlled ratios of amorphous phase and crystalline Form I were prepared. Quantitative models based on PXRD, DSC, and near-infrared spectroscopy (NIRS) data were developed to predict amorphous content, and classification accuracy was evaluated. Experimental results confirmed that all three models achieved classification accuracy values exceeding 70% in the stability prediction of the two groups of samples, which included “stable” and “unstable” samples, substantiating the hypothesis. Among them, the modeling method based on NIRS data was not only non-destructive and rapid but also demonstrates a superior discrimination accuracy value reaching 100% (n = 11), showing potential for promotion and application in industrial sample detection. The quantitative correlation between amorphous content and stability was successfully established in this study, offering a novel method for a quality stability assessment of atorvastatin calcium drug substances. Full article

(This article belongs to the Special Issue Spectroscopic Techniques for Chemical Analysis)

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15 pages, 2463 KB

Open AccessArticle

Measurement of the Effective Refractive Index of Suspensions Containing 5 µm Diameter Spherical Polystyrene Microparticles by Surface Plasmon Resonance and Scattering

by Osvaldo Rodríguez-Quiroz, Donato Luna-Moreno, Araceli Sánchez-Álvarez, Gabriela Elizabeth Quintanilla-Villanueva, Oscar Javier Silva-Hernández, Melissa Marlene Rodríguez-Delgado and Juan Francisco Villarreal-Chiu

Chemosensors 2025, 13(7), 257; https://doi.org/10.3390/chemosensors13070257 - 15 Jul 2025

Viewed by 673

Abstract

Microplastics (MP) have been found not only in the environment but also in living beings, including humans. As an initial step in MP detection, a method is proposed to measure the effective refractive index of a solution containing 5 µm diameter spherical polystyrene particles (SPSP) in distilled water, based on the surface plasmon resonance (SPR) technique and Mie scattering theory. The reflectances of the samples are obtained with their resonance angles and depths that must be normalized and adjusted according to the reference of the air and the distilled water, to subsequently find their effective refraction index corresponding to the Mie scattering theory. The system has an optical sensor with a Kretschmann–Raether configuration, consisting of a semicircular prism, a thin gold film, and a glass cell for solution samples with different concentrations (0.00, 0.20, 0.05, 0.50, and 1.00%). The experimental result provided a good linear fit with an R² = 0.9856 and a sensitivity of 7.2863 ×

10^{- 5}

RIU/% (refractive index unit per percentage of fill fraction). The limits of detection (LOD) and limit of quantification (LOQ) were determined to be 0.001% and 0.0035%, respectively. The developed optomechatronic system and its applications based on the SPR and Scattering enabled the effective measurement of the refractive index and concentration of solutions containing 5 µm diameter SPSP in distilled water. Full article

(This article belongs to the Special Issue Spectroscopic Techniques for Chemical Analysis)

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15 pages, 6078 KB

Open AccessArticle

Developing a Quantitative Profiling Method for Detecting Free Fatty Acids in Crude Lanolin Based on Analytical Quality by Design

by Sihan Liu, Shaohua Wu, Hao Zhang and Xingchu Gong

Chemosensors 2025, 13(4), 126; https://doi.org/10.3390/chemosensors13040126 - 3 Apr 2025

Viewed by 1191

Abstract

In this study, a quantitative profiling method for detecting free fatty acids in crude lanolin based on the Quality by Design (QbD) concept was developed. High-performance liquid chromatography (HPLC) equipped with a charged aerosol detector (CAD) and a Proshell 120 EC C18 column was employed for the separation of crude lanolin components. Initially, the analytical target profile and critical method attributes were defined. Potential critical method parameters, including column temperature, flow rate, isocratic run time, gradient end organic phase ratio, and gradient time, were identified using fishbone diagrams and single-factor experiments. The definitive screening design (DSD) was then utilized to screen and optimize these parameters. Stepwise regression was applied to establish quantitative models between the critical method attributes and the method parameters. Subsequently, the method operable design region (MODR) was calculated and was successfully verified. The analytical conditions established were configured with 0.1% formic acid in water and 0.1% formic acid in acetonitrile serving as the mobile phases. The flow rate was set at 0.8 mL/min, and the column temperature was maintained at 35 °C with the evaporation tube temperature also set at 35 °C. An injection volume of 10 μL was used for each analysis. The gradient elution conditions were as follows: from 0 to 30 min, 75% of solvent B was used, and from 30 to 60 min, the proportion of solvent B was increased from 75% to 79%. Ten components, including 12-hydroxystearic acid, 2-hexyldecanoic acid, and palmitic acid, were identified by mass spectrometry, and seven common peaks were found in the fingerprints. The contents of palmitic acid, oleic acid, and stearic acid in the crude lanolin were quantitatively determined. Both the fingerprint and quantitative analysis methods were validated. The method was applied to analyze 15 batches of crude lanolin from different sources. The new established quantitative profiling method for free fatty acids can be potentially used for industrial applications to enhance the quality control of crude lanolin. Full article

(This article belongs to the Special Issue Spectroscopic Techniques for Chemical Analysis)

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27 pages, 4109 KB

Open AccessReview

What’s New with the Old Ones: Updates on Analytical Methods for Fossil Research

by Luminița Ghervase and Monica Dinu

Chemosensors 2025, 13(9), 328; https://doi.org/10.3390/chemosensors13090328 - 2 Sep 2025

Viewed by 1977

Abstract

Fossils are portals to the past, providing researchers with vital information about the evolution of life on Earth throughout the geological eras. The present study synthesizes the recent trends in fossil research, emphasizing the most common techniques found in the specialized literature over the past 20 years. The bibliographic survey revealed that destructive methods continue to play a significant role in scientific production related to this topic, particularly in studies on 3D morphologies, diagenesis, nutritional ecology, dating, elucidating dietary or habitat preferences, or understanding the physiology of extinct species. However, noninvasive tools, such as Raman spectroscopy, are rapidly rising, particularly when integrated with imaging techniques. As such, fossil research continues to advance even beyond the borders of our planet, exploring extraterrestrial samples in a quest to unlock the universal mystery of life. At the same time, the advent of advanced AI methods—particularly model chatbots that rival the capabilities of experienced scientists—has facilitated and enhanced data interpretation and classification. As fossil research evolves, upcoming technological advancements in spatial resolution, penetration depth, and detection sensitivity will integrate state-of-the-art spectroscopic tools. This will undoubtedly take fossil research to new heights, generating breakthroughs that optimize analysis while preserving invaluable specimens. Overall, the present study offers a holistic overview of analytical techniques through meta-analysis and bibliometric mapping, including a critical assessment of commonly used methods and offering a glimpse into the integration of machine learning and AI tools in fossil research. Full article

(This article belongs to the Special Issue Spectroscopic Techniques for Chemical Analysis)

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