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Special Issue "Advances in Chemical Analysis Procedures (Part II): Statistical and Chemometric Approaches"

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

Deadline for manuscript submissions: closed (31 December 2019).

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A printed edition of this Special Issue is available here.

Special Issue Editors

Prof. Dr. Marcello Locatelli
Website SciProfiles
Guest Editor
Department of Pharmacy, University “G. d'Annunzio” of Chieti and Pescara, Chieti, Italy
Interests: innovative (micro) extraction procedures (MEPS, FPSE, DLLME, SULLE, MAE, etc.) and hyphenated instrument configurations; bioactive compounds (drugs, drugs associations, and natural bioactive compounds); characterization, fingerprints, and method validation; HPLC; mass spectrometry (MS and MS/MS) * Section EiC of Hyphenated Instrument Configurations & Section EiC of Sample Pretreatment and Extraction
Special Issues and Collections in MDPI journals
Dr. Angela Tartaglia

Guest Editor
Department of Pharmacy, University "G. d'Annunzio" of Chieti-Pescara; Build B, level II, Via dei Vestini, 31, 66100-Chieti (CH), Italy
Interests: method development; analytical and bioanalytical chemistry; method validation; hyphenated assay; HPLC
Special Issues and Collections in MDPI journals
Prof. Dr. Dora Melucci
Website
Guest Editor
Alma Mater Studiorum University of Bologna, Department of Chemistry “Giacomo Ciamician”, Via Selmi 2, I-40126 Bologna, Italy
Interests: Chemometrics; Environmental chemistry; Forensics; Food chemistry; Pharmaceutics
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Prof. Dr. Abuzar Kabir
Website
Guest Editor
International Forensic Research Institute, Department of Chemistry and Biochemistry, Florida International University, Miami, Florida, USA
Interests: chromatographic stationary phases; substrate-free solid-phase extraction sorbents; molecular imprinting technology; sorbents for environmental pollution remediation; miniaturized sample preparation devices; field deployable sample preparation technology
Special Issues and Collections in MDPI journals
Prof. Dr. Halil Ibrahim Ulusoy
Website SciProfiles
Guest Editor
Analytical Chemistry, Faculty of Pharmacy, Cumhuriyet University, Sivas, Turkey
Interests: analytical method development; chromatography; pre-concentration and seperation methods; trace analysis; molecular and atomic spectroscopy
Special Issues and Collections in MDPI journals
Dr. Victoria Samanidou
Website SciProfiles
Guest Editor
Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Interests: analytical chemistry; sample preparation; separations; HPLC; extraction techniques
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Analytical chemistry deals with both qualitative and quantitative measurements, although modern approaches are more inclined towards quantitative science. In analytical laboratories, the measurements are usually made on a small group of representative samples to determine the presence and the concentration of the target analytes. Following the data collection, the results are tabulated to evaluate the quality of the data. An important area in evaluating analytical data is represented by statistical approaches, which should not be considered only for evaluating the results of experiments, but also in the planning and design of experiments. The design and optimization process should include the identification of those experimental factors and then combine them in an optimal way, to obtain the best sensitivity, selectivity, etc. The major quantitative chemical problems can also be performed with chemometric measurements. The starting point of multivariate measurements is usually represented by principal component analysis (PCA) which can reduce the dimensionality of the data, eliminate false information, search outliers, etc. The modern tools for the various measurements are completely devoid of manual controls and are controlled by personal computers that record and manage the obtained data. In recent years, appreciable progress has been made and in the most modern analytical chemistry laboratories, instruments not only allow quick and precise data calculations but also include instrument performance control and reporting of any malfunctions.

Subtopics: Chemometric approaches; analytical statistical approaches; data elaboration 

Schedule:  Manuscript Submission Deadline: August 2019
Peer Review Due: September 2019
Revision Due: October 2019
Notification of Acceptance by the Guest Editors: October 2019
Final Manuscripts Due: November 2019

Prof. Dr. Marcello Locatelli
Dr. Angela Tartaglia
Dr. Dora Melucci
Dr. Abuzar Kabir
Prof. Dr. Halil Ibrahim Ulusoy
Prof. Dr. Victoria Samanidou
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

  • statistics and chemometric approaches
  • quantitative analysis
  • data elaboration
  • multivariate models
  • PCA

Published Papers (12 papers)

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Research

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Open AccessArticle
Raman Spectroscopy and Chemometric Modeling to Predict Physical-Chemical Honey Properties from Campeche, Mexico
Molecules 2019, 24(22), 4091; https://doi.org/10.3390/molecules24224091 - 13 Nov 2019
Abstract
In this work, 10 chemometric models based on Raman spectroscopy were constructed to predict the physicochemical properties of honey produced in the state of Campeche, Mexico. The properties of honey studied were pH, moisture, total soluble solids (TSS), free acidity, lactonic acidity, total [...] Read more.
In this work, 10 chemometric models based on Raman spectroscopy were constructed to predict the physicochemical properties of honey produced in the state of Campeche, Mexico. The properties of honey studied were pH, moisture, total soluble solids (TSS), free acidity, lactonic acidity, total acidity, electrical conductivity, Redox potential, hydroxymethylfurfural (HMF), and ash content. These proprieties were obtained according to the methods described by the Association of Official Analytical Chemists, Codex Alimentarius, and the International Honey Commission. For the construction of the chemometric models, 189 honey samples were collected and analyzed in triplicate using Raman spectroscopy to generate the matrix data [X], which were correlated with each of the physicochemical properties [Y]. The predictive capacity of each model was determined by cross validation and external validation, using the statistical parameters: standard error of calibration (SEC), standard error of prediction (SEP), coefficient of determination of cross-validation (R2cal), coefficient of determination for external validation (R2val), and Student’s t-test. The statistical results indicated that the chemometric models satisfactorily predict the humidity, TSS, free acidity, lactonic acidity, total acidity, and Redox potential. However, the models for electric conductivity and pH presented an acceptable prediction capacity but not adequate to supply the conventional processes, while the models for predicting ash content and HMF were not satisfactory. The developed models represent a low-cost tool to analyze the quality of honey, and contribute significantly to increasing the honey distribution and subsequently the economy of the region. Full article
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Open AccessArticle
ATR-FTIR Spectroscopy, a New Non-Destructive Approach for the Quantitative Determination of Biogenic Silica in Marine Sediments
Molecules 2019, 24(21), 3927; https://doi.org/10.3390/molecules24213927 - 31 Oct 2019
Cited by 2
Abstract
Biogenic silica is the major component of the external skeleton of marine micro-organisms, such as diatoms, which, after the organisms death, settle down onto the seabed. These micro-organisms are involved in the CO2 cycle because they remove it from the atmosphere through [...] Read more.
Biogenic silica is the major component of the external skeleton of marine micro-organisms, such as diatoms, which, after the organisms death, settle down onto the seabed. These micro-organisms are involved in the CO2 cycle because they remove it from the atmosphere through photosynthesis. The biogenic silica content in marine sediments, therefore, is an indicator of primary productivity in present and past epochs, which is useful to study the CO2 trends. Quantification of biosilica in sediments is traditionally carried out by wet chemistry followed by spectrophotometry, a time-consuming analytical method that, besides being destructive, is affected by a strong risk of analytical biases owing to the dissolution of other silicatic components in the mineral matrix. In the present work, the biosilica content was directly evaluated in sediment samples, without chemically altering them, by attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy. Quantification was performed by combining the multivariate standard addition method (MSAM) with the net analyte signal (NAS) procedure to solve the strong matrix effect of sediment samples. Twenty-one sediment samples from a sediment core and one reference standard sample were analyzed, and the results (extrapolated concentrations) were found to be comparable to those obtained by the traditional wet method, thus demonstrating the feasibility of the ATR-FTIR-MSAM-NAS approach as an alternative method for the quantification of biosilica. Future developments will cover in depth investigation on biosilica from other biogenic sources, the extension of the method to sediments of other provenance, and the use higher resolution IR spectrometers. Full article
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Open AccessArticle
Untargeted Metabolomic Profile for the Detection of Prostate Carcinoma—Preliminary Results from PARAFAC2 and PLS–DA Models
Molecules 2019, 24(17), 3063; https://doi.org/10.3390/molecules24173063 - 22 Aug 2019
Cited by 1
Abstract
Prostate-specific antigen (PSA) is the main biomarker for the screening of prostate cancer (PCa), which has a high sensibility (higher than 80%) that is negatively offset by its poor specificity (only 30%, with the European cut-off of 4 ng/mL). This generates a large [...] Read more.
Prostate-specific antigen (PSA) is the main biomarker for the screening of prostate cancer (PCa), which has a high sensibility (higher than 80%) that is negatively offset by its poor specificity (only 30%, with the European cut-off of 4 ng/mL). This generates a large number of useless biopsies, involving both risks for the patients and costs for the national healthcare systems. Consequently, efforts were recently made to discover new biomarkers useful for PCa screening, including our proposal of interpreting a multi-parametric urinary steroidal profile with multivariate statistics. This approach has been expanded to investigate new alleged biomarkers by the application of untargeted urinary metabolomics. Urine samples from 91 patients (43 affected by PCa; 48 by benign hyperplasia) were deconjugated, extracted in both basic and acidic conditions, derivatized with different reagents, and analyzed with different gas chromatographic columns. Three-dimensional data were obtained from full-scan electron impact mass spectra. The PARADISe software, coupled with NIST libraries, was employed for the computation of PARAFAC2 models, the extraction of the significative components (alleged biomarkers), and the generation of a semiquantitative dataset. After variables selection, a partial least squares–discriminant analysis classification model was built, yielding promising performances. The selected biomarkers need further validation, possibly involving, yet again, a targeted approach. Full article
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Open AccessArticle
Identification of Metabolites of Eupatorin in Vivo and in Vitro Based on UHPLC-Q-TOF-MS/MS
Molecules 2019, 24(14), 2658; https://doi.org/10.3390/molecules24142658 - 23 Jul 2019
Cited by 3
Abstract
Eupatorin is the major bioactive component of Java tea (Orthosiphon stamineus), exhibiting strong anticancer and anti-inflammatory activities. However, no research on the metabolism of eupatorin has been reported to date. In the present study, ultra-high-performance liquid chromatography coupled with hybrid triple [...] Read more.
Eupatorin is the major bioactive component of Java tea (Orthosiphon stamineus), exhibiting strong anticancer and anti-inflammatory activities. However, no research on the metabolism of eupatorin has been reported to date. In the present study, ultra-high-performance liquid chromatography coupled with hybrid triple quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) combined with an efficient online data acquisition and a multiple data processing method were developed for metabolite identification in vivo (rat plasma, bile, urine and feces) and in vitro (rat liver microsomes and intestinal flora). A total of 51 metabolites in vivo, 60 metabolites in vitro were structurally characterized. The loss of CH2, CH2O, O, CO, oxidation, methylation, glucuronidation, sulfate conjugation, N-acetylation, hydrogenation, ketone formation, glycine conjugation, glutamine conjugation and glucose conjugation were the main metabolic pathways of eupatorin. This was the first identification of metabolites of eupatorin in vivo and in vitro and it will provide reference and valuable evidence for further development of new pharmaceuticals and pharmacological mechanisms. Full article
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Open AccessFeature PaperArticle
A Quick and Efficient Non-Targeted Screening Test for Saffron Authentication: Application of Chemometrics to Gas-Chromatographic Data
Molecules 2019, 24(14), 2602; https://doi.org/10.3390/molecules24142602 - 17 Jul 2019
Cited by 4
Abstract
Saffron is one of the most adulterated food products all over the world because of its high market prize. Therefore, a non-targeted approach based on the combination of headspace flash gas-chromatography with flame ionization detection (HS-GC-FID) and chemometrics was tested and evaluated to [...] Read more.
Saffron is one of the most adulterated food products all over the world because of its high market prize. Therefore, a non-targeted approach based on the combination of headspace flash gas-chromatography with flame ionization detection (HS-GC-FID) and chemometrics was tested and evaluated to check adulteration of this spice with two of the principal plant-derived adulterants: turmeric (Curcuma longa L.) and marigold (Calendula officinalis L.). Chemometric models were carried out through both linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLS-DA) from the gas-chromatographic data. These models were also validated by cross validation (CV) and external validation, which were performed by testing both models on pure spices and artificial mixtures capable of simulating adulterations of saffron with the two adulterants examined. These models gave back satisfactory results. Indeed, both models showed functional internal and external prediction ability. The achieved results point out that the method based on a combination of chemometrics with gas-chromatography may provide a rapid and low-cost screening method for the authentication of saffron. Full article
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Open AccessArticle
Protein-Based Fingerprint Analysis for the Identification of Ranae Oviductus Using RP-HPLC
Molecules 2019, 24(9), 1687; https://doi.org/10.3390/molecules24091687 - 30 Apr 2019
Cited by 6
Abstract
This work demonstrated a method combining reversed-phase high-performance liquid chromatography (RP-HPLC) with chemometrics analysis to identify the authenticity of Ranae Oviductus. The fingerprint chromatograms of the Ranae Oviductus protein were established through an Agilent Zorbax 300SB-C8 column and diode array detection at [...] Read more.
This work demonstrated a method combining reversed-phase high-performance liquid chromatography (RP-HPLC) with chemometrics analysis to identify the authenticity of Ranae Oviductus. The fingerprint chromatograms of the Ranae Oviductus protein were established through an Agilent Zorbax 300SB-C8 column and diode array detection at 215 nm, using 0.085% TFA (v/v) in acetonitrile (A) and 0.1% TFA in ultrapure water (B) as mobile phase. The similarity was in the range of 0.779–0.980. The fingerprint chromatogram of Ranae Oviductus showed a significant difference with counterfeit products. Hierarchical clustering analysis (HCA) and principal component analysis (PCA) successfully identified Ranae Oviductus from the samples. These results indicated that the method established in this work was reliable. Full article
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Open AccessArticle
Quality Evaluation of Gastrodia Elata Tubers Based on HPLC Fingerprint Analyses and Quantitative Analysis of Multi-Components by Single Marker
Molecules 2019, 24(8), 1521; https://doi.org/10.3390/molecules24081521 - 17 Apr 2019
Cited by 8
Abstract
Gastrodia elata (G. elata) tuber is a valuable herbal medicine used to treat many diseases. The procedure of establishing a reasonable and feasible quality assessment method for G. elata tuber is important to ensure its clinical safety and efficacy. In this [...] Read more.
Gastrodia elata (G. elata) tuber is a valuable herbal medicine used to treat many diseases. The procedure of establishing a reasonable and feasible quality assessment method for G. elata tuber is important to ensure its clinical safety and efficacy. In this research, an effective and comprehensive evaluation method for assessing the quality of G. elata has been developed, based on the analysis of high performance liquid chromatography (HPLC) fingerprint, combined with the quantitative analysis of multi-components by single marker (QAMS) method. The contents of the seven components, including gastrodin, p-hydroxybenzyl alcohol, p-hydroxy benzaldehyde, parishin A, parishin B, parishin C, and parishin E were determined, simultaneously, using gastrodin as the reference standard. The results demonstrated that there was no significant difference between the QAMS method and the traditional external standard method (ESM) (p > 0.05, RSD < 4.79%), suggesting that QAMS was a reliable and convenient method for the content determination of multiple components, especially when there is a shortage of reference substances. In conclusion, this strategy could be beneficial for simplifying the processes in the quality control of G. elata tuber and giving references to promote the quality standards of herbal medicines. Full article
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Open AccessArticle
Geographical Authentication of Macrohyporia cocos by a Data Fusion Method Combining Ultra-Fast Liquid Chromatography and Fourier Transform Infrared Spectroscopy
Molecules 2019, 24(7), 1320; https://doi.org/10.3390/molecules24071320 - 03 Apr 2019
Cited by 5
Abstract
Macrohyporia cocos is a medicinal and edible fungi, which is consumed widely. The epidermis and inner part of its sclerotium are used separately. M. cocos quality is influenced by geographical origins, so an effective and accurate geographical authentication method is required. Liquid chromatograms [...] Read more.
Macrohyporia cocos is a medicinal and edible fungi, which is consumed widely. The epidermis and inner part of its sclerotium are used separately. M. cocos quality is influenced by geographical origins, so an effective and accurate geographical authentication method is required. Liquid chromatograms at 242 nm and 210 nm (LC242 and LC210) and Fourier transform infrared (FTIR) spectra of two parts were applied to authenticate the geographical origin of cultivated M. cocos combined with low and mid-level data fusion strategies, and partial least squares discriminant analysis. Data pretreatment involved correlation optimized warping and second derivative. The results showed that the potential of the chromatographic fingerprint was greater than that of five triterpene acids contents. LC242-FTIR low-level fusion took full advantage of information synergy and showed good performance. Further, the predictive ability of the FTIR low-level fusion model of two parts was satisfactory. The performance of the low-level fusion strategy preceded those of the single technique and mid-level fusion strategy. The inner parts were more suitable for origin identification than the epidermis. This study proved the feasibility of the data fusion of chromatograms and spectra, and the data fusion of different parts for the accurate authentication of geographical origin. This method is meaningful for the quality control of food and the protection of geographical indication products. Full article
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Open AccessArticle
Artificial Neural Network Prediction of Retention of Amino Acids in Reversed-Phase HPLC under Application of Linear Organic Modifier Gradients and/or pH Gradients
Molecules 2019, 24(3), 632; https://doi.org/10.3390/molecules24030632 - 11 Feb 2019
Cited by 1
Abstract
A multi-layer artificial neural network (ANN) was used to model the retention behavior of 16 o-phthalaldehyde derivatives of amino acids in reversed-phase liquid chromatography under application of various gradient elution modes. The retention data, taken from literature, were collected in acetonitrile–water eluents [...] Read more.
A multi-layer artificial neural network (ANN) was used to model the retention behavior of 16 o-phthalaldehyde derivatives of amino acids in reversed-phase liquid chromatography under application of various gradient elution modes. The retention data, taken from literature, were collected in acetonitrile–water eluents under application of linear organic modifier gradients ( gradients), pH gradients, or double pH/ gradients. At first, retention data collected in  gradients and pH gradients were modeled separately, while these were successively combined in one dataset and fitted simultaneously. Specific ANN-based models were generated by combining the descriptors of the gradient profiles with 16 inputs representing the amino acids and providing the retention time of these solutes as the response. Categorical “bit-string” descriptors were adopted to identify the solutes, which allowed simultaneously modeling the retention times of all 16 target amino acids. The ANN-based models tested on external gradients provided mean errors for the predicted retention times of 1.1% ( gradients), 1.4% (pH gradients), 2.5% (combined  and pH gradients), and 2.5% (double pH/ gradients). The accuracy of ANN prediction was better than that previously obtained by fitting of the same data with retention models based on the solution of the fundamental equation of gradient elution. Full article
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Open AccessArticle
Comparison and Identification for Rhizomes and Leaves of Paris yunnanensis Based on Fourier Transform Mid-Infrared Spectroscopy Combined with Chemometrics
Molecules 2018, 23(12), 3343; https://doi.org/10.3390/molecules23123343 - 17 Dec 2018
Cited by 6
Abstract
Paris polyphylla, as a traditional herb with long history, has been widely used to treat diseases in multiple nationalities of China. Nevertheless, the quality of P. yunnanensis fluctuates among from different geographical origins, so that a fast and accurate classification method was [...] Read more.
Paris polyphylla, as a traditional herb with long history, has been widely used to treat diseases in multiple nationalities of China. Nevertheless, the quality of P. yunnanensis fluctuates among from different geographical origins, so that a fast and accurate classification method was necessary for establishment. In our study, the geographical origin identification of 462 P. yunnanensis rhizome and leaf samples from Kunming, Yuxi, Chuxiong, Dali, Lijiang, and Honghe were analyzed by Fourier transform mid infrared (FT-MIR) spectra, combined with partial least squares discriminant analysis (PLS-DA), random forest (RF), and hierarchical cluster analysis (HCA) methods. The obvious cluster tendency of rhizomes and leaves FT-MIR spectra was displayed by principal component analysis (PCA). The distribution of the variable importance for the projection (VIP) was more uniform than the important variables obtained by RF, while PLS-DA models obtained higher classification abilities. Hence, a PLS-DA model was more suitably used to classify the different geographical origins of P. yunnanensis than the RF model. Additionally, the clustering results of different geographical origins obtained by HCA dendrograms also proved the chemical information difference between rhizomes and leaves. The identification performances of PLS-DA and the RF models of leaves FT-MIR matrixes were better than those of rhizomes datasets. In addition, the model classification abilities of combination datasets were higher than the individual matrixes of rhizomes and leaves spectra. Our study provides a reference to the rational utilization of resources, as well as a fast and accurate identification research for P. yunnanensis samples. Full article
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Review

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Open AccessFeature PaperReview
Chemometrics Approaches in Forced Degradation Studies of Pharmaceutical Drugs
Molecules 2019, 24(20), 3804; https://doi.org/10.3390/molecules24203804 - 22 Oct 2019
Abstract
Chemometrics is the chemistry field responsible for planning and extracting the maximum of information of experiments from chemical data using mathematical tools (linear algebra, statistics, and so on). Active pharmaceutical ingredients (APIs) can form impurities when exposed to excipients or environmental variables such [...] Read more.
Chemometrics is the chemistry field responsible for planning and extracting the maximum of information of experiments from chemical data using mathematical tools (linear algebra, statistics, and so on). Active pharmaceutical ingredients (APIs) can form impurities when exposed to excipients or environmental variables such as light, high temperatures, acidic or basic conditions, humidity, and oxidative environment. By considering that these impurities can affect the safety and efficacy of the drug product, it is necessary to know how these impurities are yielded and to establish the pathway of their formation. In this context, forced degradation studies of pharmaceutical drugs have been used for the characterization of physicochemical stability of APIs. These studies are also essential in the validation of analytical methodologies, in order to prove the selectivity of methods for the API and its impurities and to create strategies to avoid the formation of degradation products. This review aims to demonstrate how forced degradation studies have been actually performed and the applications of chemometric tools in related studies. Some papers are going to be discussed to exemplify the chemometric applications in forced degradation studies. Full article
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Open AccessReview
Approaching Authenticity Issues in Fish and Seafood Products by Qualitative Spectroscopy and Chemometrics
Molecules 2019, 24(9), 1812; https://doi.org/10.3390/molecules24091812 - 10 May 2019
Cited by 5
Abstract
The intrinsically complex nature of fish and seafood, as well as the complicated organisation of the international fish supply and market, make struggle against counterfeiting and falsification of fish and seafood products very difficult. The development of fast and reliable omics strategies based [...] Read more.
The intrinsically complex nature of fish and seafood, as well as the complicated organisation of the international fish supply and market, make struggle against counterfeiting and falsification of fish and seafood products very difficult. The development of fast and reliable omics strategies based on spectroscopy in conjunction with multivariate data analysis has been attracting great interest from food scientists, so that the studies linked to fish and seafood authenticity have increased considerably in recent years. The present work has been designed to review the most promising studies dealing with the use of qualitative spectroscopy and chemometrics for the resolution of the key authenticity issues of fish and seafood products, with a focus on species substitution, geographical origin falsification, production method or farming system misrepresentation, and fresh for frozen/thawed product substitution. Within this framework, the potential of fluorescence, vibrational, nuclear magnetic resonance, and hyperspectral imaging spectroscopies, combined with both unsupervised and supervised chemometric techniques, has been highlighted, each time pointing out the trends in using one or another analytical approach and the performances achieved. Full article
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