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Zheng W, Chen Y, Pang W, Gao J, Li T. Riverine seasonal rainfall event tracing of organic pollution sources using fluorescence fingerprint difference spectrum. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 949:175024. [PMID: 39059669 DOI: 10.1016/j.scitotenv.2024.175024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Revised: 07/02/2024] [Accepted: 07/23/2024] [Indexed: 07/28/2024]
Abstract
Elucidating the dynamics of dissolved organic matter (DOM) transport and transformation under seasonal rainfall events is essential for the conservation of riverine ecosystems, for mitigating the effects of climate change, and for crafting informed water management strategies. Therefore, this study aimed to investigate the evolutionary characteristics of organic pollution sources during consecutive rainfall events in early spring and to quantify their relative contributions to the process of surface water pollution. The results showed seasonal rainfall induces water quality exceedances in rivers due to the combined impacts of terrestrial inputs and endogenous releases. Humic acid (HA) (region V) and fulvic acid (FA) (region III) emerged as the predominant organic matter in the water column, with their fluorescence intensity altering as rainwater flushed the riverbed. Sources of pollution include agricultural and urban domestic sources (AS + DS) (72.29 %), industrial and urban domestic and microbial sources (IS + DS + MS) (37.71 %), and agricultural and industrial sources (AS + IS) (63.32 %), indicating that agricultural surface pollution discharges contribute significantly. The gas-chromatography-mass spectrometry (GC-MS) further confirmed that exogenous inputs were predominantly comprised of particulate pollutants. This study underscores the efficacy of fluorescence difference spectrometry in delineating the migration and transformation of river pollution sources during seasonal rainfall and facilitating the implementation of targeted management strategies for river ecosystems.
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Affiliation(s)
- Wenjing Zheng
- Key Laboratory of Yellow River Water Environment in Gansu Province, Lanzhou Jiaotong University, Lanzhou 730070, China; College of Environment and Municipal Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
| | - Yan Chen
- Key Laboratory of Yellow River Water Environment in Gansu Province, Lanzhou Jiaotong University, Lanzhou 730070, China; College of Environment and Municipal Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China.
| | - Weihai Pang
- College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Key Laboratory of Yangtze River Water Environment, Ministry of Education, Shanghai 200092, China
| | - Jianling Gao
- Key Laboratory of Yellow River Water Environment in Gansu Province, Lanzhou Jiaotong University, Lanzhou 730070, China; College of Environment and Municipal Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
| | - Tian Li
- College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Key Laboratory of Yangtze River Water Environment, Ministry of Education, Shanghai 200092, China
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Froelich NM, Azcarate SM, Goicoechea HC, Campiglia AD. Differentiating Nylon Samples with Visually Indistinguishable Fluorescence Using Principal Component Analysis and Common Dimension Partial Least Squares Linear Discriminant Analysis with Synchronous Fluorescence Spectroscopy. APPLIED SPECTROSCOPY 2024; 78:962-973. [PMID: 38775045 DOI: 10.1177/00037028241255150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2024]
Abstract
Fluorescence spectroscopy is an attractive candidate for analyzing samples of nylon. Impurities within the polymers formed during the synthesis and processing of nylons give rise to the observed fluorescence, allowing for nylons to be analyzed based on their impurities. Nylons from the same source are expected to display similar fluorescence profiles, and nylons with different fluorescence are expected to be from different sources. This paper investigates an important case where different nylons displayed similar fluorescence, preventing easy discrimination. Samples of Nylon 6 and Nylon 6/12 had visually indistinguishable excitation-emission matrices (EEM), excitation spectra, fluorescence spectra, and synchronous fluorescence spectra at larger Δλ. By collecting synchronous fluorescence spectra at smaller Δλ, additional features in the fluorescence profiles were identified that allowed for some discrimination between the two nylons. Combining the EEM and synchronous fluorescence data with chemometric algorithms provided a clearer differentiation between the two nylons. parallel factor analysis, principal component analysis, and common dimension partial least squares (ComDim-PLS) showed two distinct clusters in the data, with ComDim-PLS providing the greatest distinction between the clusters. The loadings revealed the variables of interest to the ComDim-PLS were the 400 nm and 335 nm bands for all synchronous fluorescence spectra, the 460 nm and 310 nm bands for the Δλ = 20 nm and Δλ = 30 nm synchronous fluorescence spectra, and the 440 nm band for the Δλ = 20 nm synchronous fluorescence spectra. The linear discriminant analysis performed with the PLS data yielded a classification accuracy of 95% with the EEM data and 100% with the synchronous fluorescence data, displaying the power of this technique to differentiate two different nylons with visually indistinguishable fluorescence spectra.
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Affiliation(s)
- Noah M Froelich
- Chemistry Department, University of Central Florida, Orlando, Florida, USA
| | - Silvana M Azcarate
- Facultad de Ciencias Exactas y Naturales, Universidad Nacional de La Pampa, Instituto de Ciencias de la Tierra y Ambientales de La Pampa (INCITAP), Santa Rosa, La Pampa, Argentina
| | - Héctor C Goicoechea
- Laboratorio de Desarrollo Analítico y Quimiometría, Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral, Ciudad Universitaria, Santa Fe, Argentina
| | - Andrés D Campiglia
- Chemistry Department, University of Central Florida, Orlando, Florida, USA
- National Center for Forensic Science, University of Central Florida, Orlando, Florida, USA
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Ding ZW, Wu HL, Wang T, Wang XZ, Yu RQ. Anti-interference and non-destructive identification of textile fabrics using front-face excitation-emission matrix fluorescence spectroscopy combined with multi-way chemometrics. Talanta 2023; 265:124866. [PMID: 37418956 DOI: 10.1016/j.talanta.2023.124866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 06/09/2023] [Accepted: 06/20/2023] [Indexed: 07/09/2023]
Abstract
The identification of trace textile fabrics discovered at crime scenes plays a crucial role in the case of forensic investigations. Additionally, in practical situations, fabrics may be contaminated, making identification more challenging. To address the aforementioned issue and promote the application of fabrics identification in forensic analysis, front-face excitation-emission matrix (FF-EEM) fluorescence spectra coupled with multi-way chemometric methods were proposed for the interference-free and non-destructive identification of textile fabrics. Common commercial dyes in the same color range under different materials (cotton, acrylic, and polyester) that cannot be visually distinguished were investigated, and several binary classification models for the identification of dye were established using partial least squares discriminant analysis (PLS-DA). The identification of dyed fabrics in the presence of fluorescent interference was also taken into consideration. In each kind of pattern recognition model mentioned above, the classification accuracy (ACC) of the prediction set was 100%. The alternating trilinear decomposition (ATLD) algorithm was executed to separate mathematically and remove the interference, and the classification model based on the reconstructed spectra attained an accuracy of 100%. These findings indicate that FF-EEM technology combined with multi-way chemometric methods has broad prospects for forensic trace textile fabric identification, especially in the presence of interference.
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Affiliation(s)
- Zi-Wei Ding
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha, 410082, China
| | - Hai-Long Wu
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha, 410082, China.
| | - Tong Wang
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha, 410082, China.
| | - Xiao-Zhi Wang
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha, 410082, China
| | - Ru-Qin Yu
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha, 410082, China
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Sauzier G, van Bronswijk W, Lewis SW. Chemometrics in forensic science: approaches and applications. Analyst 2021; 146:2415-2448. [PMID: 33729240 DOI: 10.1039/d1an00082a] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Forensic investigations are often reliant on physical evidence to reconstruct events surrounding a crime. However, there remains a need for more objective approaches to evidential interpretation, along with rigorously validated procedures for handling, storage and analysis. Chemometrics has been recognised as a powerful tool within forensic science for interpretation and optimisation of analytical procedures. However, careful consideration must be given to factors such as sampling, validation and underpinning study design. This tutorial review aims to provide an accessible overview of chemometric methods within the context of forensic science. The review begins with an overview of selected chemometric techniques, followed by a broad review of studies demonstrating the utility of chemometrics across various forensic disciplines. The tutorial review ends with the discussion of the challenges and emerging trends in this rapidly growing field.
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Affiliation(s)
- Georgina Sauzier
- School of Molecular and Life Sciences, Curtin University, GPO Box U1987, Perth, Western Australia 6845, Australia.
| | - Wilhelm van Bronswijk
- School of Molecular and Life Sciences, Curtin University, GPO Box U1987, Perth, Western Australia 6845, Australia.
| | - Simon W Lewis
- School of Molecular and Life Sciences, Curtin University, GPO Box U1987, Perth, Western Australia 6845, Australia.
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Cabrera-Bañegil M, Valdés-Sánchez E, Muñoz de la Peña A, Durán-Merás I. Combination of fluorescence excitation emission matrices in polar and non-polar solvents to obtain three- and four- way arrays for classification of Tempranillo grapes according to maturation stage and hydric status. Talanta 2019; 199:652-661. [DOI: 10.1016/j.talanta.2019.03.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 02/28/2019] [Accepted: 03/01/2019] [Indexed: 12/29/2022]
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Unsupervised classification of PSII with and without water-oxidizing complex samples by PARAFAC resolution of excitation-emission fluorescence images. JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY B-BIOLOGY 2019; 195:58-66. [PMID: 31100638 DOI: 10.1016/j.jphotobiol.2019.03.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Revised: 03/12/2019] [Accepted: 03/13/2019] [Indexed: 11/19/2022]
Abstract
The potential of excitation-emission fluorescence spectroscopy combined with three-way analysis was investigated for discriminating the photosystem II (PSII) (with the water-oxidizing complex) and without the water-oxidizing complex (wPSII) using unsupervised classification methods. The water-oxidizing complex within PSII carry out the reaction of water splitting which is as a vital process on the earth. Therefore, discriminating the presence of the water-oxidizing complex in protein samples is crucial. Low cost and accurate spectroscopic determination of the amount of clusters inside PSII or any other protein containing species are important when investigating the inclusion and exclusion of such clusters into and from species. Fluorescence data of samples were similar, and we showed the potential usefulness of multivariate methods, such as parallel factor analysis (PARAFAC) and principal component analysis (PCA) for recognition of the two types of samples. Both techniques were applied to the excitation-emission fluorescence matrices (EEM) of solutions at two of different pH values (2.0 and 12.0). Three fluorescent components were found for all samples that are related to tyrosine (Tyr), tryptophan (Trp) and phenylalanine (Phe) amino acids. These three amino acids are representative of all datasets and indicate their similarities and differences. We then found the effectual wavelengths for separation of samples in a specific acidity, including the excitation wavelengths of 220 and 230 nm and the emission wavelengths of 300 and 305 nm. The acidity of the solutions has various influences on the conformation of proteins. In PSII and PSII the without water-oxidizing complex samples conformational changes can change their spectra which was applied for discrimination purpose. This separation was better in pH = 12.0. We also showed the effect of time on small conformational changes within datasets were higher in pH = 2.0. In the end, for indicating the high distribution of spectral data from proteins which is the result of conformational changes, we compared the distribution of measured spectral data with that from a simple organic molecule, fluorescein. Altogether, we could distinguish between the two groups of protein samples properly at pH = 12.0 using low-cost EEM spectral images and PARAFAC.
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Mujumdar N, de la Peña AM, Campiglia AD. Classification of pre-dyed textile fibers exposed to weathering and photodegradation by non-destructive excitation-emission fluorescence spectroscopy paired with discriminant unfolded-partial least squares. Forensic Chem 2019. [DOI: 10.1016/j.forc.2018.11.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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Front-Face Fluorescence Combined with Second-Order Multiway Classification, Based on Polyphenol and Chlorophyll Compounds, for Virgin Olive Oil Monitoring Under Different Photo- and Thermal-Oxidation Procedures. FOOD ANAL METHOD 2019. [DOI: 10.1007/s12161-019-01471-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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Dolan MJ, Blackledge RD, Jorabchi K. Classifying single fibers based on fluorinated surface treatments. Anal Bioanal Chem 2019; 411:4775-4784. [DOI: 10.1007/s00216-019-01596-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Revised: 01/04/2019] [Accepted: 01/09/2019] [Indexed: 01/23/2023]
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10
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Front-face fluorescence excitation-emission matrices in combination with three-way chemometrics for the discrimination and prediction of phenolic response to vineyard agronomic practices. Food Chem 2019; 270:162-172. [DOI: 10.1016/j.foodchem.2018.07.071] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2018] [Revised: 06/08/2018] [Accepted: 07/11/2018] [Indexed: 12/20/2022]
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Mistek E, Fikiet MA, Khandasammy SR, Lednev IK. Toward Locard's Exchange Principle: Recent Developments in Forensic Trace Evidence Analysis. Anal Chem 2018; 91:637-654. [PMID: 30404441 DOI: 10.1021/acs.analchem.8b04704] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Ewelina Mistek
- Department of Chemistry , University at Albany, SUNY , 1400 Washington Avenue , Albany , New York 12222 , United States
| | - Marisia A Fikiet
- Department of Chemistry , University at Albany, SUNY , 1400 Washington Avenue , Albany , New York 12222 , United States
| | - Shelby R Khandasammy
- Department of Chemistry , University at Albany, SUNY , 1400 Washington Avenue , Albany , New York 12222 , United States
| | - Igor K Lednev
- Department of Chemistry , University at Albany, SUNY , 1400 Washington Avenue , Albany , New York 12222 , United States
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12
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Azcarate SM, de Araújo Gomes A, Muñoz de la Peña A, Goicoechea HC. Modeling second-order data for classification issues: Data characteristics, algorithms, processing procedures and applications. Trends Analyt Chem 2018. [DOI: 10.1016/j.trac.2018.07.022] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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13
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Hu Y, Wu HL, Yin XL, Gu HW, Liu Z, Xiao R, Xie LX, Fang H, Yu RQ. A flexible and novel strategy of alternating trilinear decomposition method coupled with two-dimensional linear discriminant analysis for three-way chemical data analysis: Characterization and classification. Anal Chim Acta 2018; 1021:28-40. [DOI: 10.1016/j.aca.2018.03.050] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2017] [Revised: 03/11/2018] [Accepted: 03/15/2018] [Indexed: 10/17/2022]
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Durán Merás I, Domínguez Manzano J, Airado Rodríguez D, Muñoz de la Peña A. Detection and quantification of extra virgin olive oil adulteration by means of autofluorescence excitation-emission profiles combined with multi-way classification. Talanta 2018; 178:751-762. [DOI: 10.1016/j.talanta.2017.09.095] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2017] [Revised: 09/27/2017] [Accepted: 09/30/2017] [Indexed: 11/27/2022]
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15
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Ghasemi-Varnamkhasti M, Amiri ZS, Tohidi M, Dowlati M, Mohtasebi SS, Silva AC, Fernandes DDS, Araujo MCU. Differentiation of cumin seeds using a metal-oxide based gas sensor array in tandem with chemometric tools. Talanta 2017; 176:221-226. [PMID: 28917744 DOI: 10.1016/j.talanta.2017.08.024] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2017] [Revised: 08/03/2017] [Accepted: 08/06/2017] [Indexed: 11/25/2022]
Abstract
Cumin is a plant of the Apiaceae family (umbelliferae) which has been used since ancient times as a medicinal plant and as a spice. The difference in the percentage of aromatic compounds in cumin obtained from different locations has led to differentiation of some species of cumin from other species. The quality and price of cumin vary according to the specie and may be an incentive for the adulteration of high value samples with low quality cultivars. An electronic nose simulates the human olfactory sense by using an array of sensors to distinguish complex smells. This makes it an alternative for the identification and classification of cumin species. The data, however, may have a complex structure, difficult to interpret. Given this, chemometric tools can be used to manipulate data with two-dimensional structure (sensor responses in time) obtained by using electronic nose sensors. In this study, an electronic nose based on eight metal oxide semiconductor sensors (MOS) and 2D-LDA (two-dimensional linear discriminant analysis), U-PLS-DA (Partial least square discriminant analysis applied to the unfolded data) and PARAFAC-LDA (Parallel factor analysis with linear discriminant analysis) algorithms were used in order to identify and classify different varieties of both cultivated and wild black caraway and cumin. The proposed methodology presented a correct classification rate of 87.1% for PARAFAC-LDA and 100% for 2D-LDA and U-PLS-DA, indicating a promising strategy for the classification different varieties of cumin, caraway and other seeds.
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Affiliation(s)
- Mahdi Ghasemi-Varnamkhasti
- Department of Mechanical Engineering of Biosystems, Faculty of Agriculture, Shahrekord University, PO Box 115, Shahrekord, 88186-34141, Iran.
| | - Zahra Safari Amiri
- Department of Mechanical Engineering of Biosystems, Faculty of Agriculture, Shahrekord University, PO Box 115, Shahrekord, 88186-34141, Iran
| | - Mojtaba Tohidi
- Department of Mechanical Engineering of Biosystems, Faculty of Agriculture, Shahrekord University, PO Box 115, Shahrekord, 88186-34141, Iran
| | - Majid Dowlati
- Department of Mechanical Engineering of Biosystems, Faculty of Agriculture, University of Jiroft, Jiroft, Iran; Department of Food Science and Technology, Toyserkan Faculty of Industrial Engineering, Bu-Ali Sina University
| | - Seyed Saeid Mohtasebi
- Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran
| | - Adenilton C Silva
- Universidade Federal da Paraíba, Departamento de Química, Laboratório de Automação e Instrumentação em Química Analítica/Quimiometria (LAQA), Caixa Postal 5093, 58051-970 João Pessoa, PB, Brazil
| | - David D S Fernandes
- Universidade Federal da Paraíba, Departamento de Química, Laboratório de Automação e Instrumentação em Química Analítica/Quimiometria (LAQA), Caixa Postal 5093, 58051-970 João Pessoa, PB, Brazil
| | - Mário C U Araujo
- Universidade Federal da Paraíba, Departamento de Química, Laboratório de Automação e Instrumentação em Química Analítica/Quimiometria (LAQA), Caixa Postal 5093, 58051-970 João Pessoa, PB, Brazil
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Chemometric Discrimination Between Smoked and Non-Smoked Paprika Samples. Quantification of PAHs in Smoked Paprika by Fluorescence-U-PLS/RBL. FOOD ANAL METHOD 2016. [DOI: 10.1007/s12161-016-0676-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
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17
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Identification of detergents for forensic fiber analysis. Anal Bioanal Chem 2016; 408:7935-7943. [DOI: 10.1007/s00216-016-9927-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2016] [Revised: 08/30/2016] [Accepted: 09/06/2016] [Indexed: 11/25/2022]
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Differentiation of aged fibers by Raman spectroscopy and multivariate data analysis. Talanta 2016; 154:467-73. [PMID: 27154701 DOI: 10.1016/j.talanta.2016.04.013] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2015] [Revised: 04/01/2016] [Accepted: 04/05/2016] [Indexed: 11/22/2022]
Abstract
Raman spectroscopy followed by multivariate data analysis was used to analyze cotton fibers dyed using similar formulations and submitted to different aging conditions. Spectra were collected on a commercial instrument using a near-infrared laser with a 780nm light source. Discriminant analysis allowed to correctly classify the aged fibers 100% of the time. The prediction ability of the calculated model was estimated to be 100% by the "leave-one-out" cross-validation for 3 out of the 4 series under investigation. Finally, reliability of the developed approach for the discrimination of aged vs new fibers was confirmed by the analysis of commercial polyamide and polyester textiles submitted to the same aging process.
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