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Yoon S, Jeong H, Jo SM, Hong SJ, Park H, Ban Y, Youn MY, Shin EC. Physicochemical and chemosensory properties of pomegranate (Punica granatum L.) seeds under various oven-roasting conditions. Food Chem 2024; 446:138907. [PMID: 38452508 DOI: 10.1016/j.foodchem.2024.138907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 02/27/2024] [Accepted: 02/28/2024] [Indexed: 03/09/2024]
Abstract
This study investigated the effects of oven-roasting temperature (160, 180, and 200 ℃) and time (5, 10, 15, and 20 min) on pomegranate seeds. Physicochemical properties, such as color (L*, a*, and b* values), browning index (BI), total phenolic and flavonoid contents, 2,2-diphenyl-1-picrylhydrazyl radical scavenging capacity, and chemosensory properties, including taste and volatile compounds, were analyzed. The L* and a* values, and level of sourness, umami, sweetness, and terpenes decreased, whereas the b* value, BI, and level of saltiness, bitterness, furan derivatives, pyrazines, and sulfur-containing compounds, increased with roasting time. The findings of this study showed that the positive roasting conditions for pomegranate seeds were 10-20 min at 160 ℃ and, 5-10 min at 180 ℃. This study is expected to be used as a primary reference for selecting the optimal oven-roasting conditions in which positive effects appear and for developing products utilizing pomegranate seeds.
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Affiliation(s)
- Sojeong Yoon
- Department of GreenBio Science/Food Science and Technology, Gyeongsang National University, Jinju 52725, Republic of Korea
| | - Hyangyeon Jeong
- Department of GreenBio Science/Food Science and Technology, Gyeongsang National University, Jinju 52725, Republic of Korea
| | - Seong Min Jo
- Department of GreenBio Science/Food Science and Technology, Gyeongsang National University, Jinju 52725, Republic of Korea
| | - Seong Jun Hong
- Department of GreenBio Science/Food Science and Technology, Gyeongsang National University, Jinju 52725, Republic of Korea
| | - Hyeonjin Park
- Department of GreenBio Science/Food Science and Technology, Gyeongsang National University, Jinju 52725, Republic of Korea
| | - Younglan Ban
- Department of GreenBio Science/Food Science and Technology, Gyeongsang National University, Jinju 52725, Republic of Korea
| | - Moon Yeon Youn
- Department of GreenBio Science/Food Science and Technology, Gyeongsang National University, Jinju 52725, Republic of Korea
| | - Eui-Cheol Shin
- Department of GreenBio Science/Food Science and Technology, Gyeongsang National University, Jinju 52725, Republic of Korea.
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Lee T, Mischler SE, Wolfe C. Classification of asbestos and their nonasbestiform analogues using FTIR and multivariate data analysis. J Hazard Mater 2024; 469:133874. [PMID: 38430588 DOI: 10.1016/j.jhazmat.2024.133874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 02/08/2024] [Accepted: 02/22/2024] [Indexed: 03/05/2024]
Abstract
This study presents a possible application of Fourier transform infrared (FTIR) spectrometry and multivariate data analysis, principal component analysis (PCA), and partial least squares-discriminant analysis (PLS-DA) for classifying asbestos and their nonasbestiform analogues. The objectives of the study are: 1) to classify six regulated asbestos types and 2) to classify between asbestos types and their nonasbestiform analogues. The respirable fraction of six regulated asbestos types and their nonasbestiform analogues were prepared in potassium bromide pellets and collected on polyvinyl chloride membrane filters for FTIR measurement. Both PCA and PLS-DA classified asbestos types and their nonasbestiform analogues on the score plots showed a very distinct clustering of samples between the serpentine (chrysotile) and amphibole groups. The PLS-DA model provided ∼95% correct prediction with a single asbestos type in the sample, although it did not provide all correct predictions for all the challenge samples due to their inherent complexity and the limited sample number. Further studies are necessary for a better prediction level in real samples and standardization of sampling and analysis procedures.
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Affiliation(s)
- Taekhee Lee
- Health Hazards Prevention Branch, Pittsburgh Mining Research Division, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Pittsburgh, PA 15236, USA.
| | - Steven E Mischler
- Health Hazards Prevention Branch, Pittsburgh Mining Research Division, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Pittsburgh, PA 15236, USA
| | - Cody Wolfe
- Health Hazards Prevention Branch, Pittsburgh Mining Research Division, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Pittsburgh, PA 15236, USA
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Tahseen H, Ul Huda N, Nawaz H, Majeed MI, Alwadie N, Rashid N, Aslam MA, Zafar N, Asghar M, Anwar A, Ashraf A, Umer R. Surface-enhanced Raman spectroscopy for comparison of biochemical profile of bacteriophage sensitive and resistant methicillin-resistant Staphylococcus aureus (MRSA) strains. Spectrochim Acta A Mol Biomol Spectrosc 2024; 310:123968. [PMID: 38330510 DOI: 10.1016/j.saa.2024.123968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 01/10/2024] [Accepted: 01/24/2024] [Indexed: 02/10/2024]
Abstract
Methicillin-resistant Staphylococcus aureus (MRSA) is gram positive bacteria and leading cause of a wide variety of diseases. It is a common cause of hospitalized and community-acquired infections. Development of increasing antibiotic-resistance by methicillin-resistant S. aureus (MRSA) strains demand to develop alternate novel therapies. Bacteriophages are now widely used as antibacterial therapies against antibiotic-resistant gram-positive pathogens. So, there is an urgent need to find fast detection techniques to point out phage susceptible and resistant strains of methicillin-resistant S. aureus (MRSA) bacteria. Samples of two separate strains of bacteria, S. aureus, in form of pellets and supernatant, were used for this purpose. Strain-I was resistant to phage, while the other (strain-II) was sensitive. Surface Enhanced Raman Spectroscopy (SERS) has detected significant biochemical changes in these bacterial strains of pellets and supernatants in the form of SERS spectral features. The protein portion of these two types of strains of methicillin-resistant S. aureus (MRSA) in their relevant pellets and supernatants is major distinguishing biomolecule as shown by their representative SERS spectral features. In addition, multivariate data analysis techniques such as principal component analysis (PCA) and a partial least squares-discriminant analysis (PLS-DA) were found to be helpful in identifying and characterizing various strains of S. aureus which are sensitive and resistant to bacteriophage with 100% specificity, 100% accuracy, and 99.8% sensitivity in case of SERS spectral data sets of bacterial cell pellets. Moreover, in case of supernatant samples, the results of PLS-DA model including 95.5% specificity, 96% sensitivity, and 96.5% accuracy are obtained.
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Affiliation(s)
- Hira Tahseen
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
| | - Noor Ul Huda
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
| | - Haq Nawaz
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan.
| | - Muhammad Irfan Majeed
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan.
| | - Najah Alwadie
- Department of Physics, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
| | - Nosheen Rashid
- Department of Chemistry, University of Education, Faisalabad Campus, Faisalabad 38000, Pakistan
| | - Muhammad Aamir Aslam
- Institute of Microbiology, Faculty of Veterinary, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
| | - Nishat Zafar
- Institute of Microbiology, Faculty of Veterinary, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
| | - Maria Asghar
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
| | - Ayesha Anwar
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
| | - Ayesha Ashraf
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
| | - Rabiea Umer
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
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Jin W, Cai W, Zhao S, Gao R, Jiang P. Uncovering the differences in flavor volatiles of different colored foxtail millets based on gas chromatography-ion migration spectrometry and chemometrics. Curr Res Food Sci 2023; 7:100585. [PMID: 37744553 PMCID: PMC10514424 DOI: 10.1016/j.crfs.2023.100585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 08/28/2023] [Accepted: 09/03/2023] [Indexed: 09/26/2023] Open
Abstract
The differences of volatile organic compounds in commercially available foxtail millets with different colors (black, green, white and yellow) were assayed through gas chromatography-ion migration spectrometry (GC-IMS) to explore their volatile flavor characteristics. Fifty-five volatile components were found in various colored foxtail millets, including 25 kinds of aldehydes (accounting for 39.19-48.69%), 10 ketones (25.36-32.37%), 15 alcohols (20.19-24.11%), 2 ethers (2.29-2.45%), 2 furans (1.49-2.95%) and 1 ester (0.27-0.39%). Aldehydes, alcohols and ketones were the chief volatiles in different colored foxtail millet, followed by furans, esters and ethers. These identified volatile flavor components in various colored foxtail millets obtained by GC-IMS could be well distinguished by principal components and cluster analysis. Meanwhile, a stable prediction model was fitted via partial least squares-discriminant analysis (PLS-DA), in which 17 kinds of differentially volatile components were screened out based on variable importance in projection (VIP>1). These findings might provide certain information for understanding the flavor traits of colored foxtail millets in future.
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Affiliation(s)
- Wengang Jin
- Qinba State Key Laboratory of Biological Resource and Ecological Environment (Incubation), School of Bioscience and Technology, Shaanxi University of Technology, Hanzhong, Shaanxi, 723001, China
- Collaborative Innovation Center of Bio-Resource in Qinba Mountain Area, Shaanxi Province Key Laboratory of Bio-resources, Hanzhong, Shaanxi, 723001, China
| | - Wenqiang Cai
- School of Food Science and Technology, Dalian Polytechnic University, Dalian, Liaoning, 116034, China
| | - Shibo Zhao
- Qinba State Key Laboratory of Biological Resource and Ecological Environment (Incubation), School of Bioscience and Technology, Shaanxi University of Technology, Hanzhong, Shaanxi, 723001, China
- Collaborative Innovation Center of Bio-Resource in Qinba Mountain Area, Shaanxi Province Key Laboratory of Bio-resources, Hanzhong, Shaanxi, 723001, China
| | - Ruichang Gao
- Qinba State Key Laboratory of Biological Resource and Ecological Environment (Incubation), School of Bioscience and Technology, Shaanxi University of Technology, Hanzhong, Shaanxi, 723001, China
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, 212013, China
| | - Pengfei Jiang
- School of Food Science and Technology, Dalian Polytechnic University, Dalian, Liaoning, 116034, China
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Saleem M, Nawaz H, Majeed MI, Rashid N, Anjum F, Tahir M, Shahzad R, Sehar A, Sabir A, Rafiq N, Ishtiaq S, Shahid M. Surface-enhanced Raman spectroscopy (SERS) for the characterization of supernatants of bacterial cultures of bacterial strains causing sinusitis. Photodiagnosis Photodyn Ther 2023; 41:103278. [PMID: 36627069 DOI: 10.1016/j.pdpdt.2023.103278] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/29/2022] [Accepted: 01/04/2023] [Indexed: 01/08/2023]
Abstract
BACKGROUND Sinusitis is defined as inflammation of the paranasal sinus mucous membrane lining caused by bacteria which usually invade the sinus by upper respiratory tract viral infections (UTI). OBJECTIVES In the present study, Surface-enhanced Raman spectroscopy (SERS) has been applied to differentiate and characterize supernatant samples, in triplicate, of three different types of bacteria which are considered leading cause of sinusitis disease. METHODS For this purpose, supernatant samples of three different strains of bacteria namely Staphylococcus aureus, Klebsiella pneumoniae and Enterococcus faecalis. The SERS has identified significant changes as a result of secretions of biomolecules by these bacteria in their supernatants which can be helpful to explore the potential of this technique for the identification and characterization of different strains of bacteria causing same disease. RESULTS These differentiating characteristic SERS spectral features including 552 cm-1 (C-S-S-C bonds), 951 cm-1 (CN stretching), 1008 cm-1 (Phenylalanine), 1032 cm-1 (In plane CH bending mode Phenylalanine), 1280 cm-1, 1320 cm-1, 1329 cm-1 (Amide III band), 1368 cm-1, 1400 cm-1, 1420 cm-1 (COO-sym. stretching and CH bending), 1583 cm-1 (Tyrosine) correspond to Proteins and 1051 cm-1 (C-C, C-O, -C-OH def.) correspond to carbohydrates contents of these three different types of bacterial secretions in their respective supernatants. Furthermore, multivariate data analysis techniques like principal component analysis (PCA) and a supervised method partial least squares-discriminant analysis (PLS-DA) were found to be useful for the identification and characterization of different bacterial supernatants. CONCLUSIONS Surface-enhanced Raman spectroscopy is proven to be a helpful approach for the characterization and discrimination of three bacterial supernatants including S. aureus, K. pneumonia and E. faecalis.
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Affiliation(s)
- Mudassar Saleem
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
| | - Haq Nawaz
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan.
| | - Muhammad Irfan Majeed
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan.
| | - Nosheen Rashid
- Department of Chemistry, University of Education, Faisalabad Campus, Faisalabad 38000, Pakistan
| | - Fozia Anjum
- Department of Chemistry, Government College University Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Tahir
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
| | - Rida Shahzad
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
| | - Aafia Sehar
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
| | - Amina Sabir
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
| | - Nighat Rafiq
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
| | - Shazra Ishtiaq
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Shahid
- Department of Biochemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
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Msimanga HZ, Dockery CR, Vandenbos DD. Classification of local diesel fuels and simultaneous prediction of their physicochemical parameters using FTIR-ATR data and chemometrics. Spectrochim Acta A Mol Biomol Spectrosc 2022; 279:121451. [PMID: 35675738 DOI: 10.1016/j.saa.2022.121451] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/01/2022] [Revised: 05/21/2022] [Accepted: 05/28/2022] [Indexed: 06/15/2023]
Abstract
Class identification and prediction of physicochemical variables of eight diesel fuel brands collected from several stations within the Atlanta metropolitan area in the State of Georgia were investigated using principal component analysis (PCA), partial least squares discriminant analysis (PLS2-DA), and partial least squares regression (PLSR) as modeling techniques. The fuels were from a common pipeline, therefore, assumed to have very similar characteristics. Ten FTIR-ATR spectra per fuel brand were collected over the 650 - 4000 cm-1 mid-infrared region, and the 80 x 3351 matrix was submitted to PCA to determine if there were any clusters. Following PCA, the 80 x 3351 matrix was split into a training matrix (56x3351) and a test matrix (24x3351). PLS2-DA models were built and evaluated for class identification using dummy variables (I,0) as input matrix. For physicochemical variable predictions, models were developed via PLSR using the FTIR-ATR spectra training matrix and physicochemical variables obtained from the Georgia Department of Agriculture Labs as input. Correlation coefficients of the eight fuels ranged from 0.9960 to 0.9998. PCA revealed all eight clusters of the diesel fuels, regardless of the tight correlation coefficients range. With a 1.0 ± 0.1 cut-off for fuel identification, the PLS2-DA models showed 100% correct predictions for four or five fuel brands, and 75% correct prediction for all eight fuel brands. PLSR predicted 100% correct physicochemical variables, with a RMSEP range of 0.019 to 1.132 for all 80 variables targeted.
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Affiliation(s)
- Huggins Z Msimanga
- Kennesaw State University, Department of Chemistry and Biochemistry, 370 Paulding Avenue NW, Kennesaw GA 30144, United States of America.
| | - Christopher R Dockery
- Kennesaw State University, Department of Chemistry and Biochemistry, 370 Paulding Avenue NW, Kennesaw GA 30144, United States of America.
| | - Deidre D Vandenbos
- Kennesaw State University, Department of Chemistry and Biochemistry, 370 Paulding Avenue NW, Kennesaw GA 30144, United States of America; Present Address: AkzoNobel Wood Coatings, 1431 Progress Avenue, High Point, NC 27260, United States of America.
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Park J, Kumar S, Han SH, Singh VK, Nam SH, Lee Y. Two-Step Partial Least Squares-Discriminant Analysis Modeling for Accurate Classification of Edible Sea Salt Products Using Laser-Induced Breakdown Spectroscopy. Appl Spectrosc 2022; 76:1042-1050. [PMID: 35311386 DOI: 10.1177/00037028221091581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Laser-induced breakdown spectroscopy (LIBS) has been widely applied to material classification in various fields, and partial least squares-discriminant analysis (PLS-DA) is one of the frequently used classical multivariate statistics to construct classification models based on the LIBS spectra. However, classification accuracy of the PLS-DA model is sensitive to the number of classes and their similarities. Considering this characteristic of PLS-DA, we suggest a two-step PLS-DA modeling approach to improve the classification accuracy. This strategy was demonstrated for a six-class problem in which six commercial edible sea salts produced in Japan, South Korea, and France are classified using their LIBS spectra. At the first step, test spectra were sorted into four classes and one extended class, composed of the two other most confusing classes, and then the test spectra in the extended class were further classified into each of the two constituent classes which were modeled separately from the other four classes. This two-step classification has been found to remarkably improve the PLS-DA classification accuracy by maximizing the difference between the confusing classes in the second-step modeling.
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Affiliation(s)
- Jeong Park
- Department of Chemistry, 34991Mokpo National University, Muan-gun, Korea
| | - Sandeep Kumar
- Spectrochemical Analysis Center for Organic and Inorganic Materials and Natural Products, 34991Mokpo National University, Muan-gun, Korea
| | - Song-Hee Han
- Division of Navigation Science, 34990Mokpo National Maritime University, Mokpo, Korea
| | - Vivek K Singh
- Department of Physics, University of Lucknow, Lucknow, India
| | - Sang-Ho Nam
- Department of Chemistry, 34991Mokpo National University, Muan-gun, Korea
- Spectrochemical Analysis Center for Organic and Inorganic Materials and Natural Products, 34991Mokpo National University, Muan-gun, Korea
| | - Yonghoon Lee
- Department of Chemistry, 34991Mokpo National University, Muan-gun, Korea
- Spectrochemical Analysis Center for Organic and Inorganic Materials and Natural Products, 34991Mokpo National University, Muan-gun, Korea
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Diehn S, Zimmermann B, Tafintseva V, Bağcıoğlu M, Kohler A, Ohlson M, Fjellheim S, Kneipp J. Discrimination of grass pollen of different species by FTIR spectroscopy of individual pollen grains. Anal Bioanal Chem 2020; 412:6459-6474. [PMID: 32350580 PMCID: PMC7442581 DOI: 10.1007/s00216-020-02628-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 03/11/2020] [Accepted: 03/28/2020] [Indexed: 02/06/2023]
Abstract
Fourier-transform infrared (FTIR) spectroscopy enables the chemical characterization and identification of pollen samples, leading to a wide range of applications, such as paleoecology and allergology. This is of particular interest in the identification of grass (Poaceae) species since they have pollen grains of very similar morphology. Unfortunately, the correct identification of FTIR microspectroscopy spectra of single pollen grains is hindered by strong spectral contributions from Mie scattering. Embedding of pollen samples in paraffin helps to retrieve infrared spectra without scattering artifacts. In this study, pollen samples from 10 different populations of five grass species (Anthoxanthum odoratum, Bromus inermis, Hordeum bulbosum, Lolium perenne, and Poa alpina) were embedded in paraffin, and their single grain spectra were obtained by FTIR microspectroscopy. Spectra were subjected to different preprocessing in order to suppress paraffin influence on spectral classification. It is shown that decomposition by non-negative matrix factorization (NMF) and extended multiplicative signal correction (EMSC) that utilizes a paraffin constituent spectrum, respectively, leads to good success rates for the classification of spectra with respect to species by a partial least square discriminant analysis (PLS-DA) model in full cross-validation for several species. PLS-DA, artificial neural network, and random forest classifiers were applied on the EMSC-corrected spectra using an independent validation to assign spectra from unknown populations to the species. Variation within and between species, together with the differences in classification results, is in agreement with the systematics within the Poaceae family. The results illustrate the great potential of FTIR microspectroscopy for automated classification and identification of grass pollen, possibly together with other, complementary methods for single pollen chemical characterization.
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Affiliation(s)
- Sabrina Diehn
- Department of Chemistry, Humboldt-Universität zu Berlin, Brook-Taylor-Straße 2, 12489, Berlin, Germany
| | - Boris Zimmermann
- Faculty of Science and Technology, Norwegian University of Life Sciences, 1432, Ås, Norway
| | - Valeria Tafintseva
- Faculty of Science and Technology, Norwegian University of Life Sciences, 1432, Ås, Norway
| | - Murat Bağcıoğlu
- Faculty of Science and Technology, Norwegian University of Life Sciences, 1432, Ås, Norway
| | - Achim Kohler
- Faculty of Science and Technology, Norwegian University of Life Sciences, 1432, Ås, Norway
| | - Mikael Ohlson
- Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, 1432, Ås, Norway
| | - Siri Fjellheim
- Faculty of Biosciences, Norwegian University of Life Sciences, 1432, Ås, Norway
| | - Janina Kneipp
- Department of Chemistry, Humboldt-Universität zu Berlin, Brook-Taylor-Straße 2, 12489, Berlin, Germany.
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Park MK, Choi HS, Kim YS, Cho IH. Comparison of volatile profiles in Fagopyrum esculentum (buckwheat) soksungjang prepared with different starter cultures during fermentation. Food Sci Biotechnol 2019; 28:1037-45. [PMID: 31275703 DOI: 10.1007/s10068-018-00549-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Revised: 12/26/2018] [Accepted: 12/28/2018] [Indexed: 10/27/2022] Open
Abstract
This study investigated the differences and changes in the volatile profiles of buckwheat soksungjang (BS) inoculated with multiple microbial starters (Lactobacillus brevis + Aspergillus oryzae, BS-LA vs. Lactobacillus brevis + Bacillus amyloliquefaciens, BS-LB) during fermentation using SPME coupled with GC-MS and partial least square-discriminant analysis. BS samples fermented for 5 weeks could be differentiated from other BS samples with shorter fermentation periods, and the BS-LA and BS-LB samples fermented for 5 weeks were separated. Acids, benzenes, and esters were main volatile compounds in both BS samples, however, their differences and changes were varied. The increase of 3-methylbutanoic acid was bigger in BS-LB than BS-LA, while the contents of 2- and 3-methylbutanal were relatively higher in BS-LA than BS-LB. Furthermore, the contents of esters of BS-LA significantly increased during fermentation. These results indicate that the volatile profiles of BS samples depend on the fermentation periods and the combination of microbial starters.
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10
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Zhang X, Li M, Cheng Z, Ma L, Zhao L, Li J. A comparison of electronic nose and gas chromatography-mass spectrometry on discrimination and prediction of ochratoxin A content in Aspergillus carbonarius cultured grape-based medium. Food Chem 2019; 297:124850. [PMID: 31253256 DOI: 10.1016/j.foodchem.2019.05.124] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2018] [Revised: 05/07/2019] [Accepted: 05/17/2019] [Indexed: 01/12/2023]
Abstract
This study investigated discrimination and prediction of ochratoxin A (OTA) in three Aspergillus carbonarius strains cultured grape-based medium using E-nose technology and GC-MS analysis. Results showed that these strains cultured medium samples were divided into four groups regarding their log 10 OTA value using an equispaced normal distribution analysis. Partial least squares-discriminant analysis (PLS-DA) revealed that GC-MS PLS-DA model only separated the low OTA level medium samples from the rest OTA level samples, whereas all the OTA level samples were segregated from each other using E-nose PLS-DA model. Partial least squares regression (PLSR) analysis indicated that an excellent prediction performance was established on the accumulation of OTA in these medium samples using E-nose PLSR, whereas GC-MS PLSR model showed a screening performance on the OTA formation. These indicated that E-nose analysis could be a reliable method on discriminating and predicting OTA in A. carbonarius strains under grape-based medium.
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Affiliation(s)
- Xiaoxu Zhang
- College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China; College of Food Engineering and Biotechnology, Tianjin University of Science and Technology, Tianjin 300457, China
| | - Menghua Li
- College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China
| | - Zhan Cheng
- College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China
| | - Liyan Ma
- College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China; Inspection & Testing Center for Agricultural Products Quality, Ministry of Agriculture, Beijing 100083, China; Key Laboratory of Safety Assessment of Genetically Modified Organism (Food Safety), Ministry of Agriculture, Beijing 100083, China
| | - Longlian Zhao
- College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
| | - Jingming Li
- College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China.
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Park MK, Choi HS, Kim YS, Cho IH. Change in profiles of volatile compounds from two types of Fagopyrum esculentum (buckwheat) soksungjang during fermentation. Food Sci Biotechnol 2018; 26:871-882. [PMID: 30263615 DOI: 10.1007/s10068-017-0115-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2016] [Revised: 03/25/2017] [Accepted: 04/04/2017] [Indexed: 11/28/2022] Open
Abstract
Fagopyrum esculentum (buckwheat) soksungjang is one of the traditional soybean pastes in Korea. This study profiled and compared volatile compounds between traditionally manufactured (TBS) and commercially modified buckwheat soksungjang (CBS) according to their fermentation periods. More volatile compounds were generated and non-uniform increases or decreases in volatiles were more common during TBS fermentation. In addition, the changes in and differences between the volatiles from TBS and CBS during the fermentation process (after 0, 1, 2, and 5 weeks) were investigated in partial least squares-discriminant analysis models. The changes were accelerated during CBS fermentation in comparison with TBS fermentation. Several major volatile compounds, such as methyl decanoate, 3-hydroxy-2,6-dimethylpyran-4-one, and methyl heptanoate were found in the final stage of fermentation in TBS, in contrary, tridecane, (Z)-hex-3-en-1-ol, furan-2-carbaldehyde, and ethyl tetradecanoate were contributed to the latest of fermentation in CBS.
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Affiliation(s)
- Min-Kyung Park
- 1Department of Food Science and Engineering, Ewha Womans University, Seoul, 03760 Korea
| | - Hye-Sun Choi
- 2Division of Agrofood Resources, Rural Development Administration, National Academy of Agricultural Science, Jeonjusi, Jeonbuk 54875 Korea
| | - Young-Suk Kim
- 1Department of Food Science and Engineering, Ewha Womans University, Seoul, 03760 Korea
| | - In Hee Cho
- 3Division of Food and Environmental Sciences, Wonkwang University, Iksansi, Jeonbuk 54538 Korea
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Chen H, Lin Z, Tan C. Fast discrimination of the geographical origins of notoginseng by near-infrared spectroscopy and chemometrics. J Pharm Biomed Anal 2018; 161:239-245. [PMID: 30172878 DOI: 10.1016/j.jpba.2018.08.052] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 08/22/2018] [Accepted: 08/25/2018] [Indexed: 11/29/2022]
Abstract
Notoginseng is a type of highly valued Traditional Chinese medicine (TCM) due to its hemostatic and cardiovascular functions. Notoginseng of Yunnan in China usually commands a premium price and is often the subject of fraudulent practices. The feasibility of combining near-infrared (NIR) spectroscopy with chemometrics was investigated to discriminate notoginseng of different geographical origins. A total of 250 samples of four different provinces in China were collected and divided equally into the training and test sets. Principal component analysis (PCA) was used for observing possible trend of grouping. Two chemometric algorithms including partial least squares-discriminant analysis (PLSDA) and soft independent modeling of class analogy (SIMCA) were used to construct the discriminant models. Standard normal variate (SNV) and first derivative were used for pre-processing spectra. On the independent test set, the PLSDA model outperforms the SIMCA model. When combining both pre-processing methods, the constructed PLSDA model achieved 100% sensitivity and 100% specificity on both the training set and the test set. It indicates that SNV+first derivative pre-processing and PLSDA algorithm can serve as the potential tool of fast discriminating the geographical origins of notoginseng.
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Affiliation(s)
- Hui Chen
- Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China; Hospital, Yibin University, Yibin, Sichuan 644000, China
| | - Zan Lin
- Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China; The First Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China
| | - Chao Tan
- Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China.
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Pérez-Guaita D, Kuligowski J, Lendl B, Wood BR, Quintás G. Assessment of discriminant models in infrared imaging using constrained repeated random sampling - Cross validation. Anal Chim Acta 2018; 1033:156-64. [PMID: 30172321 DOI: 10.1016/j.aca.2018.05.019] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2018] [Revised: 05/02/2018] [Accepted: 05/04/2018] [Indexed: 11/23/2022]
Abstract
Infrared (IR) imaging is an emerging and powerful approach for studying the molecular composition of cells and tissues. It is a non-destructive and phenotypic technique which combines label-free molecular specific information from cells and tissues provided by IR with spatial resolution, offering great potential in biochemical and biomedical research and routine applications. The application of multivariate discriminant analysis using bilinear models such as Partial Least Squares-Discriminant Analysis (PLS-DA) to IR images requires to unfold the spatial directions in a two-way matrix, resulting in a loss of spatial information and structure. In this article, first we evidence that internal validation methods such as repeated k-fold cross-validation (CV) can be overly optimistic when the pixel size of the image is lower than the lateral spatial resolution. Secondly, we propose a new approach for the unbiased internal evaluation of the model performance named COnstrained Repeated Random Subsampling-Cross Validation (CORRS-CV). This method is based on the generation of q training and test sub-sets using a constrained random sampling of n training pixels without replacement and it circumvents overly optimistic effects due to oversampling, providing more accurate and robust images. The approach can be applied in IR microscopy for the development of discriminant models to analyse underlying biochemical differences associated to anatomical and histopathological features in cells and tissues.
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Abstract
High-throughput proteomic experiments have raised the importance and complexity of bioinformatic analysis to extract useful information from raw data. Discriminant analysis is frequently used to identify differences among test groups of individuals or to describe combinations of discriminant variables. However, even in relatively large studies, the number of detected variables typically largely exceeds the number of samples and the classifiers should be thoroughly validated to assess their performance for new samples. Cross-validation is a widely approach when an external validation set is not available. In this chapter, different approaches for cross-validation are presented including relevant aspects that should be taken into account to avoid overly optimistic results and the assessment of the statistical significance of cross-validated figures of merit.
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Affiliation(s)
- Julia Kuligowski
- Neonatal Research Centre, Health Research Institute La Fe, Valencia, Spain
| | - David Pérez-Guaita
- Centre for Biospectroscopy, School of Chemistry, Monash University, Clayton, Australia
| | - Guillermo Quintás
- Safety and sustainability Division, Leitat Technological Center, Avda. Fernando Abril Martorell, 106, 46026, Valencia, Spain.
- Analytical Unit, Health Research Institute La Fe, Valencia, Spain.
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Abstract
A new liquid chromatography mass spectrometry (LC-MS) metabolomics strategy coupled to chemometric evaluation, including variable and biomarker selection, has been assessed as a tool to discriminate between control and stressed Saccharomyces cerevisiae yeast samples. Metabolic changes occurring during yeast culture at different temperatures (30 and 42 °C) were analysed and the complex data generated in profiling experiments were evaluated by different chemometric multivariate approaches. Multivariate curve resolution alternating least squares (MCR-ALS) was applied to full spectral scan LC-MS preprocessed data multisets arranged in augmented column-wise data matrices. The results showed that sectioning the MS-chromatograms in different windows and analysing them by MCR-ALS enabled the proper resolution of very complex coeluted chromatographic peaks. The investigation of possible relationships between MCR-ALS resolved chromatographic peak areas and culture temperature was then investigated by partial least squares discriminant analysis (PLS-DA). Selection of most relevant resolved chromatographic peaks associated to yeast culture temperature changes was achieved according to PLS-DA-Variable Importance in Projection scores. A metabolite identification workflow was developed utilizing MCR-ALS resolved pure MS spectra and high-resolution accurate mass measurements to confirm assigned structures based on entries in metabolite databases. A total of 65 metabolites were identified. A preliminary interpretation of these results indicates that the strategy described in this study can be proposed as a general tool to facilitate biomarker identification and modelling in similar untargeted metabolomic studies.
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Affiliation(s)
- Mireia Farrés
- Institute of Environmental Assessment and Water Research (IDAEA), Spanish Council for Scientific Research (CSIC), Jordi Girona 18-26, 08034 Barcelona, Spain
| | - Benjamí Piña
- Institute of Environmental Assessment and Water Research (IDAEA), Spanish Council for Scientific Research (CSIC), Jordi Girona 18-26, 08034 Barcelona, Spain
| | - Romà Tauler
- Institute of Environmental Assessment and Water Research (IDAEA), Spanish Council for Scientific Research (CSIC), Jordi Girona 18-26, 08034 Barcelona, Spain
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