1
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Wang G, Kong J, Leng T, Zhang W, Chen T, Xu X, Huang Z, Xie J. Metabolomics analysis based on UHPLC-QTOF-MS/MS to explore the synthesis mechanism and culture conditions optimization of Penicillium EF-2 exopolysaccharide. Int J Food Microbiol 2024; 423:110841. [PMID: 39059140 DOI: 10.1016/j.ijfoodmicro.2024.110841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 06/25/2024] [Accepted: 07/23/2024] [Indexed: 07/28/2024]
Abstract
Penicillium exopolysaccharide (EPS) inhibits galactose lectins and enhances immunity. However, EPS production is low and its synthesis mechanism remains unclear. Penicillium EF-2 strains with high EPS production were selected for this study, and Penicillium fermentation conditions were subsequently improved. The optimal culture conditions were 30 g/L lactose, 6 g/L yeast extract powder, 4 d seed age, 10 % inoculation amount, 3 d of secondary fermentation time, and the final EPS yield was 3.97 g/L. UHPLC-Q-TOF-MS/MS was used to explore the mechanism of EPS synthesis at the metabolic level. Optimal carbon source: lactose and optimal nitrogen source: yeast extract can provide precursors for EPS synthesis through related metabolic pathways. Moreover, regulating the energy, vitamin, and lipid metabolic pathways created favourable conditions for EPS synthesis and secretion. These findings explain the mechanism of EPS synthesis at the metabolic level and provide a theoretical basis for optimising and industrialising EPS production.
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Affiliation(s)
- Gang Wang
- State Key Laboratory of Food Science and Resources, Nanchang University, No. 235 Nanjing East Road, Nanchang 330047, China
| | - Jia Kong
- State Key Laboratory of Food Science and Resources, Nanchang University, No. 235 Nanjing East Road, Nanchang 330047, China
| | - Tuo Leng
- State Key Laboratory of Food Science and Resources, Nanchang University, No. 235 Nanjing East Road, Nanchang 330047, China
| | - Weidong Zhang
- State Key Laboratory of Food Science and Resources, Nanchang University, No. 235 Nanjing East Road, Nanchang 330047, China
| | - Ting Chen
- State Key Laboratory of Food Science and Resources, Nanchang University, No. 235 Nanjing East Road, Nanchang 330047, China
| | - Xizhe Xu
- State Key Laboratory of Food Science and Resources, Nanchang University, No. 235 Nanjing East Road, Nanchang 330047, China
| | - Zhibing Huang
- State Key Laboratory of Food Science and Resources, Nanchang University, No. 235 Nanjing East Road, Nanchang 330047, China; Sino-German Joint Research Institute, Nanchang University, No. 235 Nanjing East Road, Nanchang 330047, China.
| | - Jianhua Xie
- State Key Laboratory of Food Science and Resources, Nanchang University, No. 235 Nanjing East Road, Nanchang 330047, China.
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2
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Wanapat M, Dagaew G, Sommai S, Matra M, Suriyapha C, Prachumchai R, Muslykhah U, Phupaboon S. The application of omics technologies for understanding tropical plants-based bioactive compounds in ruminants: a review. J Anim Sci Biotechnol 2024; 15:58. [PMID: 38689368 PMCID: PMC11062008 DOI: 10.1186/s40104-024-01017-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Accepted: 02/29/2024] [Indexed: 05/02/2024] Open
Abstract
Finding out how diet impacts health and metabolism while concentrating on the functional qualities and bioactive components of food is the crucial scientific objective of nutritional research. The complex relationship between metabolism and nutrition could be investigated with cutting-edge "omics" and bioinformatics techniques. This review paper provides an overview of the use of omics technologies in nutritional research, with a particular emphasis on the new applications of transcriptomics, proteomics, metabolomics, and genomes in functional and biological activity research on ruminant livestock and products in the tropical regions. A wealth of knowledge has been uncovered regarding the regulation and use of numerous physiological and pathological processes by gene, mRNA, protein, and metabolite expressions under various physiological situations and guidelines. In particular, the components of meat and milk were assessed using omics research utilizing the various methods of transcriptomics, proteomics, metabolomics, and genomes. The goal of this review is to use omics technologies-which have been steadily gaining popularity as technological tools-to develop new nutritional, genetic, and leadership strategies to improve animal products and their quality control. We also present an overview of the new applications of omics technologies in cattle production and employ nutriomics and foodomics technologies to investigate the microbes in the rumen ecology. Thus, the application of state-of-the-art omics technology may aid in our understanding of how species and/or breeds adapt, and the sustainability of tropical animal production, in the long run, is becoming increasingly important as a means of mitigating the consequences of climate change.
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Affiliation(s)
- Metha Wanapat
- Tropical Feed Resources Research and Development Center (TROFREC), Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Gamonmas Dagaew
- Tropical Feed Resources Research and Development Center (TROFREC), Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Sukruthai Sommai
- Tropical Feed Resources Research and Development Center (TROFREC), Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Maharach Matra
- Tropical Feed Resources Research and Development Center (TROFREC), Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Chaichana Suriyapha
- Tropical Feed Resources Research and Development Center (TROFREC), Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Rittikeard Prachumchai
- Department of Animal Science, Faculty of Agricultural Technology, University of Technology Thanyaburi, Rajamangala Pathum Thani, 12130, Thailand
| | - Uswatun Muslykhah
- Tropical Feed Resources Research and Development Center (TROFREC), Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Srisan Phupaboon
- Tropical Feed Resources Research and Development Center (TROFREC), Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand.
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3
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Aspromonte J, Mascrez S, Eggermont D, Purcaro G. Solid-phase microextraction coupled to comprehensive multidimensional gas chromatography for food analysis. Anal Bioanal Chem 2024; 416:2221-2246. [PMID: 37999723 DOI: 10.1007/s00216-023-05048-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 10/22/2023] [Accepted: 11/09/2023] [Indexed: 11/25/2023]
Abstract
Solid-phase microextraction and comprehensive multidimensional gas chromatography represent two milestone innovations that occurred in the field of separation science in the 1990s. They have a common root in their introduction and have found a perfect coupling in their evolution and applications. This review will focus on food analysis, where the paradigm has changed significantly over time, moving from a targeted analysis, focusing on a limited number of analytes at the time, to a more holistic approach for assessing quality in a larger sense. Indeed, not only some major markers or contaminants are considered, but a large variety of compounds and their possible interaction, giving rise to the field of foodomics. In order to obtain such detailed information and to answer more sophisticated questions related to food quality and authenticity, the use of SPME-GC × GC-MS has become essential for the comprehensive analysis of volatile and semi-volatile analytes. This article provides a critical review of the various applications of SPME-GC × GC in food analysis, emphasizing the crucial role this coupling plays in this field. Additionally, this review dwells on the importance of appropriate data treatment to fully harness the results obtained to draw accurate and meaningful conclusions.
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Affiliation(s)
- Juan Aspromonte
- Laboratorio de Investigación y Desarrollo de Métodos Analíticos, LIDMA, Facultad de Ciencias Exactas (Universidad Nacional de La Plata, CIC-PBA, CONICET), Calle 47 Esq. 115, 1900, La Plata, Argentina
| | - Steven Mascrez
- Gembloux Agro-Bio Tech, University of Liège, Passage Des Déportés, 2, B-5030, Gembloux, Belgium
| | - Damien Eggermont
- Gembloux Agro-Bio Tech, University of Liège, Passage Des Déportés, 2, B-5030, Gembloux, Belgium
| | - Giorgia Purcaro
- Gembloux Agro-Bio Tech, University of Liège, Passage Des Déportés, 2, B-5030, Gembloux, Belgium.
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4
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Tengstrand E, Måge I, Solberg LE, Afseth NK, Wold JP. Diagnosing the cage of covariance to increase understanding and robustness of spectroscopic calibration models. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 310:123877. [PMID: 38241929 DOI: 10.1016/j.saa.2024.123877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 01/08/2024] [Accepted: 01/08/2024] [Indexed: 01/21/2024]
Abstract
When vibrational spectroscopy is used for quantification purposes, multivariate analysis is often used to extract information from covariances between the spectra and any given reference values. In complex samples, there is a high risk that the constituents covary with each other. In such scenarios many methods may confuse the analytes and use signal from several analytes, rather than just the analyte of interest. While this allows the method to use more signal, and thus have a better effective signal-to-noise ratio, it also makes them less robust to changes to the chemical composition in the samples. This effect has been termed the cage of covariance. In order to avoid cage of covariance to affect predictive performances, it is highly important to have simple diagnostic tools to analyze and review this effect. Therefore, in the present paper, a systematic overview of tools for diagnosing and quantifying the cage of covariance in spectroscopic calibration models is provided. A collection of previously published methods with some expansions is provided, as well as two completely new tools: covariance ratio and virtual spiking. Practical applications of the tools on three different datasets are also shown.
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Affiliation(s)
- Erik Tengstrand
- Nofima AS - Norwegian Institute of Food, Fisheries and Aquaculture Research, PB 210, NO-1431 Ås, Norway.
| | - Ingrid Måge
- Nofima AS - Norwegian Institute of Food, Fisheries and Aquaculture Research, PB 210, NO-1431 Ås, Norway
| | - Lars Erik Solberg
- Nofima AS - Norwegian Institute of Food, Fisheries and Aquaculture Research, PB 210, NO-1431 Ås, Norway
| | - Nils Kristian Afseth
- Nofima AS - Norwegian Institute of Food, Fisheries and Aquaculture Research, PB 210, NO-1431 Ås, Norway
| | - Jens Petter Wold
- Nofima AS - Norwegian Institute of Food, Fisheries and Aquaculture Research, PB 210, NO-1431 Ås, Norway
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5
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Cozzolino D, Chapman J. Advances, limitations, and considerations on the use of vibrational spectroscopy towards the development of management decision tools in food safety. Anal Bioanal Chem 2024; 416:611-620. [PMID: 37542534 DOI: 10.1007/s00216-023-04849-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Revised: 07/05/2023] [Accepted: 07/06/2023] [Indexed: 08/07/2023]
Abstract
Food safety and food security are two of the main concerns for the modern food manufacturing industry. Disruptions in the food supply and value chains have created the need to develop agile screening tools that will allow the detection of food pathogens, spoilage microorganisms, microbial contaminants, toxins, herbicides, and pesticides in agricultural commodities, natural products, and food ingredients. Most of the current routine analytical methods used to detect and identify microorganisms, herbicides, and pesticides in food ingredients and products are based on the use of reliable and robust immunological, microbiological, and biochemical techniques (e.g. antigen-antibody interactions, extraction and analysis of DNA) and chemical methods (e.g. chromatography). However, the food manufacturing industries are demanding agile and affordable analytical methods. The objective of this review is to highlight the advantages and limitations of the use of vibrational spectroscopy combined with chemometrics as proxy to evaluate and quantify herbicides, pesticides, and toxins in foods.
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Affiliation(s)
- Daniel Cozzolino
- The University of Queensland, Centre for Nutrition and Food Sciences, Queensland Alliance for Agriculture and Food Innovation, St. Lucia, Brisbane, QLD, 4072, Australia.
| | - James Chapman
- School of Science, RMIT University, GPO Box 2476, Melbourne, VIC, 3001, Australia
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6
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Lacalle-Bergeron L, Goterris-Cerisuelo R, Beltran J, Sancho JV, Navarro-Moreno C, Martinez-Garcia F, Portolés T. Untargeted metabolomics approach using UHPLC-IMS-QTOF MS for surface body samples to identify low-volatility chemosignals related to maternal care in mice. Talanta 2023; 258:124389. [PMID: 36867958 DOI: 10.1016/j.talanta.2023.124389] [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: 11/18/2022] [Revised: 02/14/2023] [Accepted: 02/19/2023] [Indexed: 02/25/2023]
Abstract
The present study is focused on the determination of low-volatile chemosignals excreted or secreted by mouse pups in their early days of life involved in maternal care induction in mice adult females. Untargeted metabolomics was employed to differentiate between samples collected with swabs from facial and anogenital area from neonatal mouse pups receiving maternal care (first two weeks of life) and the elder mouse pups in the weaning period (4th week old). The sample extracts were analysed by ultra-high pressure liquid chromatography (UHPLC) coupled to ion mobility separation (IMS) in combination with high resolution mass spectrometry (HRMS). After data processing with Progenesis QI and multivariate statistical analysis, five markers present in the first two weeks of mouse pups life and putatively involved in materno-filial chemical communication were tentatively identified: arginine, urocanic acid, erythro-sphingosine (d17:1), sphingosine (d18:1) and sphinganine. The four-dimensional data and the tools associated to the additional structural descriptor obtained by IMS separation were of great help in the compound identification. The results demonstrated the great potential of UHPLC-IMS-HRMS based untargeted metabolomics to identity putative pheromones in mammals.
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Affiliation(s)
- Leticia Lacalle-Bergeron
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water (IUPA), Universitat Jaume I, Av. Sos Baynat S/N, 12071, Castellón de la Plana, Spain
| | - Rafael Goterris-Cerisuelo
- Laboratory of Functional Neuroanatomy (Unitat Mixta NeuroFun-UV-UJI), Predepartamental Unit of Medicine, Universitat Jaume I, Av. Sos Baynat S/N, 12071, Castellón de la Plana, Spain
| | - Joaquin Beltran
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water (IUPA), Universitat Jaume I, Av. Sos Baynat S/N, 12071, Castellón de la Plana, Spain
| | - Juan Vicente Sancho
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water (IUPA), Universitat Jaume I, Av. Sos Baynat S/N, 12071, Castellón de la Plana, Spain
| | - Cinta Navarro-Moreno
- Laboratory of Functional Neuroanatomy (Unitat Mixta NeuroFun-UV-UJI), Predepartamental Unit of Medicine, Universitat Jaume I, Av. Sos Baynat S/N, 12071, Castellón de la Plana, Spain
| | - Fernando Martinez-Garcia
- Laboratory of Functional Neuroanatomy (Unitat Mixta NeuroFun-UV-UJI), Predepartamental Unit of Medicine, Universitat Jaume I, Av. Sos Baynat S/N, 12071, Castellón de la Plana, Spain
| | - Tania Portolés
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water (IUPA), Universitat Jaume I, Av. Sos Baynat S/N, 12071, Castellón de la Plana, Spain.
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7
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Zou W, Peng Y, Yang D, Zuo J, Li Y, Guo Q. An Intelligent Detector for Sensing Pork Freshness In Situ Based on a Multispectral Technique. BIOSENSORS 2022; 12:998. [PMID: 36354507 PMCID: PMC9688451 DOI: 10.3390/bios12110998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 11/07/2022] [Accepted: 11/07/2022] [Indexed: 06/16/2023]
Abstract
Fresh pork is prone to spoilage during storage, transportation, and sale, resulting in reduced freshness. The total viable count (TVC) and total volatile basic nitrogen (TVB-N) content are key indicators for evaluating the freshness of fresh pork, and when they reach unacceptable limits, this seriously threatens dietary safety. To realize the on-site, low-cost, rapid, and non-destructive testing and evaluation of fresh pork freshness, a miniaturized detector was developed based on a cost-effective multi-channel spectral sensor. The partial least squares discriminant analysis (PLS-DA) model was used to distinguish fresh meat from deteriorated meat. The detector consists of microcontroller, light source, multi-channel spectral sensor, heat-dissipation modules, display system, and battery. In this study, the multispectral data of pork samples with different freshness levels were collected by the developed detector, and its ability to distinguish pork freshness was based on different spectral shape features (SSF) (spectral ratio (SR), spectral difference (SD), and normalized spectral intensity difference (NSID)) were compared. The experimental results show that compared with the original multispectral modeling, the performance of the model based on spectral shape features is significantly improved. The model established by optimizing the spectral shape feature variables has the best performance, and the discrimination accuracy of its prediction set is 91.67%. In addition, the validation accuracy of the optimal model was 86.67%, and its sensitivity and variability were 87.50% and 85.71%, respectively. The results show that the detector developed in this study is cost-effective, compact in its structure, stable in its performance, and suitable for the on-site digital rapid non-destructive testing of freshness during the storage, transportation, and sale of fresh pork.
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Wang J, Li X, Wu Y, Qu F, Liu L, Wang B, Wang P, Zhang X. HS−SPME/GC−MS Reveals the Season Effects on Volatile Compounds of Green Tea in High−Latitude Region. Foods 2022; 11:foods11193016. [PMID: 36230092 PMCID: PMC9563017 DOI: 10.3390/foods11193016] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 09/20/2022] [Accepted: 09/23/2022] [Indexed: 11/19/2022] Open
Abstract
This study investigates the volatile compounds of green tea produced with different leaves from spring, summer, and autumn in high−latitude region. A total of 95 volatile compounds were identified by gas chromatography–mass spectrometry (GC–MS). Spring, summer and autumn green tea contained 68, 72 and 82 volatile compounds, respectively. Principal component analysis (PCA), partial least squares−discrimination analysis (PLS−DA), and hierarchical cluster analysis (HCA) classified the samples and showed the difference. And 32 key characteristic components were screened out based on variable importance in the projection (VIP) values higher than 1.0. The characteristic volatile compounds of spring green tea including 18 components, such as geranylacetone, phenethyl alcohol, geraniol, β−ionone, jasmone, 1−octen−3−ol and longifolene. 13 components such as 2−methylfuran, indole, 1−octanol, D−limonene and ethanethiol were the key compounds in summer green tea. And 2,4,6−trimethylstyrene was the major differential volatile compounds in autumn green tea. The results increase our knowledge of green tea in different seasons and provide a theoretical basis for production control of green tea.
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Affiliation(s)
- Jie Wang
- College of Horticulture, Qingdao Agricultural University, Qingdao 266109, China
| | - Xiaohan Li
- College of Horticulture, Qingdao Agricultural University, Qingdao 266109, China
| | - Ying Wu
- College of Agriculture, Tennessee State University, Nashville, TN 37209, USA
| | - Fengfeng Qu
- College of Horticulture, Qingdao Agricultural University, Qingdao 266109, China
| | - Lei Liu
- Bureau of Agriculture and Rural Affairs of Laoshan District, Qingdao 266061, China
| | - Baoyi Wang
- College of Horticulture, Qingdao Agricultural University, Qingdao 266109, China
| | - Peiqiang Wang
- College of Horticulture, Qingdao Agricultural University, Qingdao 266109, China
| | - Xinfu Zhang
- College of Horticulture, Qingdao Agricultural University, Qingdao 266109, China
- Correspondence: ; Tel.: +86-13969681993
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Allegretta I, Squeo G, Gattullo CE, Porfido C, Cicchetti A, Caponio F, Cesco S, Nicoletto C, Terzano R. TXRF spectral information enhanced by multivariate analysis: A new strategy for food fingerprint. Food Chem 2022; 401:134124. [PMID: 36126374 DOI: 10.1016/j.foodchem.2022.134124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 08/01/2022] [Accepted: 09/02/2022] [Indexed: 11/18/2022]
Abstract
The increased costumers' request of safe and high-quality food products makes food traceability a priority for frauds identification and quality certification. Elemental profiling is one of the strategies used for food traceability, and TXRF spectroscopy is widely used in food analysis even if its potentialities have not been fully investigated. In this work, a new method for food traceability using directly TXRF spectra coupled with multivariate analyses, was tested. Twenty-four different beans' genotypes (Phaseolus vulgaris L.) grown onto two different sites have been studied. After the development of the method for beans' analysis, TXRF spectra were collected and processed with PCA combined with SNV and GLSW filter obtaining a perfect clustering of the seeds according to their geographical origin. Finally, using PLS-DA, beans were correctly classified demonstrating that TXRF spectra can be successfully used as fingerprint for food/seed traceability and that elemental quantification procedure is not necessary to this aim.
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Affiliation(s)
- Ignazio Allegretta
- Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Via G. Amendola 165/A, 70126 Bari, Italy.
| | - Giacomo Squeo
- Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Via G. Amendola 165/A, 70126 Bari, Italy
| | - Concetta Eliana Gattullo
- Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Via G. Amendola 165/A, 70126 Bari, Italy
| | - Carlo Porfido
- Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Via G. Amendola 165/A, 70126 Bari, Italy
| | - Antonio Cicchetti
- Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Via G. Amendola 165/A, 70126 Bari, Italy
| | - Francesco Caponio
- Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Via G. Amendola 165/A, 70126 Bari, Italy
| | - Stefano Cesco
- Faculty of Science and Technology, Free University of Bozen-Bolzano, Piazza Università 5, 39100 Bolzano, Italy
| | - Carlo Nicoletto
- Department of Agronomy, Food, Natural Resources, Animals, and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy
| | - Roberto Terzano
- Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Via G. Amendola 165/A, 70126 Bari, Italy
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10
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Tarapoulouzi M, Ortone V, Cinti S. Heavy metals detection at chemometrics-powered electrochemical (bio)sensors. Talanta 2022; 244:123410. [DOI: 10.1016/j.talanta.2022.123410] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 03/21/2022] [Accepted: 03/25/2022] [Indexed: 01/04/2023]
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11
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Li F, Zhang J, Wang Y. Vibrational Spectroscopy Combined with Chemometrics in Authentication of Functional Foods. Crit Rev Anal Chem 2022; 54:333-354. [PMID: 35533108 DOI: 10.1080/10408347.2022.2073433] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Many foods have both edible and medical importance and are appreciated as functional foods, preventing diseases. However, due to unscrupulous vendors and imperfect market supervision mechanisms, curative foods are prone to adulteration or some other events that harm the interests of consumers. However, traditional analytical methods are unsuitable and expensive for a broad and complex application. Therefore, people urgently need a fast, efficient, and accurate detection method to protect self-interests. Recently, the study of target samples by vibration spectrum shows strong qualitative and quantitative ability. The model established by platform technology combined with the stoichiometric analysis method can obtain better parameters, which it has good robustness and can detect functional food efficiently, quickly and nondestructive. The review compared and prospect five different vibrational spectroscopic techniques (near-infrared, Fourier transform infrared, Raman, hyperspectral imaging spectroscopy and Terahertz spectroscopy). In order to better solve some of the actual situations faced by certification, we explore and through relevant research and investigation to appropriately highlight the applicability and importance of technology combined with chemometrics in functional food authentication. There are four categories of authentication discussed: functional food authenticated in source, processing method, fraud and ingredient ratio. This paper provides an innovative process for the authentication of functional food, which has a meaningful reference value for future review or scientific research of relevant departments.
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Affiliation(s)
- Fengjiao Li
- Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, China
- School of Agriculture, Yunnan University, Kunming, China
| | - Jinyu Zhang
- Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, China
| | - Yuanzhong Wang
- Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, China
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12
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Data Fusion Approaches for the Characterization of Musts and Wines Based on Biogenic Amine and Elemental Composition. SENSORS 2022; 22:s22062132. [PMID: 35336301 PMCID: PMC8950699 DOI: 10.3390/s22062132] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 03/05/2022] [Accepted: 03/07/2022] [Indexed: 02/04/2023]
Abstract
Samples from various winemaking stages of the production of sparkling wines using different grape varieties were characterized based on the profile of biogenic amines (BAs) and the elemental composition. Liquid chromatography with fluorescence detection (HPLC-FLD) combined with precolumn derivatization with dansyl chloride was used to quantify BAs, while inductively coupled plasma (ICP) techniques were applied to determine a wide range of elements. Musts, base wines, and sparkling wines were analyzed accordingly, and the resulting data were subjected to further chemometric studies to try to extract information on oenological practices, product quality, and varieties. Although good descriptive models were obtained when considering each type of data separately, the performance of data fusion approaches was assessed as well. In this regard, low-level and mid-level approaches were evaluated, and from the results, it was concluded that more comprehensive models can be obtained when joining data of different natures.
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Wang R, Sun J, Lassabliere B, Yu B, Liu SQ. UPLC-Q-TOF-MS based metabolomics and chemometric analyses for green tea fermented with Saccharomyces boulardii CNCM I-745 and Lactiplantibacillus plantarum 299V. Curr Res Food Sci 2022; 5:471-478. [PMID: 35252880 PMCID: PMC8892000 DOI: 10.1016/j.crfs.2022.02.012] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 01/07/2022] [Accepted: 02/20/2022] [Indexed: 10/27/2022] Open
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14
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Buvé C, Saeys W, Rasmussen MA, Neckebroeck B, Hendrickx M, Grauwet T, Van Loey A. Application of multivariate data analysis for food quality investigations: An example-based review. Food Res Int 2022; 151:110878. [PMID: 34980408 DOI: 10.1016/j.foodres.2021.110878] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 11/29/2021] [Accepted: 12/04/2021] [Indexed: 11/15/2022]
Abstract
These days, large multivariate data sets are common in the food research area. This is not surprising as food quality, which is important for consumers, and its changes are the result of a complex interplay of multiple compounds and reactions. In order to comprehensively extract information from these data sets, proper data analysis tools should be applied. The application of multivariate data analysis (MVDA) is therefore highly recommended. However, at present the use of MVDA for food quality investigations is not yet fully explored. This paper focusses on a number of MVDA methods (PCA (Principal Component Analysis), PLS (Partial Least Squares Regression), PARAFAC (Parallel Factor Analysis) and ASCA (ANOVA Simultaneous Component Analysis)) useful for food quality investigations. The terminology, main steps and the theoretical basis of each method will be explained. As this is an example-based review, each method was applied on the same experimental data set to give the reader an idea about each selected MVDA method and to make a comparison between the outcomes. Numerous MVDA methods are available in literature. Which method to select depends on the data set and objective. PCA should be the first choice for data exploration of two-dimensional data. For predictive purposes, PLS is the most appropriate method. Given an underlying experimental design, ASCA takes into account both the relation between the different variables and the design factors. In case of a multi-way data set, PARAFAC can be used for data exploration. While these methods have already proven their value in research, there is a need to further explore their potential to investigate the complex interplay of compounds and reactions contributing to food quality. With this work we would like to encourage food scientists with no or limited knowledge of MVDA to get some first insights into the selected methods.
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Affiliation(s)
- Carolien Buvé
- KU Leuven Department of Microbial and Molecular Systems, Laboratory of Food Technology, Kasteelpark Arenberg 22 Box 2457, 3001 Leuven, Belgium
| | - Wouter Saeys
- KU Leuven Department of Biosystems, MeBioS division, Kasteelpark Arenberg 30, 3001 Leuven, Belgium
| | - Morten Arendt Rasmussen
- University of Copenhagen, Department of Food Science, Faculty of Science, Rolighedsvej 26, 1958 Frederiksberg, Denmark; COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Bram Neckebroeck
- KU Leuven Department of Microbial and Molecular Systems, Laboratory of Food Technology, Kasteelpark Arenberg 22 Box 2457, 3001 Leuven, Belgium
| | - Marc Hendrickx
- KU Leuven Department of Microbial and Molecular Systems, Laboratory of Food Technology, Kasteelpark Arenberg 22 Box 2457, 3001 Leuven, Belgium
| | - Tara Grauwet
- KU Leuven Department of Microbial and Molecular Systems, Laboratory of Food Technology, Kasteelpark Arenberg 22 Box 2457, 3001 Leuven, Belgium
| | - Ann Van Loey
- KU Leuven Department of Microbial and Molecular Systems, Laboratory of Food Technology, Kasteelpark Arenberg 22 Box 2457, 3001 Leuven, Belgium.
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15
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Detection of Foreign Materials on Broiler Breast Meat Using a Fusion of Visible Near-Infrared and Short-Wave Infrared Hyperspectral Imaging. APPLIED SCIENCES-BASEL 2021. [DOI: 10.3390/app112411987] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Foreign material (FM) found on a poultry product lowers the quality and safety of the product. We developed a fusion method combining two hyperspectral imaging (HSI) modalities in the visible-near infrared (VNIR) range of 400–1000 nm and the short-wave infrared (SWIR) range of 1000–2500 nm for the detection of FMs on the surface of fresh raw broiler breast fillets. Thirty different types of FMs that could be commonly found in poultry processing plants were used as samples and prepared in two different sizes (5 × 5 mm2 and 2 × 2 mm2). The accuracies of the developed Fusion model for detecting 2 × 2 mm2 pieces of polymer, wood, and metal were 95%, 95%, and 81%, respectively, while the detection accuracies of the Fusion model for detecting 5 × 5 mm2 pieces of polymer, wood, and metal were all 100%. The performance of the Fusion model was higher than the VNIR- and SWIR-based detection models by 18% and 5%, respectively, when F1 scores were compared, and by 38% and 5%, when average detection rates were compared. The study results suggested that the fusion of two HSI modalities could detect FMs more effectively than a single HSI modality.
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16
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Yang M, Li J, Zhao C, Xiao H, Fang X, Zheng J. LC-Q-TOF-MS/MS detection of food flavonoids: principle, methodology, and applications. Crit Rev Food Sci Nutr 2021:1-21. [PMID: 34672231 DOI: 10.1080/10408398.2021.1993128] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Flavonoids have been attracting increasing research interest because of their multiple health promoting effects. However, many flavonoids with similar structures are present in foods, often at low concentrations, which increases the difficulty of their separation and identification. Liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (LC-Q-TOF-MS/MS) has become one of the most widely used techniques for flavonoid detection. LC-Q-TOF-MS/MS can achieve highly efficient separation by LC; it also provides structural information regarding flavonoids by Q-TOF-MS/MS. This review presents a comprehensive summary of the scientific principles and detailed methodologies (e.g., qualitative determination, quantitative determination, and data processing) of LC-Q-TOF-MS/MS specifically for food flavonoids. It also discusses the recent applications of LC-Q-TOF-MS/MS in determination of flavonoid types and contents in agricultural products, changes in their structures and contents during food processing, and metabolism in vivo after consumption. Moreover, it proposes necessary technological improvements and potential applications. This review would facilitate the scientific understanding of theory and technique of LC-Q-TOF-MS/MS for flavonoid detection, and promote its applications in food and health industry.
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Affiliation(s)
- Minke Yang
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing, China.,College of Food Science, South China Agricultural University, Guangzhou, China
| | - Juan Li
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Chengying Zhao
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing, China.,Guangdong Province Key Laboratory of Nutraceuticals and Functional Foods, College of Food Science, South China Agricultural University, Guangzhou, Guangdong, China
| | - Hang Xiao
- Department of Food Science, University of Massachusetts, Amherst, Massachusetts, USA
| | - Xiang Fang
- College of Food Science, South China Agricultural University, Guangzhou, China.,Guangdong Province Key Laboratory of Nutraceuticals and Functional Foods, College of Food Science, South China Agricultural University, Guangzhou, Guangdong, China
| | - Jinkai Zheng
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing, China.,Department of Food Science, University of Massachusetts, Amherst, Massachusetts, USA
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17
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Klein-Junior LC, de Souza MR, Viaene J, Bresolin TMB, de Gasper AL, Henriques AT, Heyden YV. Quality Control of Herbal Medicines: From Traditional Techniques to State-of-the-art Approaches. PLANTA MEDICA 2021; 87:964-988. [PMID: 34412146 DOI: 10.1055/a-1529-8339] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Herbal medicines are important options for the treatment of several illnesses. Although their therapeutic applicability has been demonstrated throughout history, several concerns about their safety and efficacy are raised regularly. Quality control of articles of botanical origin, including plant materials, plant extracts, and herbal medicines, remains a challenge. Traditionally, qualitative (e.g., identification and chromatographic profile) and quantitative (e.g., content analyses) markers are applied for this purpose. The compound-oriented approach may stand alone in some cases (e.g., atropine in Atropa belladonna). However, for most plant materials, plant extracts, and herbal medicines, it is not possible to assure quality based only on the content or presence/absence of one (sometimes randomly selected) compound. In this sense, pattern-oriented approaches have been extensively studied, introducing the use of multivariate data analysis on chromatographic/spectroscopic fingerprints. The use of genetic methods for plant material/plant extract authentication has also been proposed. In this study, traditional approaches are reviewed, although the focus is on the applicability of fingerprints for quality control, highlighting the most used approaches, as well as demonstrating their usefulness. The literature review shows that a pattern-oriented approach may be successfully applied to the quality assessment of articles of botanical origin, while also providing directions for a compound-oriented approach and a rational marker selection. These observations indicate that it may be worth considering to include fingerprints and their data analysis in the regulatory framework for herbal medicines concerning quality control since this is the foundation of the holistic view that these complex products demand.
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Affiliation(s)
- Luiz C Klein-Junior
- School of Health Sciences, Universidade do Vale do Itajaí - UNIVALI, Itajaí/SC, Brazil
| | - Maira R de Souza
- Laboratory of Pharmacognosy and Quality Control of Phytomedicines, Faculty of Pharmacy, Universidade Federal do Rio Grande do Sul-UFRGS, Porto Alegre/RS, Brazil
| | - Johan Viaene
- Department of Analytical Chemistry, Applied Chemometrics and Molecular Modelling, Center for Pharmaceutical Research (CePhaR), Vrije Universiteit Brussel - VUB, Brussels, Belgium
| | - Tania M B Bresolin
- School of Health Sciences, Universidade do Vale do Itajaí - UNIVALI, Itajaí/SC, Brazil
| | - André L de Gasper
- Herbarium Dr. Roberto Miguel Klein, Department of Natural Sciences, Universidade Regional de Blumenau - FURB, Blumenau/SC, Brazil
| | - Amélia T Henriques
- Laboratory of Pharmacognosy and Quality Control of Phytomedicines, Faculty of Pharmacy, Universidade Federal do Rio Grande do Sul-UFRGS, Porto Alegre/RS, Brazil
| | - Yvan Vander Heyden
- Department of Analytical Chemistry, Applied Chemometrics and Molecular Modelling, Center for Pharmaceutical Research (CePhaR), Vrije Universiteit Brussel - VUB, Brussels, Belgium
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18
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Recent advances in assessing qualitative and quantitative aspects of cereals using nondestructive techniques: A review. Trends Food Sci Technol 2021. [DOI: 10.1016/j.tifs.2021.08.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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19
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Diving Deep into the Data: A Review of Deep Learning Approaches and Potential Applications in Foodomics. Foods 2021; 10:foods10081803. [PMID: 34441579 PMCID: PMC8392494 DOI: 10.3390/foods10081803] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 07/30/2021] [Accepted: 08/02/2021] [Indexed: 01/18/2023] Open
Abstract
Deep learning is a trending field in bioinformatics; so far, mostly known for image processing and speech recognition, but it also shows promising possibilities for data processing in food analysis, especially, foodomics. Thus, more and more deep learning approaches are used. This review presents an introduction into deep learning in the context of metabolomics and proteomics, focusing on the prediction of shelf-life, food authenticity, and food quality. Apart from the direct food-related applications, this review summarizes deep learning for peptide sequencing and its context to food analysis. The review’s focus further lays on MS (mass spectrometry)-based approaches. As a result of the constant development and improvement of analytical devices, as well as more complex holistic research questions, especially with the diverse and complex matrix food, there is a need for more effective methods for data processing. Deep learning might offer meeting this need and gives prospect to deal with the vast amount and complexity of data.
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20
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Parinet J. Prediction of pesticide retention time in reversed-phase liquid chromatography using quantitative-structure retention relationship models: A comparative study of seven molecular descriptors datasets. CHEMOSPHERE 2021; 275:130036. [PMID: 33676277 DOI: 10.1016/j.chemosphere.2021.130036] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 02/16/2021] [Accepted: 02/17/2021] [Indexed: 06/12/2023]
Abstract
Predicting chromatographic retention times of pesticides has become more and more important for suspect and non-target screening. Indeed, high-resolution mass spectrometry hyphenated (HRMS) to liquid chromatography (LC) are of growing interest for research and monitoring of pesticides, their metabolites and transformation products. The development of quantitative structure-retention relationship models require selecting the most adequate and best set of molecular descriptors and the best machine-learning algorithm. Here, we used seven molecular descriptor sets extracted from four well-known studies and applied them to roughly 800 pesticides and their chromatographic reversed-phase retention times. We used and optimized five different machine-learning algorithms with these descriptor sets to carry out predictions. Our results show that a support-vector machine regression algorithm with only eight molecular descriptors gave the best compromise between the number of molecular descriptors, processing time and model complexity to optimize prediction performance for this specific gradient LC method.
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Affiliation(s)
- Julien Parinet
- Université de Paris-Est, ANSES, Laboratory for Food Safety, 94700, Maisons-Alfort, France.
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21
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Analytical Methods for Extraction and Identification of Primary and Secondary Metabolites of Apple (Malus domestica) Fruits: A Review. SEPARATIONS 2021. [DOI: 10.3390/separations8070091] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Apples represent a greater proportion of the worldwide fruit supply, due to their availability on the market and to the high number of existing cultivar varieties and apple-based products (fresh fruit, fruit juice, cider and crushed apples). Several studies on apple fruit metabolites are available, with most of them focusing on their healthy properties’ evaluation. In general, the metabolic profile of apple fruits strongly correlates with most of their peculiar characteristics, such as taste, flavor and color. At the same time, many bioactive molecules could be identified as markers of a specific apple variety. Therefore, a complete description of the analytical protocols commonly used for apple metabolites’ characterization and quantification could be useful for researchers involved in the identification of new phytochemical compounds from different apple varieties. This review describes the analytical methods published in the last ten years, in order to analyze the most important primary and secondary metabolites of Malus domestica fruits. In detail, this review gives an account of the spectrophotometric, chromatographic and mass spectrometric methods. A discussion on the quantitative and qualitative analytical shortcomings for the identification of sugars, fatty acids, polyphenols, organic acids, carotenoids and terpenes found in apple fruits is reported.
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22
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Munekata PES, Pateiro M, López-Pedrouso M, Gagaoua M, Lorenzo JM. Foodomics in meat quality. Curr Opin Food Sci 2021. [DOI: 10.1016/j.cofs.2020.10.003] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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23
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A Metabolomic Approach to Beer Characterization. Molecules 2021; 26:molecules26051472. [PMID: 33800512 PMCID: PMC7962951 DOI: 10.3390/molecules26051472] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 03/04/2021] [Accepted: 03/04/2021] [Indexed: 11/16/2022] Open
Abstract
The consumers’ interest towards beer consumption has been on the rise during the past decade: new approaches and ingredients get tested, expanding the traditional recipe for brewing beer. As a consequence, the field of “beeromics” has also been constantly growing, as well as the demand for quick and exhaustive analytical methods. In this study, we propose a combination of nuclear magnetic resonance (NMR) spectroscopy and chemometrics to characterize beer. 1H-NMR spectra were collected and then analyzed using chemometric tools. An interval-based approach was applied to extract chemical features from the spectra to build a dataset of resolved relative concentrations. One aim of this work was to compare the results obtained using the full spectrum and the resolved approach: with a reasonable amount of time needed to obtain the resolved dataset, we show that the resolved information is comparable with the full spectrum information, but interpretability is greatly improved.
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24
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Data processing strategies for non-targeted analysis of foods using liquid chromatography/high-resolution mass spectrometry. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2021.116188] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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25
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Modupalli N, Naik M, Sunil C, Natarajan V. Emerging non-destructive methods for quality and safety monitoring of spices. Trends Food Sci Technol 2021. [DOI: 10.1016/j.tifs.2020.12.021] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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26
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Jimenez-Carvelo AM, Cuadros-Rodríguez L. Data mining/machine learning methods in foodomics. Curr Opin Food Sci 2021. [DOI: 10.1016/j.cofs.2020.09.008] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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27
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Chromatography hyphenated to high resolution mass spectrometry in untargeted metabolomics for investigation of food (bio)markers. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2020.116161] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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28
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Tortorella S, Cinti S. How Can Chemometrics Support the Development of Point of Need Devices? Anal Chem 2021; 93:2713-2722. [DOI: 10.1021/acs.analchem.0c04151] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Sara Tortorella
- Molecular Horizon srl, Via Montelino 30, 06084 Bettona, Perugia, Italy
| | - Stefano Cinti
- Department of Pharmacy, University of Naples “Federico II”, Via Domenico Montesano 49, 80131 Naples, Italy
- BAT Center−Interuniversity Center for Studies on Bioinspired Agro-Environmental Technology, University of Napoli “Federico II”, 80055 Portici, Naples, Italy
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29
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Buric F, Zrimec J, Zelezniak A. Parallel Factor Analysis Enables Quantification and Identification of Highly Convolved Data-Independent-Acquired Protein Spectra. PATTERNS (NEW YORK, N.Y.) 2020; 1:100137. [PMID: 33336195 PMCID: PMC7733873 DOI: 10.1016/j.patter.2020.100137] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 09/14/2020] [Accepted: 10/12/2020] [Indexed: 11/26/2022]
Abstract
High-throughput data-independent acquisition (DIA) is the method of choice for quantitative proteomics, combining the best practices of targeted and shotgun approaches. The resultant DIA spectra are, however, highly convolved and with no direct precursor-fragment correspondence, complicating biological sample analysis. Here, we present CANDIA (canonical decomposition of data-independent-acquired spectra), a GPU-powered unsupervised multiway factor analysis framework that deconvolves multispectral scans to individual analyte spectra, chromatographic profiles, and sample abundances, using parallel factor analysis. The deconvolved spectra can be annotated with traditional database search engines or used as high-quality input for de novo sequencing methods. We demonstrate that spectral libraries generated with CANDIA substantially reduce the false discovery rate underlying the validation of spectral quantification. CANDIA covers up to 33 times more total ion current than library-based approaches, which typically use less than 5% of total recorded ions, thus allowing quantification and identification of signals from unexplored DIA spectra. Conventional DIA spectral libraries cover less than 3% of a scan's total ion count CANDIA deconvolves peptide signals by leveraging all scan data CANDIA uses GPUs to enable tensor algebra on massive DIA mass spectrometry data CANDIA output enables high-confidence and precise quantitative proteomics
The latest high-throughput mass spectrometry-based technologies can record virtually all molecules from complex biological samples, providing a holistic picture of proteomes in cells and tissues and enabling an evaluation of the overall status of a person's health. However, current best practices are still only scratching the surface of the wealth of available information obtained from the massive proteome datasets, and efficient novel data-driven strategies are needed. Powered by advances in GPU hardware and open-source machine-learning frameworks, we developed a data-driven approach, CANDIA, which disassembles highly complex proteomics data into the elementary molecular signatures of the proteins in biological samples. Our work provides a performant and adaptable solution that complements existing mass spectrometry techniques. As the central mathematical methods are generic, other scientific fields that are dealing with highly convolved datasets will benefit from this work.
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Affiliation(s)
- Filip Buric
- Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, Gothenburg 412 96, Sweden
| | - Jan Zrimec
- Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, Gothenburg 412 96, Sweden
| | - Aleksej Zelezniak
- Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, Gothenburg 412 96, Sweden.,Science for Life Laboratory, Tomtebodavägen 23a, Stockholm 171 65, Sweden
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30
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Ma YB, Amamcharla JK. A rapid method to quantify casein in fluid milk by front-face fluorescence spectroscopy combined with chemometrics. J Dairy Sci 2020; 104:243-252. [PMID: 33162066 DOI: 10.3168/jds.2020-18799] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Accepted: 08/24/2020] [Indexed: 11/19/2022]
Abstract
Casein in fluid milk determines cheese yield and affects cheese quality. Traditional methods of measuring casein in milk involve lengthy sample preparations with labor-intensive nitrogen-based protein quantifications. The objective of this study was to quantify casein in fluid milk with different casein-to-crude-protein ratios using front-face fluorescence spectroscopy (FFFS) and chemometrics. We constructed calibration samples by mixing microfiltration and ultrafiltration retentate and permeate in different ratios to obtain different casein concentrations and casein-to-crude-protein ratios. We developed partial least squares regression and elastic net regression models for casein prediction in fluid milk using FFFS tryptophan emission spectra and reference casein contents. We used a set of 20 validation samples (including raw, skim, and ultrafiltered milk) to optimize and validate model performance. We externally tested another independent set of 20 test samples (including raw, skim, and ultrafiltered milk) by root mean square error of prediction (RMSEP), residual prediction deviation (RPD), and relative prediction error (RPE). The RMSEP for casein content quantification in raw, skim, and ultrafiltered milk ranged from 0.12 to 0.13%, and the RPD ranged from 3.2 to 3.4. The externally validated error of prediction was comparable to the existing rapid method and showed practical model performance for quality-control purposes. This FFFS-based method can be implemented as a routine quality-control tool in the dairy industry, providing rapid quantification of casein content in fluid milk intended for cheese manufacturing.
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Affiliation(s)
- Yizhou B Ma
- Department of Animal Sciences and Industry/Food Science Institute, Kansas State University, Manhattan 66506
| | - Jayendra K Amamcharla
- Department of Animal Sciences and Industry/Food Science Institute, Kansas State University, Manhattan 66506.
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31
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Qi D, Ma C, Wang W, Zhang L, Li J. Gas Chromatography-Mass Spectrometry Analysis as a Tool to Reveal Differences Between the Volatile Compound Profile of Royal Jelly Produced from Tea and Pagoda Trees. FOOD ANAL METHOD 2020. [DOI: 10.1007/s12161-020-01880-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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32
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Cui L, Kimmel J, Zhou L, Rao J, Chen B. Combining solid dispersion-based spray drying with cyclodextrin to improve the functionality and mitigate the beany odor of pea protein isolate. Carbohydr Polym 2020; 245:116546. [PMID: 32718639 DOI: 10.1016/j.carbpol.2020.116546] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Revised: 05/28/2020] [Accepted: 05/29/2020] [Indexed: 11/25/2022]
Abstract
The beany flavor of pea protein limits its application in the food industry. This study aimed at addressing this problem by combining the advantages of solid-based spray drying technique and the ability of cyclodextrins (CD) to entrap volatiles. Pea protein isolates (PPI) was extracted by alkaline extraction-isoelectric precipitation, followed by co-spray drying with CD. The resulted PPI-CD showed no major structure changes. HS-SPME-GC-MS coupled to untargeted metabolomics successfully identified 23 aroma compounds that represent the different odorants among PPI-control, physically mixed PPI-CD, and co-spray dried PPI-CD samples. Heat map analysis also showed a remarkable beany odor mitigation effect upon the addition of CD, which was further proved to be due to CD entrapping aroma compounds during spray drying. In the meantime, the functional attributes of PPI-CD were not adversely impacted by the addition of CD.
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Affiliation(s)
- Leqi Cui
- Department of Plant Sciences, North Dakota State University, Fargo, ND, 58108, USA
| | | | - Leon Zhou
- Roquette America Inc., Geneva, IL, 60134, USA
| | - Jiajia Rao
- Department of Plant Sciences, North Dakota State University, Fargo, ND, 58108, USA
| | - Bingcan Chen
- Department of Plant Sciences, North Dakota State University, Fargo, ND, 58108, USA.
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33
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Lorenzo JM. Grand Challenges in Product Quality. FRONTIERS IN ANIMAL SCIENCE 2020. [DOI: 10.3389/fanim.2020.599866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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34
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Dąbrowski Ł. Evaluation of a Simplified Method for GC/MS Qualitative Analysis of Polycyclic Aromatic Hydrocarbons, Polychlorinated Biphenyls, and Organic Pesticides Using PARADISe Computer Program. Molecules 2020; 25:molecules25163727. [PMID: 32824143 PMCID: PMC7465948 DOI: 10.3390/molecules25163727] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2020] [Revised: 08/12/2020] [Accepted: 08/14/2020] [Indexed: 11/16/2022] Open
Abstract
For complex matrices such as environmental samples, there is usually a problem with not fully resolved peaks during GC/MS analysis. The PARADISe computer program (based on the PARFAC2 model) allows the identification of peaks using the deconvoluted mass spectra and the NIST MS library. The number of repetitions required by this software (at least five) is a real limitation for the determination of semi-volatile compounds, like polycyclic aromatic hydrocarbons, polychlorinated biphenyls, and organic pesticides in environmental samples. In this work, the method to overcome this condition was proposed and evaluated. The sets of the five files required by PARADISe were prepared by mathematically modifying the original GC/MS chromatograms obtained for the standard mixture (C = 2 µg/mL of 40 compounds) and real sample extracts (soil samples with different total organic carbon content and one cardboard extract) spiked with standards. Total average match factor for all the substances identified in a standard mixture was 874 (near 900—“excellent match”), and for all the substances in the real samples, it was 786 (near 800—“good match”). The results from PARADISe were comparable to those obtained with other programs: AMDIS (NIST) and MassHunter (Agilent), tested also in this work. PARADISe software can be effectively used for chromatogram deconvolution and substance identification.
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Affiliation(s)
- Łukasz Dąbrowski
- Department of Food Analysis and Environmental Protection, Faculty of Chemical Technology and Engineering, UTP University of Science and Technology, 3 Seminaryjna Street, 85-326 Bydgoszcz, Poland
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Cozzolino D. The Sample, the Spectra and the Maths-The Critical Pillars in the Development of Robust and Sound Applications of Vibrational Spectroscopy. Molecules 2020; 25:E3674. [PMID: 32806655 PMCID: PMC7466136 DOI: 10.3390/molecules25163674] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 08/03/2020] [Accepted: 08/07/2020] [Indexed: 12/02/2022] Open
Abstract
The last two decades have witnessed an increasing interest in the use of the so-called rapid analytical methods or high throughput techniques. Most of these applications reported the use of vibrational spectroscopy methods (near infrared (NIR), mid infrared (MIR), and Raman) in a wide range of samples (e.g., food ingredients and natural products). In these applications, the analytical method is integrated with a wide range of multivariate data analysis (MVA) techniques (e.g., pattern recognition, modelling techniques, calibration, etc.) to develop the target application. The availability of modern and inexpensive instrumentation together with the access to easy to use software is determining a steady growth in the number of uses of these technologies. This paper underlines and briefly discusses the three critical pillars-the sample (e.g., sampling, variability, etc.), the spectra and the mathematics (e.g., algorithms, pre-processing, data interpretation, etc.)-that support the development and implementation of vibrational spectroscopy applications.
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Affiliation(s)
- Daniel Cozzolino
- Centre for Nutrition and Food Sciences, Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, Brisbane, Queensland 4072, Australia;
- ARC Training Centre for Uniquely Australian Foods, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Block 10, Level 1, 39 Kessels Rd, Coopers Plains Qld 4108, Australia
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Augustijn D, Kulakova A, Mahapatra S, Harris P, Rinnan Å. Isothermal Chemical Denaturation: Data Analysis, Error Detection, and Correction by PARAFAC2. Anal Chem 2020; 92:6958-6967. [PMID: 32323977 DOI: 10.1021/acs.analchem.9b05748] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Characterization of a protein's conformational stability is a key step in the development of biotherapeutics, where protein unfolding leads to adverse properties, such as aggregation and loss of efficacy. Isothermal chemical denaturation (ICD) can be applied to determine chemical stability, aiming to identify the optimal solvent conditions, in terms of pH, salt concentration, and added excipients. For seven monoclonal antibodies, this study investigates the observed intrinsic protein fluorescence emission spectra as a function of denaturant concentration. Protein formulations are screened in two experimental series. We show how the peak shapes of folded and unfolded proteins are preserved under added salt (0-140 mM NaCl) and added excipients concentrations, as typically found in biotherapeutic formulations and that only minor effects in tryptophan fluorescence peak tailing are observed over a large pH range (5.5-9.0). The data of seven mAbs, where GuHCl was a suitable denaturant, are modeled using PARAFAC2. PARAFAC2, a linear decomposition method, is well suited for the data and yields robust, valid, and automated models that allow for the detection of erroneous measurements. Analysis of the errors show correlation with the well-based experimental setup, and differences in observed errors between the two experimental series. We additionally show a correction method for these outliers based on PARAFAC2 model scores, such that full transition curves can be retrieved, increasing the accuracy of any subsequent analysis.
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Affiliation(s)
- Dillen Augustijn
- Department of Food Science, Faculty of Life Sciences, University of Copenhagen, Rolighedsvej 30, DK-1958 Frederiksberg C, Denmark
| | - Alina Kulakova
- Department of Chemistry, Technical University of Denmark, Kemitorvet 207, 2800 Kgs. Lyngby, Denmark
| | - Sujata Mahapatra
- Department of Chemistry, Technical University of Denmark, Kemitorvet 207, 2800 Kgs. Lyngby, Denmark.,Novozymes A/S, Biologiens Vej 2, 2800 Kongens Lyngby, Denmark
| | - Pernille Harris
- Department of Chemistry, Technical University of Denmark, Kemitorvet 207, 2800 Kgs. Lyngby, Denmark
| | - Åsmund Rinnan
- Department of Food Science, Faculty of Life Sciences, University of Copenhagen, Rolighedsvej 30, DK-1958 Frederiksberg C, Denmark
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37
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Gas chromatography-mass spectrometry analysis reveals the differences in volatile components of royal jelly from different honeybee stocks. Lebensm Wiss Technol 2020. [DOI: 10.1016/j.lwt.2020.109143] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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38
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Rolinger L, Rüdt M, Hubbuch J. A critical review of recent trends, and a future perspective of optical spectroscopy as PAT in biopharmaceutical downstream processing. Anal Bioanal Chem 2020; 412:2047-2064. [PMID: 32146498 PMCID: PMC7072065 DOI: 10.1007/s00216-020-02407-z] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Revised: 01/06/2020] [Accepted: 01/10/2020] [Indexed: 12/01/2022]
Abstract
As competition in the biopharmaceutical market gets keener due to the market entry of biosimilars, process analytical technologies (PATs) play an important role for process automation and cost reduction. This article will give a general overview and address the recent innovations and applications of spectroscopic methods as PAT tools in the downstream processing of biologics. As data analysis strategies are a crucial part of PAT, the review discusses frequently used data analysis techniques and addresses data fusion methodologies as the combination of several sensors is moving forward in the field. The last chapter will give an outlook on the application of spectroscopic methods in combination with chemometrics and model predictive control (MPC) for downstream processes. Graphical abstract.
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Affiliation(s)
- Laura Rolinger
- Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology, Fritz-Haber-Weg 2, 76131, Karlsruhe, Germany
| | - Matthias Rüdt
- Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology, Fritz-Haber-Weg 2, 76131, Karlsruhe, Germany
| | - Jürgen Hubbuch
- Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology, Fritz-Haber-Weg 2, 76131, Karlsruhe, Germany.
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39
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Alves Filho EG, Silva LMA, Wurlitzer NJ, Fernandes FAN, Fonteles TV, Rodrigues S, de Brito ES. An integrated analytical approach based on NMR, LC-MS and GC-MS to evaluate thermal and non-thermal processing of cashew apple juice. Food Chem 2020; 309:125761. [PMID: 31757490 DOI: 10.1016/j.foodchem.2019.125761] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Revised: 10/17/2019] [Accepted: 10/20/2019] [Indexed: 10/25/2022]
Abstract
Innovative chemometric approaches by NMR and LC-MS data fusion (multiblock analysis) and decomposition of the GC-MS raw data by PARADISe were applied to evaluate the influence of thermal and non-thermal processing on the composition of cashew apple juices. Comparative investigations by Principal Component Analysis (PCA) highlighted pronounced effect of thermal processing on juice compared to non-thermal processing, as decreases of anacardic acids, sucrose, malic acid, tyrosine, phenylalanine, and important flavor compounds (esters, aldehydes, and ketones). Ultrasound presented relevant influence on increase of anacardic acids concentration. Non-thermal processing carried out at more intense conditions (10 min of ultrasound, 5 min of ozone, and pulsed light at 10 V) showed pronounced effect compared to other non-thermal processing. Although individual PCA enables to detect the influence of different processing technologies, data fusion and PARADISe presented advantages, since a more comprehensive understanding of the relationship among chemical changes from different analytical techniques were established.
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Affiliation(s)
- Elenilson G Alves Filho
- Universidade Federal do Ceará, Departamento de Engenharia de Alimentos, Bloco 858, Campus do Pici, Fortaleza CE 60440-900, Brazil
| | - Lorena Mara A Silva
- Embrapa Agroindústria Tropical, Rua Dra Sara Mesquita, 2270, Pici, Fortaleza CE 60511-110, Brazil
| | - Nedio Jair Wurlitzer
- Embrapa Agroindústria Tropical, Rua Dra Sara Mesquita, 2270, Pici, Fortaleza CE 60511-110, Brazil
| | - Fabiano André N Fernandes
- Universidade Federal do Ceará, Departamento de Engenharia Química, Bloco 709, Campus do Pici, Fortaleza CE 60440-900, Brazil
| | - Thatyane Vidal Fonteles
- Universidade Federal do Ceará, Departamento de Engenharia de Alimentos, Bloco 858, Campus do Pici, Fortaleza CE 60440-900, Brazil
| | - Sueli Rodrigues
- Universidade Federal do Ceará, Departamento de Engenharia de Alimentos, Bloco 858, Campus do Pici, Fortaleza CE 60440-900, Brazil
| | - Edy S de Brito
- Embrapa Agroindústria Tropical, Rua Dra Sara Mesquita, 2270, Pici, Fortaleza CE 60511-110, Brazil.
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40
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Zaukuu JLZ, Soós J, Bodor Z, Felföldi J, Magyar I, Kovacs Z. Authentication of Tokaj Wine (Hungaricum) with the Electronic Tongue and Near Infrared Spectroscopy. J Food Sci 2019; 84:3437-3444. [PMID: 31762045 DOI: 10.1111/1750-3841.14956] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Revised: 10/07/2019] [Accepted: 10/21/2019] [Indexed: 11/28/2022]
Abstract
Tokaj wines (Hungaricum) are botrytized wines acknowledged for the unique organoleptic properties bestowed by botrytized grape berries during production. Excluding these berries during wine production or manipulating the sugar content of low-grade wines to imitate high-grade wines are some recent suspicious activities that threaten the wine quality. Advanced methods such as spectroscopy and sensor-based devices have been lauded for rapid, reliable, and cost-effective analysis, but there has been no report of their application to monitor grape must concentrate adulteration in botrytized wines. The study aimed to develop models to rapidly discriminate lower grade Tokaj wines, "Forditas I" and "Forditas II," that were artificially adulterated with grape must concentrate to match the sugar content of high-grade Tokaj wines using an electronic tongue (e-tongue) and two near infrared spectrometers (NIRS). Data were evaluated with the following chemometrics: principal component analysis (PCA), discriminant analysis (LDA), partial least square regression (PLSR), and aquaphotomics (a novel approach). There was a noticeable pattern of separation in PCA for all three instruments and 100% classification of adulterated and nonadulterated wines in LDA using the e-tongue. Aquagrams from the aquaphotomics approach showed important water absorption bands capable of being markers of Tokaj wine quality. PLSR models showed coefficient of determination (R2 CV) of 0.98 (e-tongue), 0.97 (benchtop NIRS), 0.87 (handheld NIRS), and low root mean squared errors of cross-validation. All three instruments could discriminate, classify, and predict grape must concentrate adulteration in Tokaj with a high accuracy and low error. The methods can be applied for routine quality checks of botrytized wines. PRACTICAL APPLICATION: Tokaj wines (Hungaricum) are botrytized wines acknowledged for the unique organoleptic properties bestowed by botrytized grape berries during production. Excluding these berries during wine production or manipulating the sugar content of low-grade wines to imitate high-grade wines are some recent suspicious activities that threaten the wine quality. Using advanced instruments, the electronic tongue, benchtop near infrared spectroscopy, and a handheld near infrared spectroscopy, we could discriminate, classify, and predict grape must concentrate adulteration in Tokaj with a high accuracy and low error. The models in our study can be applied for routine quality checks of botrytized wines.
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Affiliation(s)
| | - János Soós
- Dept. of Physics and Control, Szent Istvan Univ., Budapest, Hungary.,Dept. of Oenology, Szent Istvan Univ., Budapest, Hungary
| | - Zsanett Bodor
- Dept. of Physics and Control, Szent Istvan Univ., Budapest, Hungary
| | - József Felföldi
- Dept. of Physics and Control, Szent Istvan Univ., Budapest, Hungary
| | - Ildikó Magyar
- Dept. of Oenology, Szent Istvan Univ., Budapest, Hungary
| | - Zoltan Kovacs
- Dept. of Physics and Control, Szent Istvan Univ., Budapest, Hungary
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41
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Kemsley EK, Defernez M, Marini F. Multivariate statistics: Considerations and confidences in food authenticity problems. Food Control 2019. [DOI: 10.1016/j.foodcont.2019.05.021] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
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42
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Gonçalves TR, Rosa LN, Torquato AS, da Silva LFO, Março PH, Gomes STM, Matsushita M, Valderrama P. Assessment of Brazilian Monovarietal Olive Oil in Two Different Package Systems by Using Data Fusion and Chemometrics. FOOD ANAL METHOD 2019. [DOI: 10.1007/s12161-019-01511-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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43
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Wang W, Jin S, Guo Y. Exploration of a Method of Distinguishing Different Nongxiang Tieguanyin Tea Grades Based on Aroma Determined by GC-MS Combined with Chemometrics. Molecules 2019; 24:molecules24091707. [PMID: 31052526 PMCID: PMC6539088 DOI: 10.3390/molecules24091707] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Accepted: 04/30/2019] [Indexed: 12/30/2022] Open
Abstract
An aroma-based method for distinguishing different grades of Nongxiang Tieguanyin was explored by taking special grade (K110) and 1-4 grades (K101, K102, K103, and K104) of this tea as samples. Tea samples were analyzed by gas chromatography-mass spectrometry (GC-MS) combined with chemometrics. Results showed differences in the types and relative contents of aroma components among different grades of Nongxiang Tieguanyin tea. In the principal component analysis (PCA) scoring plot, except for K102 and K103, tea samples of different grades were distributed in different regions. Components satisfying variable important for the projection (VIP) > 1 and peak areas with significant differences (p < 0.05) among different tea grades were screened. Finally, 18 differential variables were screened out from 143 volatiles. The clustering results of these variables were consistent with those of PCA. K102 and K103 were initially clustered into one group and then clustered with K101, K110, and K104 in turn. The clear PCA separation of these samples and uniform hierarchical cluster analysis (HCA) clustering results suggests that GC-MS coupled with chemometrics analysis is a valid and accurate approach for discriminating different grades of Nongxiang Tieguanyin. The screened differential variables could represent a difference in aroma quality among five grades of Nongxiang Tieguanyin tea. Clear rules between peak area and the grade were also observed in some differential variables. 1-Ethylpyrrole and unknown-32 were positively correlated with grade. 2-Methylfuran, 2-ethylfuran, 2-methylidenecyclopentan-1-ol, mesityl oxide, 2-amylfuran, and D-limonene were negatively correlated with grade. The peak areas of methyl acetate, dimethyl sulfide, 6-methylhept-5-en-2-one, and (Z)-β-ocimene initially decreased but then increased with declining grade. The toluene content was especially high in K104 but only a negligible difference was observed among other grades. This study provides a potential method for differentiating Nongxiang Tieguanyin teas of different grades based on aroma. Unknown samples could be classified by comparison of their spatial distribution with those of known standard samples in PCA or HCA, as well as the peak area differences of differential variables between unknown samples and known standard samples.
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Affiliation(s)
- Wei Wang
- College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
| | - Shan Jin
- College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
- Key Laboratory of Tea Science of Fujian Province, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
| | - Yaling Guo
- College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
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44
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Cordero C, Kiefl J, Reichenbach SE, Bicchi C. Characterization of odorant patterns by comprehensive two-dimensional gas chromatography: A challenge in omic studies. Trends Analyt Chem 2019. [DOI: 10.1016/j.trac.2018.06.005] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
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45
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Jiménez-Carvelo AM, González-Casado A, Bagur-González MG, Cuadros-Rodríguez L. Alternative data mining/machine learning methods for the analytical evaluation of food quality and authenticity - A review. Food Res Int 2019; 122:25-39. [PMID: 31229078 DOI: 10.1016/j.foodres.2019.03.063] [Citation(s) in RCA: 121] [Impact Index Per Article: 24.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Revised: 03/25/2019] [Accepted: 03/26/2019] [Indexed: 12/31/2022]
Abstract
In recent years, the variety and volume of data acquired by modern analytical instruments in order to conduct a better authentication of food has dramatically increased. Several pattern recognition tools have been developed to deal with the large volume and complexity of available trial data. The most widely used methods are principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), soft independent modelling by class analogy (SIMCA), k-nearest neighbours (kNN), parallel factor analysis (PARAFAC), and multivariate curve resolution-alternating least squares (MCR-ALS). Nevertheless, there are alternative data treatment methods, such as support vector machine (SVM), classification and regression tree (CART) and random forest (RF), that show a great potential and more advantages compared to conventional ones. In this paper, we explain the background of these methods and review and discuss the reported studies in which these three methods have been applied in the area of food quality and authenticity. In addition, we clarify the technical terminology used in this particular area of research.
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Affiliation(s)
- Ana M Jiménez-Carvelo
- Department of Analytical Chemistry, Faculty of Science, University of Granada, C/ Fuentenueva s/n, E-18071 Granada, Spain.
| | - Antonio González-Casado
- Department of Analytical Chemistry, Faculty of Science, University of Granada, C/ Fuentenueva s/n, E-18071 Granada, Spain
| | - M Gracia Bagur-González
- Department of Analytical Chemistry, Faculty of Science, University of Granada, C/ Fuentenueva s/n, E-18071 Granada, Spain
| | - Luis Cuadros-Rodríguez
- Department of Analytical Chemistry, Faculty of Science, University of Granada, C/ Fuentenueva s/n, E-18071 Granada, Spain
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46
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47
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Study on the effects of rapid aging technology on the aroma quality of white tea using GC–MS combined with chemometrics: In comparison with natural aged and fresh white tea. Food Chem 2018; 265:189-199. [DOI: 10.1016/j.foodchem.2018.05.080] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Revised: 05/17/2018] [Accepted: 05/17/2018] [Indexed: 12/16/2022]
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48
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The scientific challenges in moving from targeted to non-targeted mass spectrometric methods for food fraud analysis: A proposed validation workflow to bring about a harmonized approach. Trends Food Sci Technol 2018. [DOI: 10.1016/j.tifs.2018.08.007] [Citation(s) in RCA: 86] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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49
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Advances in NIR spectroscopy applied to process analytical technology in food industries. Curr Opin Food Sci 2018. [DOI: 10.1016/j.cofs.2017.12.008] [Citation(s) in RCA: 83] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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50
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Paradiso VM, Pasqualone A, Summo C, Caponio F. Everything Should Be as Simple as It Can Be. But Not Simpler. Does Food Lipid Oxidation Require an Omics Approach? EUR J LIPID SCI TECH 2018. [DOI: 10.1002/ejlt.201800103] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Affiliation(s)
- Vito M. Paradiso
- Department of Soil, Plant and Food SciencesUniversity of BariVia Amendola 165/aI‐70126BariItaly
| | - Antonella Pasqualone
- Department of Soil, Plant and Food SciencesUniversity of BariVia Amendola 165/aI‐70126BariItaly
| | - Carmine Summo
- Department of Soil, Plant and Food SciencesUniversity of BariVia Amendola 165/aI‐70126BariItaly
| | - Francesco Caponio
- Department of Soil, Plant and Food SciencesUniversity of BariVia Amendola 165/aI‐70126BariItaly
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