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Zaldarriaga Heredia J, Wagner M, Jofré FC, Savio M, Azcarate SM, Camiña JM. An overview on multi-elemental profile integrated with chemometrics for food quality assessment: toward new challenges. Crit Rev Food Sci Nutr 2022; 63:8173-8193. [PMID: 35319312 DOI: 10.1080/10408398.2022.2055527] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Food products, especially those with high value-added, are commonly subjected to strict quality controls, which are of paramount importance, especially for attesting to some peculiar features related, for instance, to their geographical origin and/or the know-how of their producers. However, the sophistication of fraudulent practices requires a continuous update of analytical platforms. Different analytical techniques have become extremely appealing since the instrumental analysis tools evolution has substantially improved the capability to reveal and understand the complexity of food. In light of this, multi-elemental composition has been successful implemented solving a plethora of food authentication and traceability issues. In the last decades, it has existed an ever-increasing trend in analysis based on spectrometry analytical platforms in order to obtain a multi-elemental profile that combined with chemometrics have been noteworthy analytical methodologies able to solve these problems. This review provides an overview of published reports in the last decade (from 2011 to 2021) on food authentication and quality control from their multi-element composition in order to evaluate the state-of-the-art of this field and to identify the main characteristics of applied analytical techniques and chemometric data treatments that have permit achieve accurate discrimination/classification models, highlighting the strengths and the weaknesses of these methodologies.
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Affiliation(s)
- Jorgelina Zaldarriaga Heredia
- Instituto de Ciencias de la Tierra y Ambientales de La Pampa (INCITAP-CONICET), Santa Rosa, La Pampa, Argentina
- Facultad de Ciencias Exactas y Naturales, Universidad Nacional de La Pampa (UNLPam), Santa Rosa, La Pampa, Argentina
| | - Marcelo Wagner
- Instituto de Ciencias de la Tierra y Ambientales de La Pampa (INCITAP-CONICET), Santa Rosa, La Pampa, Argentina
| | - Florencia Cora Jofré
- Instituto de Ciencias de la Tierra y Ambientales de La Pampa (INCITAP-CONICET), Santa Rosa, La Pampa, Argentina
- Facultad de Ciencias Exactas y Naturales, Universidad Nacional de La Pampa (UNLPam), Santa Rosa, La Pampa, Argentina
| | - Marianela Savio
- Instituto de Ciencias de la Tierra y Ambientales de La Pampa (INCITAP-CONICET), Santa Rosa, La Pampa, Argentina
- Facultad de Ciencias Exactas y Naturales, Universidad Nacional de La Pampa (UNLPam), Santa Rosa, La Pampa, Argentina
| | - Silvana Mariela Azcarate
- Instituto de Ciencias de la Tierra y Ambientales de La Pampa (INCITAP-CONICET), Santa Rosa, La Pampa, Argentina
- Facultad de Ciencias Exactas y Naturales, Universidad Nacional de La Pampa (UNLPam), Santa Rosa, La Pampa, Argentina
| | - José Manuel Camiña
- Instituto de Ciencias de la Tierra y Ambientales de La Pampa (INCITAP-CONICET), Santa Rosa, La Pampa, Argentina
- Facultad de Ciencias Exactas y Naturales, Universidad Nacional de La Pampa (UNLPam), Santa Rosa, La Pampa, Argentina
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Balkir P, Kemahlioglu K, Yucel U. Foodomics: A new approach in food quality and safety. Trends Food Sci Technol 2021. [DOI: 10.1016/j.tifs.2020.11.028] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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Ejeahalaka KK, On SL. Chemometric studies of the effects of milk fat replacement with different proportions of vegetable oils in the formulation of fat-filled milk powders: Implications for quality assurance. Food Chem 2019; 295:198-205. [DOI: 10.1016/j.foodchem.2019.05.120] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Revised: 05/15/2019] [Accepted: 05/17/2019] [Indexed: 10/26/2022]
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1H NMR spectroscopy combined with multivariate data analysis for differentiation of Brazilian lager beer according to brewery. Eur Food Res Technol 2019. [DOI: 10.1007/s00217-019-03354-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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Granato D, Putnik P, Kovačević DB, Santos JS, Calado V, Rocha RS, Cruz AGD, Jarvis B, Rodionova OY, Pomerantsev A. Trends in Chemometrics: Food Authentication, Microbiology, and Effects of Processing. Compr Rev Food Sci Food Saf 2018; 17:663-677. [PMID: 33350122 DOI: 10.1111/1541-4337.12341] [Citation(s) in RCA: 246] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 01/25/2018] [Accepted: 01/26/2018] [Indexed: 11/27/2022]
Abstract
In the last decade, the use of multivariate statistical techniques developed for analytical chemistry has been adopted widely in food science and technology. Usually, chemometrics is applied when there is a large and complex dataset, in terms of sample numbers, types, and responses. The results are used for authentication of geographical origin, farming systems, or even to trace adulteration of high value-added commodities. In this article, we provide an extensive practical and pragmatic overview on the use of the main chemometrics tools in food science studies, focusing on the effects of process variables on chemical composition and on the authentication of foods based on chemical markers. Pattern recognition methods, such as principal component analysis and cluster analysis, have been used to associate the level of bioactive components with in vitro functional properties, although supervised multivariate statistical methods have been used for authentication purposes. Overall, chemometrics is a useful aid when extensive, multiple, and complex real-life problems need to be addressed in a multifactorial and holistic context. Undoubtedly, chemometrics should be used by governmental bodies and industries that need to monitor the quality of foods, raw materials, and processes when high-dimensional data are available. We have focused on practical examples and listed the pros and cons of the most used chemometric tools to help the user choose the most appropriate statistical approach for analysis of complex and multivariate data.
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Affiliation(s)
- Daniel Granato
- Dept. of Food Engineering, State Univ. of Ponta Grossa, Av. Carlos Cavalcanti, 4748, 84030-900, Ponta Grossa, Brazil
| | - Predrag Putnik
- Faculty of Food Technology and Biotechnology, Univ. of Zagreb, Pierottijeva 6, 10000, Zagreb, Croatia
| | - Danijela Bursać Kovačević
- Faculty of Food Technology and Biotechnology, Univ. of Zagreb, Pierottijeva 6, 10000, Zagreb, Croatia
| | - Jânio Sousa Santos
- Dept. of Food Engineering, State Univ. of Ponta Grossa, Av. Carlos Cavalcanti, 4748, 84030-900, Ponta Grossa, Brazil
| | - Verônica Calado
- School of Chemistry, Federal Univ. of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Ramon Silva Rocha
- Dept. de Alimentos, Inst. Federal de Educação, Ciência e Tecnologia (IFRJ), 20270-021, Rio de Janeiro, Brazil
| | - Adriano Gomes Da Cruz
- Dept. de Alimentos, Inst. Federal de Educação, Ciência e Tecnologia (IFRJ), 20270-021, Rio de Janeiro, Brazil
| | - Basil Jarvis
- Dept. of Food and Nutrition Sciences, School of Chemistry, Food and Pharmacy, The Univ. of Reading, Whiteknights, Reading, Berkshire RG6 6AP, U.K
| | - Oxana Ye Rodionova
- Semenov Inst. of Chemical Physics RAS, Kosygin str. 4, 119991, Moscow, Russia
| | - Alexey Pomerantsev
- Semenov Inst. of Chemical Physics RAS, Kosygin str. 4, 119991, Moscow, Russia
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Lee LC, Liong CY, Jemain AA. Partial least squares-discriminant analysis (PLS-DA) for classification of high-dimensional (HD) data: a review of contemporary practice strategies and knowledge gaps. Analyst 2018; 143:3526-3539. [DOI: 10.1039/c8an00599k] [Citation(s) in RCA: 261] [Impact Index Per Article: 43.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
This review highlights and discusses critically various knowledge gaps in classification modelling using PLS-DA for high dimensional data.
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Affiliation(s)
- Loong Chuen Lee
- Forensic Science Programme
- FSK
- Universiti Kebangsaan Malaysia
- 50300 Kuala Lumpur
- Malaysia
| | - Choong-Yeun Liong
- Statistics Programme
- FST
- Universiti Kebangsaan Malaysia
- 43600 Bangi
- Malaysia
| | - Abdul Aziz Jemain
- Statistics Programme
- FST
- Universiti Kebangsaan Malaysia
- 43600 Bangi
- Malaysia
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Vargas-Bello-Pérez E, Toro-Mujica P, Enriquez-Hidalgo D, Fellenberg MA, Gómez-Cortés P. Short communication: Discrimination between retail bovine milks with different fat contents using chemometrics and fatty acid profiling. J Dairy Sci 2017; 100:4253-4257. [PMID: 28434733 DOI: 10.3168/jds.2016-12393] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2016] [Accepted: 02/26/2017] [Indexed: 12/13/2022]
Abstract
We used a multivariate chemometric approach to differentiate or associate retail bovine milks with different fat contents and non-dairy beverages, using fatty acid profiles and statistical analysis. We collected samples of bovine milk (whole, semi-skim, and skim; n = 62) and non-dairy beverages (n = 27), and we analyzed them using gas-liquid chromatography. Principal component analysis of the fatty acid data yielded 3 significant principal components, which accounted for 72% of the total variance in the data set. Principal component 1 was related to saturated fatty acids (C4:0, C6:0, C8:0, C12:0, C14:0, C17:0, and C18:0) and monounsaturated fatty acids (C14:1 cis-9, C16:1 cis-9, C17:1 cis-9, and C18:1 trans-11); whole milk samples were clearly differentiated from the rest using this principal component. Principal component 2 differentiated semi-skim milk samples by n-3 fatty acid content (C20:3n-3, C20:5n-3, and C22:6n-3). Principal component 3 was related to C18:2 trans-9,trans-12 and C20:4n-6, and its lower scores were observed in skim milk and non-dairy beverages. A cluster analysis yielded 3 groups: group 1 consisted of only whole milk samples, group 2 was represented mainly by semi-skim milks, and group 3 included skim milk and non-dairy beverages. Overall, the present study showed that a multivariate chemometric approach is a useful tool for differentiating or associating retail bovine milks and non-dairy beverages using their fatty acid profile.
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Affiliation(s)
- Einar Vargas-Bello-Pérez
- Departamento de Ciencias Animales, Facultad de Agronomía e Ingeniería Forestal, Pontificia Universidad Católica de Chile, Santiago, Casilla 306, C.P. 6904411, Chile.
| | - Paula Toro-Mujica
- Departamento de Ciencias Animales, Facultad de Agronomía e Ingeniería Forestal, Pontificia Universidad Católica de Chile, Santiago, Casilla 306, C.P. 6904411, Chile
| | - Daniel Enriquez-Hidalgo
- Departamento de Ciencias Animales, Facultad de Agronomía e Ingeniería Forestal, Pontificia Universidad Católica de Chile, Santiago, Casilla 306, C.P. 6904411, Chile
| | - María Angélica Fellenberg
- Departamento de Ciencias Animales, Facultad de Agronomía e Ingeniería Forestal, Pontificia Universidad Católica de Chile, Santiago, Casilla 306, C.P. 6904411, Chile
| | - Pilar Gómez-Cortés
- Instituto de Investigación en Ciencias de la Alimentación (CSIC-UAM), Universidad Autónoma de Madrid, Nicolás Cabrera 9, Madrid, 28049, Spain
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Josić D, Peršurić Ž, Rešetar D, Martinović T, Saftić L, Kraljević Pavelić S. Use of Foodomics for Control of Food Processing and Assessing of Food Safety. ADVANCES IN FOOD AND NUTRITION RESEARCH 2017; 81:187-229. [PMID: 28317605 DOI: 10.1016/bs.afnr.2016.12.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Food chain, food safety, and food-processing sectors face new challenges due to globalization of food chain and changes in the modern consumer preferences. In addition, gradually increasing microbial resistance, changes in climate, and human errors in food handling remain a pending barrier for the efficient global food safety management. Consequently, a need for development, validation, and implementation of rapid, sensitive, and accurate methods for assessment of food safety often termed as foodomics methods is required. Even though, the growing role of these high-throughput foodomic methods based on genomic, transcriptomic, proteomic, and metabolomic techniques has yet to be completely acknowledged by the regulatory agencies and bodies. The sensitivity and accuracy of these methods are superior to previously used standard analytical procedures and new methods are suitable to address a number of novel requirements posed by the food production sector and global food market.
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Affiliation(s)
- D Josić
- University of Rijeka, Centre for High-Throughput Technologies, Radmile Matejčić 2, Rijeka, Croatia.
| | - Ž Peršurić
- University of Rijeka, Centre for High-Throughput Technologies, Radmile Matejčić 2, Rijeka, Croatia
| | - D Rešetar
- University of Rijeka, Centre for High-Throughput Technologies, Radmile Matejčić 2, Rijeka, Croatia
| | - T Martinović
- University of Rijeka, Centre for High-Throughput Technologies, Radmile Matejčić 2, Rijeka, Croatia
| | - L Saftić
- University of Rijeka, Centre for High-Throughput Technologies, Radmile Matejčić 2, Rijeka, Croatia
| | - S Kraljević Pavelić
- University of Rijeka, Centre for High-Throughput Technologies, Radmile Matejčić 2, Rijeka, Croatia
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