1
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Gottstein V, Lachenmeier DW, Kuballa T, Bunzel M. 1H NMR-based approach to determine the geographical origin and cultivation method of roasted coffee. Food Chem 2024; 433:137278. [PMID: 37688828 DOI: 10.1016/j.foodchem.2023.137278] [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: 05/05/2023] [Revised: 08/04/2023] [Accepted: 08/23/2023] [Indexed: 09/11/2023]
Abstract
A comprehensive study of 603 roasted arabica coffee samples using NMR fingerprinting and multivariate data analysis was performed to differentiate coffee samples according to their geographical origin and cultivation method. Both lipophilic and hydrophilic coffee metabolites were recorded using 1H NMR spectroscopy, and principal component analysis followed by linear discriminant analysis (PCA-LDA) was applied. Coffee samples were fist differentiated according to their continents of origin followed by discrimination of coffee samples from Brazil, Ethiopia, and Colombia from coffee samples originating from another continent. Discrimination of coffee samples according to their continent of origin and additional assignment to the countries Brazil and Ethiopia were successful. However, an unambiguous separation of Colombian coffee samples from coffee samples of another continent (other than South America) was not possible. Also, differentiation of organically and conventionally produced coffee samples by using 1H NMR and PCA-LDA was not achieved.
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Affiliation(s)
- Vera Gottstein
- Karlsruhe Institute of Technology (KIT), Department of Food Chemistry and Phytochemistry, Adenauerring 20A, D-76131 Karlsruhe, Germany; Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Strasse 3, D-76187 Karlsruhe, Germany
| | - Dirk W Lachenmeier
- Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Strasse 3, D-76187 Karlsruhe, Germany.
| | - Thomas Kuballa
- Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Strasse 3, D-76187 Karlsruhe, Germany.
| | - Mirko Bunzel
- Karlsruhe Institute of Technology (KIT), Department of Food Chemistry and Phytochemistry, Adenauerring 20A, D-76131 Karlsruhe, Germany.
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2
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de Carvalho Couto C, Corrêa de Souza Coelho C, Moraes Oliveira EM, Casal S, Freitas-Silva O. Adulteration in roasted coffee: a comprehensive systematic review of analytical detection approaches. INTERNATIONAL JOURNAL OF FOOD PROPERTIES 2023. [DOI: 10.1080/10942912.2022.2158865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Affiliation(s)
- Cinthia de Carvalho Couto
- Food and Nutrition Graduate Program, the Federal University of State of Rio de Janeiro, Rio de Janeiro, Brazil
| | | | | | - Susana Casal
- LAQV/REQUIMTE, Laboratory of Bromatology and Hydrology, Faculty of Pharmacy, University of Porto, Porto, Portugal
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3
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Soni K, Frew R, Kebede B. A review of conventional and rapid analytical techniques coupled with multivariate analysis for origin traceability of soybean. Crit Rev Food Sci Nutr 2023; 64:6616-6635. [PMID: 36734977 DOI: 10.1080/10408398.2023.2171961] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Soybean has developed a reputation as a superfood due to its nutrient profile, health benefits, and versatility. Since 1960, its demand has increased dramatically, going from a mere 17 MMT to almost 358 MMT in the production year 2021/22. These extremely high production rates have led to lower-than-expected product quality, adulteration, illegal trade, deforestation, and other concerns. This necessitates the development of an effective technology to confirm soybean's provenance. This is the first review that investigates current analytical techniques coupled with multivariate analysis for origin traceability of soybeans. The fundamentals of several analytical techniques are presented, assessed, compared, and discussed in terms of their operating specifics, advantages, and shortcomings. Additionally, significance of multivariate analysis in analyzing complex data has also been discussed.
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Affiliation(s)
- Khushboo Soni
- Department of Food Science, University of Otago, Dunedin, New Zealand
| | - Russell Frew
- Oritain Global Limited, Central Dunedin 9016, Dunedin, New Zealand
| | - Biniam Kebede
- Department of Food Science, University of Otago, Dunedin, New Zealand
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4
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Wójcicki K. Near-infrared spectroscopy as a green technology to monitor coffee roasting. FOODS AND RAW MATERIALS 2022. [DOI: 10.21603/2308-4057-2022-2-536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Wet chemistry methods are traditionally used to evaluate the quality of a coffee beverage and its chemical characteristics. These old methods need to be replaced with more rapid, objective, and simple analytical methods for routine analysis. Near-infrared spectroscopy is an increasingly popular technique for nondestructive quality evaluation called a green technology.
Our study aimed to apply near-infrared spectroscopy to evaluate the quality of coffee samples of different origin (Brazil, Guatemala, Peru, and Kongo). Particularly, we analyzed the roasting time and its effect on the quality of coffee. The colorimetric method determined a relation between the coffee color and the time of roasting. Partial least squares regression analysis assessed a possibility of predicting the roasting conditions from the near-infrared spectra.
The regression results confirmed the possibility of applying near-infrared spectra to estimate the roasting conditions. The correlation between the spectra and the roasting time had R2 values of 0.96 and 0.95 for calibration and validation, respectively. The root mean square errors of prediction were low – 0.92 and 1.05 for calibration and validation, respectively. We also found a linear relation between the spectra and the roasting power. The quality of the models differed depending on the coffee origin and sub-region. All the coffee samples showed a good correlation between the spectra and the brightness (L* parameter), with R2 values of 0.96 and 0.95 for the calibration and validation curves, respectively.
According to the results, near-infrared spectroscopy can be used together with the chemometric analysis as a green technology to assess the quality of coffee.
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5
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Nguyen Minh Q, Lai QD, Nguy Minh H, Tran Kieu MT, Lam Gia N, Le U, Hang MP, Nguyen HD, Chau TDA, Doan NTT. Authenticity green coffee bean species and geographical origin using near‐infrared spectroscopy combined with chemometrics. Int J Food Sci Technol 2022. [DOI: 10.1111/ijfs.15786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Quan Nguyen Minh
- Department of Food Technology Faculty of Chemical Engineering Ho Chi Minh City University of Technology (HCMUT) 268 Ly Thuong Kiet Street, District 10 Ho Chi Minh City 72506 Vietnam
- Vietnam National University Ho Chi Minh City Linh Trung Ward, Thu Duc District Ho Chi Minh City Vietnam
| | - Quoc Dat Lai
- Department of Food Technology Faculty of Chemical Engineering Ho Chi Minh City University of Technology (HCMUT) 268 Ly Thuong Kiet Street, District 10 Ho Chi Minh City 72506 Vietnam
- Vietnam National University Ho Chi Minh City Linh Trung Ward, Thu Duc District Ho Chi Minh City Vietnam
| | - Hoang Nguy Minh
- Department of Food Technology Faculty of Chemical Engineering Ho Chi Minh City University of Technology (HCMUT) 268 Ly Thuong Kiet Street, District 10 Ho Chi Minh City 72506 Vietnam
- Vietnam National University Ho Chi Minh City Linh Trung Ward, Thu Duc District Ho Chi Minh City Vietnam
| | - Minh Tu Tran Kieu
- Department of Food Technology Faculty of Chemical Engineering Ho Chi Minh City University of Technology (HCMUT) 268 Ly Thuong Kiet Street, District 10 Ho Chi Minh City 72506 Vietnam
- Vietnam National University Ho Chi Minh City Linh Trung Ward, Thu Duc District Ho Chi Minh City Vietnam
| | - Ngoc Lam Gia
- Department of Food Technology Faculty of Chemical Engineering Ho Chi Minh City University of Technology (HCMUT) 268 Ly Thuong Kiet Street, District 10 Ho Chi Minh City 72506 Vietnam
- Vietnam National University Ho Chi Minh City Linh Trung Ward, Thu Duc District Ho Chi Minh City Vietnam
| | - Uyen Le
- Department of Food Technology Faculty of Chemical Engineering Ho Chi Minh City University of Technology (HCMUT) 268 Ly Thuong Kiet Street, District 10 Ho Chi Minh City 72506 Vietnam
- Vietnam National University Ho Chi Minh City Linh Trung Ward, Thu Duc District Ho Chi Minh City Vietnam
| | - My Phung Hang
- Department of Food Technology Faculty of Chemical Engineering Ho Chi Minh City University of Technology (HCMUT) 268 Ly Thuong Kiet Street, District 10 Ho Chi Minh City 72506 Vietnam
- Vietnam National University Ho Chi Minh City Linh Trung Ward, Thu Duc District Ho Chi Minh City Vietnam
| | - Hoang Dung Nguyen
- Department of Food Technology Faculty of Chemical Engineering Ho Chi Minh City University of Technology (HCMUT) 268 Ly Thuong Kiet Street, District 10 Ho Chi Minh City 72506 Vietnam
- Vietnam National University Ho Chi Minh City Linh Trung Ward, Thu Duc District Ho Chi Minh City Vietnam
| | - Tran Diem Ai Chau
- Department of Food Technology Faculty of Chemical Engineering Ho Chi Minh City University of Technology (HCMUT) 268 Ly Thuong Kiet Street, District 10 Ho Chi Minh City 72506 Vietnam
- Vietnam National University Ho Chi Minh City Linh Trung Ward, Thu Duc District Ho Chi Minh City Vietnam
| | - Ngoc Thuc Trinh Doan
- Department of Food Technology Faculty of Chemical Engineering Ho Chi Minh City University of Technology (HCMUT) 268 Ly Thuong Kiet Street, District 10 Ho Chi Minh City 72506 Vietnam
- Vietnam National University Ho Chi Minh City Linh Trung Ward, Thu Duc District Ho Chi Minh City Vietnam
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6
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Osorio J, Arana VA, Medina JM, Alarcon R, Moreno E, Wist J. 1D and 2D NMR spectra of coffee from 27 countries. GIGABYTE 2022; 2022:gigabyte50. [PMID: 36824514 PMCID: PMC9650224 DOI: 10.46471/gigabyte.50] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 04/09/2022] [Indexed: 11/09/2022] Open
Abstract
Between 2012 and 2014, 715 green coffee samples were gathered by Almacafé S.A. (Bogotá, Colombia) from 27 countries. These were analysed at the nuclear magnetic resonance (NMR) laboratory at Universidad del Valle (Cali, Colombia). Over 1000 methanolic coffee extracts were prepared and 4563 spectra were acquired in a fully automatic manner using a 400 MHz NMR spectrometer (Bruker Biospin, Germany). The dataset spans the variance that could be expected for an industrial application of origin monitoring, including samples from different harvest times, collected over several years, and processed by at least two distinct operators. The resulting 1D and 2D spectra can be used to develop and evaluate feature extraction methods, multivariate algorithms, and automation monitoring techniques. They can also be used as datasets for teaching, or as a reference for new studies of similar samples and approaches.
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Affiliation(s)
- Javier Osorio
- Chemistry Department, Universidad del Valle, 760008 Cali, Colombia
| | - Victoria A. Arana
- Chemistry Program, Basic Science Faculty, Universidad del Atlantico, 081007, Puerto Colombia, Colombia
| | - Jessica M. Medina
- Chemistry Program, Basic Science Faculty, Universidad del Atlantico, 081007, Puerto Colombia, Colombia
| | | | | | - Julien Wist
- Chemistry Department, Universidad del Valle, 760008 Cali, Colombia,Australian National Phenome Centre, Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth WA 6150, Australia, Corresponding author. E-mail:
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7
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Feasibility of compact near-infrared spectrophotometers and multivariate data analysis to assess roasted ground coffee traits. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.109041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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8
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Castillejos-Mijangos LA, Acosta-Caudillo A, Gallardo-Velázquez T, Osorio-Revilla G, Jiménez-Martínez C. Uses of FT-MIR Spectroscopy and Multivariate Analysis in Quality Control of Coffee, Cocoa, and Commercially Important Spices. Foods 2022; 11:foods11040579. [PMID: 35206058 PMCID: PMC8871480 DOI: 10.3390/foods11040579] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 02/10/2022] [Accepted: 02/15/2022] [Indexed: 02/07/2023] Open
Abstract
Nowadays, coffee, cocoa, and spices have broad applications in the food and pharmaceutical industries due to their organoleptic and nutraceutical properties, which have turned them into products of great commercial demand. Consequently, these products are susceptible to fraud and adulteration, especially those sold at high prices, such as saffron, vanilla, and turmeric. This situation represents a major problem for industries and consumers’ health. Implementing analytical techniques, i.e., Fourier transform mid-infrared (FT-MIR) spectroscopy coupled with multivariate analysis, can ensure the authenticity and quality of these products since these provide unique information on food matrices. The present review addresses FT-MIR spectroscopy and multivariate analysis application on coffee, cocoa, and spices authentication and quality control, revealing their potential use and elucidating areas of opportunity for future research.
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Affiliation(s)
- Lucero Azusena Castillejos-Mijangos
- Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Av. Wilfrido Massieu Esq. Cda. Manuel Stampa s/n, Alcaldía Gustavo A. Madero, Ciudad de Mexico C.P. 07738, Mexico; (L.A.C.-M.); (A.A.-C.); (G.O.-R.)
| | - Aracely Acosta-Caudillo
- Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Av. Wilfrido Massieu Esq. Cda. Manuel Stampa s/n, Alcaldía Gustavo A. Madero, Ciudad de Mexico C.P. 07738, Mexico; (L.A.C.-M.); (A.A.-C.); (G.O.-R.)
| | - Tzayhrí Gallardo-Velázquez
- Departamento de Biofísica, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Prolongación de Carpio y Plan de Ayala s/n, Col. Santo Tomás, Ciudad de Mexico C.P. 11340, Mexico
- Correspondence: (T.G.-V.); or (C.J.-M.); Tel.: +52-(55)-5729-6000 (ext. 62305) (T.G.-V.); +52-(55)-5729-6000 (ext. 57871) (C.J.-M.)
| | - Guillermo Osorio-Revilla
- Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Av. Wilfrido Massieu Esq. Cda. Manuel Stampa s/n, Alcaldía Gustavo A. Madero, Ciudad de Mexico C.P. 07738, Mexico; (L.A.C.-M.); (A.A.-C.); (G.O.-R.)
| | - Cristian Jiménez-Martínez
- Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Av. Wilfrido Massieu Esq. Cda. Manuel Stampa s/n, Alcaldía Gustavo A. Madero, Ciudad de Mexico C.P. 07738, Mexico; (L.A.C.-M.); (A.A.-C.); (G.O.-R.)
- Correspondence: (T.G.-V.); or (C.J.-M.); Tel.: +52-(55)-5729-6000 (ext. 62305) (T.G.-V.); +52-(55)-5729-6000 (ext. 57871) (C.J.-M.)
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9
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Abstract
This review provides an overview of recent studies on the potential of spectroscopy techniques (mid-infrared, near infrared, Raman, and fluorescence spectroscopy) used in coffee analysis. It specifically covers their applications in coffee roasting supervision, adulterants and defective beans detection, prediction of specialty coffee quality and coffees’ sensory attributes, discrimination of coffee based on variety, species, and geographical origin, and prediction of coffees chemical composition. These are important aspects that significantly affect the overall quality of coffee and consequently its market price and finally quality of the brew. From the reviewed literature, spectroscopic methods could be used to evaluate coffee for different parameters along the production process as evidenced by reported robust prediction models. Nevertheless, some techniques have received little attention including Raman and fluorescence spectroscopy, which should be further studied considering their great potential in providing important information. There is more focus on the use of near infrared spectroscopy; however, few multivariate analysis techniques have been explored. With the growing demand for fast, robust, and accurate analytical methods for coffee quality assessment and its authentication, there are other areas to be studied and the field of coffee spectroscopy provides a vast opportunity for scientific investigation.
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10
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Perez M, Domínguez-López I, López-Yerena A, Vallverdú Queralt A. Current strategies to guarantee the authenticity of coffee. Crit Rev Food Sci Nutr 2021; 63:539-554. [PMID: 34278907 DOI: 10.1080/10408398.2021.1951651] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
As they become more health conscious, consumers are paying increasing attention to food quality and safety. In coffee production, fraudulent strategies to reduce costs and maximize profits include mixing beans from two species of different economic value, the addition of other substances and/or foods, and mislabeling. Therefore, testing for coffee authenticity and detecting adulterants is required for value assessment and consumer protection. Here we provide an overview of the chromatography, spectroscopy, and single-nucleotide polymorphism-based methods used to distinguish between the major coffee species Arabica and Robusta. This review also describes the techniques applied to trace the geographical origin of coffee, based mainly on the chemical composition of the beans, an approach that can discriminate between coffee-growing regions on a continental or more local level. Finally, the analytical techniques used to detect coffee adulteration with other foods and/or coffee by-products are discussed, with a look at the practice of adding pharmacologically active compounds to coffee, and their harmful effects on health.
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Affiliation(s)
- Maria Perez
- Department of Nutrition, Food Science and Gastronomy XaRTA, Institute of Nutrition and Food Safety (INSA-UB), Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain.,Laboratory of Organic Chemistry, Faculty of Pharmacy and Food Sciences, University of Barcelona, Spain
| | - Inés Domínguez-López
- Department of Nutrition, Food Science and Gastronomy XaRTA, Institute of Nutrition and Food Safety (INSA-UB), Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain
| | - Anallely López-Yerena
- Department of Nutrition, Food Science and Gastronomy XaRTA, Institute of Nutrition and Food Safety (INSA-UB), Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain
| | - Anna Vallverdú Queralt
- Department of Nutrition, Food Science and Gastronomy XaRTA, Institute of Nutrition and Food Safety (INSA-UB), Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain.,Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
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11
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Mittal M, Sharma K, Rathore A. Checking counterfeiting of pharmaceutical products by attenuated total reflection mid-infrared spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 255:119710. [PMID: 33774413 DOI: 10.1016/j.saa.2021.119710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 03/10/2021] [Accepted: 03/11/2021] [Indexed: 06/12/2023]
Abstract
Pharmaceutical products serve as the cornerstone of our healthcare system. Product quality is of paramount importance to safety and efficacy of the patients. The success of pharmaceuticals has led to attempts by dubious manufacturers to gain via counterfeiting of the products, while risking the lives of the billions of patients that depend on these products. As a result, there is critical need for an analytical tool that is simple to operate, is robust and lends itself to yielding a rapid fingerprint of a pharmaceutical. In this paper we suggest use of attenuated total reflection (ATR) mid-infrared spectroscopy as a tool for rapid fingerprinting of pharmaceuticals. Antibiotics have been used as a case study to demonstrate the utility of this approach. ATR mid-infrared spectra obtained from powdered solid pharmaceutical products were classified using multivariate data analysis. A partial least-squares discriminant analysis model was developed and tested using 57 pharmaceutical products (27 antibiotics). The model was able to predict antibiotic present in pharmaceutical formulation irrespective of brand or manufacturing process with a classification accuracy of 87.3%. This indicated that the model is robust with respect to variability in pharmaceutical formulations. In addition, the brand/manufacturing company of an antibiotic could be predicted by training a principal component analysis model for specific antibiotic to a classification accuracy of 90%. The results demonstrate the utility of the proposed approach, which can be used by the appropriate authorities for checking on counterfeiting of pharmaceutical products.
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Affiliation(s)
- Manya Mittal
- Department of Chemical Engineering, Centre of Excellence for Biopharmaceutical Technology, Indian Institute of Technology Delhi, New Delhi 110016, India
| | - Kritika Sharma
- Department of Chemical Engineering, Centre of Excellence for Biopharmaceutical Technology, Indian Institute of Technology Delhi, New Delhi 110016, India
| | - Anurag Rathore
- Department of Chemical Engineering, Centre of Excellence for Biopharmaceutical Technology, Indian Institute of Technology Delhi, New Delhi 110016, India.
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12
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Levate Macedo L, da Silva Araújo C, Costa Vimercati W, Gherardi Hein PR, Pimenta CJ, Henriques Saraiva S. Evaluation of chemical properties of intact green coffee beans using near-infrared spectroscopy. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2021; 101:3500-3507. [PMID: 33274765 DOI: 10.1002/jsfa.10981] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2020] [Revised: 11/20/2020] [Accepted: 12/04/2020] [Indexed: 06/12/2023]
Abstract
BACKGROUND The chemical compounds in coffee are important indicators of quality. Its composition varies according to several factors related to the planting and processing of coffee. Thus, this study proposed to use near-infrared spectroscopy (NIR) associated with partial least squares (PLS) regression to estimate quickly some chemical properties (moisture content, soluble solids, and total and reducing sugars) in intact green coffee samples. For this, 250 samples produced in Brazil were analyzed in the laboratory by the standard method and also had their spectra recorded. RESULTS The calibration models were developed using PLS regression with cross-validation and tested in a validation set. The models were elaborated using original spectra and preprocessed by five different mathematical methods. These models were compared in relation to the coefficient of determination, root mean square error of cross-validation (RMSECV), root mean square error of test set validation (RMSEP), and ratio of performance to deviation (RPD) and demonstrated different predictive capabilities for the chemical properties of coffee. The best model was obtained to predict grain moisture and the worst performance was observed for the soluble solids model. The highest determination coefficients obtained for the samples in the validation set were equal to 0.810, 0.516, 0.694 and 0.781 for moisture, soluble solids, total sugar, and reducing sugars, respectively. CONCLUSION The statistics associated with these models indicate that NIR technology has the potential to be applied routinely to predict the chemical properties of green coffee, and in particular, for moisture analysis. However, the soluble solid and total sugar content did not show high correlations with the spectroscopic data and need to be improved. © 2020 Society of Chemical Industry.
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Affiliation(s)
- Leandro Levate Macedo
- Department of Food Engineering, Center of Agrarian Sciences and Engineering, Federal University of Espírito Santo, Alegre, Brazil
| | - Cintia da Silva Araújo
- Department of Food Engineering, Center of Agrarian Sciences and Engineering, Federal University of Espírito Santo, Alegre, Brazil
| | - Wallaf Costa Vimercati
- Department of Food Engineering, Center of Agrarian Sciences and Engineering, Federal University of Espírito Santo, Alegre, Brazil
| | | | | | - Sérgio Henriques Saraiva
- Department of Food Engineering, Center of Agrarian Sciences and Engineering, Federal University of Espírito Santo, Alegre, Brazil
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13
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Coffee beyond the cup: analytical techniques used in chemical composition research—a review. Eur Food Res Technol 2021. [DOI: 10.1007/s00217-020-03679-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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14
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Mendes E, Duarte N. Mid-Infrared Spectroscopy as a Valuable Tool to Tackle Food Analysis: A Literature Review on Coffee, Dairies, Honey, Olive Oil and Wine. Foods 2021; 10:foods10020477. [PMID: 33671755 PMCID: PMC7926530 DOI: 10.3390/foods10020477] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 02/15/2021] [Accepted: 02/17/2021] [Indexed: 12/12/2022] Open
Abstract
Nowadays, food adulteration and authentication are topics of utmost importance for consumers, food producers, business operators and regulatory agencies. Therefore, there is an increasing search for rapid, robust and accurate analytical techniques to determine the authenticity and to detect adulteration and misrepresentation. Mid-infrared spectroscopy (MIR), often associated with chemometric techniques, offers a fast and accurate method to detect and predict food adulteration based on the fingerprint characteristics of the food matrix. In the first part of this review the basic concepts of infrared spectroscopy, sampling techniques, as well as an overview of chemometric tools are summarized. In the second part, recent applications of MIR spectroscopy to the analysis of foods such as coffee, dairy products, honey, olive oil and wine are discussed, covering a timespan from 2010 to mid-2020. The literature gathered in this article clearly reveals that the MIR spectroscopy associated with attenuated total reflection acquisition mode and different chemometric tools have been broadly applied to address quality, authenticity and adulteration issues. This technique has the advantages of being simple, fast and easy to use, non-destructive, environmentally friendly and, in the future, it can be applied in routine analyses and official food control.
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15
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Marcheafave GG, Tormena CD, Mattos LE, Liberatti VR, Ferrari ABS, Rakocevic M, Bruns RE, Scarminio IS, Pauli ED. The main effects of elevated CO 2 and soil-water deficiency on 1H NMR-based metabolic fingerprints of Coffea arabica beans by factorial and mixture design. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 749:142350. [PMID: 33370915 DOI: 10.1016/j.scitotenv.2020.142350] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 08/20/2020] [Accepted: 09/09/2020] [Indexed: 06/12/2023]
Abstract
The metabolic response of Coffea arabica trees in the face of the rising atmospheric concentration of carbon dioxide (CO2) combined with the reduction in soil-water availability is complex due to the various (bio)chemical feedbacks. Modern analytical tools and the experimental advance of agronomic science tend to advance in the understanding of the metabolic complexity of plants. In this work, Coffea arabica trees were grown in a Free-Air Carbon Dioxide Enrichment dispositive under factorial design (22) conditions considering two CO2 levels and two soil-water availabilities. The 1H NMR mixture design-fingerprinting effects of CO2 and soil-water levels on beans were strategically investigated using the principal component analysis (PCA), analysis of variance (ANOVA) - simultaneous component analysis (ASCA) and partial least squares-discriminant analysis (PLS-DA). From the ASCA, the CO2 factor had a significant effect on changing the 1H NMR profile of fingerprints. The soil-water factor and interaction (CO2 × soil-water) were not significant. 1H NMR fingerprints with PCA, ASCA and PLS-DA analysis determined spectral profiles for fatty acids, caffeine, trigonelline and glucose increases in beans from current CO2, while quinic acid/chlorogenic acids, malic acid and kahweol/cafestol increased in coffee beans from elevated CO2. PLS-DA results revealed a good classification performance between the significant effect of the atmospheric CO2 levels on the fingerprints, regardless of the soil-water availabilities. Finally, the PLS-DA model showed good prediction ability, successfully classifying validation data-set of coffee beans collected over the vertical profile of the plants and included several fingerprints of different extracting solvents. The results of this investigation suggest that the association of experimental design, mixture design, PCA, ASCA and PLS-DA can provide accurate information on a series of metabolic changes provoked by climate changes in products of commercial importance, in addition to minimizing the extra work necessary in classic analytical approaches, encouraging the development of similar strategies.
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Affiliation(s)
- Gustavo Galo Marcheafave
- Laboratory of Chemometrics in Natural Sciences (LQCN), Department of Chemistry, State University of Londrina, CP 6001, 86051-990 Londrina, PR, Brazil.
| | - Cláudia Domiciano Tormena
- Laboratory of Chemometrics in Natural Sciences (LQCN), Department of Chemistry, State University of Londrina, CP 6001, 86051-990 Londrina, PR, Brazil
| | - Lavínia Eduarda Mattos
- Laboratory of Chemometrics in Natural Sciences (LQCN), Department of Chemistry, State University of Londrina, CP 6001, 86051-990 Londrina, PR, Brazil
| | - Vanessa Rocha Liberatti
- Department of Chemistry, State University of Londrina, CP 6001, 86051-990 Londrina, PR, Brazil
| | | | - Miroslava Rakocevic
- Northern Rio de Janeiro State University - UENF, Plant Physiology Lab, Av. Alberto Lamego 2000, 28013-602 Campos dos Goytacazes, RJ, Brazil; Embrapa Environment, Rodovia SP 340, Km 127.5, 13820-000 Jaguariúna, SP, Brazil
| | - Roy Edward Bruns
- Institute of Chemistry, State University of Campinas, CP 6154, 13083-970 Campinas, SP, Brazil
| | - Ieda Spacino Scarminio
- Laboratory of Chemometrics in Natural Sciences (LQCN), Department of Chemistry, State University of Londrina, CP 6001, 86051-990 Londrina, PR, Brazil.
| | - Elis Daiane Pauli
- Institute of Chemistry, State University of Campinas, CP 6154, 13083-970 Campinas, SP, Brazil
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16
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Burton IW, Martinez Farina CF, Ragupathy S, Arunachalam T, Newmaster S, Berrué F. Quantitative NMR Methodology for the Authentication of Roasted Coffee and Prediction of Blends. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2020; 68:14643-14651. [PMID: 33252222 DOI: 10.1021/acs.jafc.0c06239] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
In response to the need from the food industry for new analytical solutions, a fit-for-purpose quantitative 1H NMR methodology was developed to authenticate pure coffee (100% arabica or robusta) as well as predict the percentage of robusta in blends through the study of 292 roasted coffee samples in triplicate. Methanol was chosen as the extraction solvent, which led to the quantitation of 12 coffee constituents: caffeine, trigonelline, 3- and 5-caffeoylquinic acid, lipids, cafestol, nicotinic acid, N-methylpyridinium, formic acid, acetic acid, kahweol, and 16-O-methylcafestol. To overcome the chemical complexity of the methanolic extract, quantitative analysis was performed using a combination of traditional integration and spectral deconvolution methods. As a result, the proposed methodology provides a systematic methodology and a linear regression model to support the classification of known and unknown roasted coffees and their blends.
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Affiliation(s)
- Ian W Burton
- Aquatic and Crop Resources Development Research Center, National Research Council of Canada, 1411 Oxford Street, Halifax, Nova Scotia B3H 3Z1, Canada
| | - Camilo F Martinez Farina
- Aquatic and Crop Resources Development Research Center, National Research Council of Canada, 1411 Oxford Street, Halifax, Nova Scotia B3H 3Z1, Canada
| | - Subramanyam Ragupathy
- NHP Research Alliance, College of Biological Sciences, University of Guelph, Guelph, Ontario N1G 4T2, Canada
| | | | - Steve Newmaster
- NHP Research Alliance, College of Biological Sciences, University of Guelph, Guelph, Ontario N1G 4T2, Canada
| | - Fabrice Berrué
- Aquatic and Crop Resources Development Research Center, National Research Council of Canada, 1411 Oxford Street, Halifax, Nova Scotia B3H 3Z1, Canada
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17
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Anyidoho EK, Teye E, Agbemafle R. Nondestructive authentication of the regional and geographical origin of cocoa beans by using a handheld NIR spectrometer and multivariate algorithm. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2020; 12:4150-4158. [PMID: 32776043 DOI: 10.1039/d0ay00901f] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Traceability in the cocoa bean trade is vital to ensuring quality. In this study, a handheld near-infrared (NIR) spectrometer was attempted for rapid and nondestructive regional and geographical classification of cocoa beans from different locations. Cocoa bean samples collected from seven cocoa-producing regions in Ghana (Eastern, Ashanti, Volta, Western South, Western North, Central, and Brong Ahafo) and four cocoa-producing countries in Africa (Uganda, Ivory Coast, Nigeria, and Ghana) were used. Among the preprocessing techniques employed, multiplicative scatter correction (MSC) performed better. The correct classification rate for the seven cocoa-producing regions in Ghana was 100% for LDA and SVM models in the training set and testing set. For classification of cocoa beans based on the country of origin, LDA and SVM also gave 100% classification rate both in the training set and testing set. The results give strong indications that hand-held spectroscopy coupled with chemometrics could be employed to provide the quick, accurate, and nondestructive classification of cocoa beans according to different locations. This technique could improve the work of quality control inspectors both from industry and regulatory perspectives for effective and quick detection of cocoa bean fraud.
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Affiliation(s)
- Elliot K Anyidoho
- University of Cape Coast, College of Agriculture and Natural Sciences, School of Agriculture, Department of Agricultural Engineering, Cape Coast, Ghana
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18
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Lachenmeier DW, Teipel J, Scharinger A, Kuballa T, Walch SG, Grosch F, Bunzel M, Okaru AO, Schwarz S. Fully Automated Identification of Coffee Species and Simultaneous Quantification of Furfuryl Alcohol Using NMR Spectroscopy. J AOAC Int 2020; 103:306-314. [PMID: 33241277 DOI: 10.1093/jaocint/qsz020] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 10/22/2019] [Indexed: 11/14/2022]
Abstract
BACKGROUND Coffee is a popular beverage with two species, Coffea canephora and C. arabica, being commercially exploited. The quality and commercial value of coffee is dependent on species and processing. C. arabica typically obtains a higher price on the market compared to C. canephora. Coffee beans undergo roasting during processing, resulting in the formation of flavor compounds including furfuryl alcohol which has been classified by the International Agency for Research on Cancer as possibly carcinogenic to humans (Group 2B). OBJECTIVE The aim of this study was to identify coffee species and other properties using nuclear magnetic resonance (NMR) spectroscopy, specifically to conduct quantification of the roasting process contaminant furfuryl alcohol. METHOD The quantification of furfuryl alcohol was performed from the NMR spectra using the pulse length-based concentration (PULCON) methodology. Prior to NMR analysis, samples were extracted using deuterated chloroform. RESULTS Roasting experiments identified the maximum roasting temperature to be the most significant factor in the formation of furfuryl alcohol. Among the coffee species, C. canephora was found to contain a relatively lower amount of furfuryl alcohol compared to C. arabica. The roasting of wet processed coffee resulted in higher contents of furfuryl alcohol. Geographical origin and variety within species had no influence on the furfuryl alcohol content. CONCLUSION Validation results show that NMR spectroscopy is fit-for-purpose to obtain targeted information of coffee samples. HIGHLIGHTS The PULCON NMR methodology allows a simple, rapid and accurate determination of constituents of coffee.
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Affiliation(s)
- Dirk W Lachenmeier
- Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Strasse 3, 76187 Karlsruhe, Germany
| | - Jan Teipel
- Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Strasse 3, 76187 Karlsruhe, Germany
| | - Andreas Scharinger
- Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Strasse 3, 76187 Karlsruhe, Germany
| | - Thomas Kuballa
- Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Strasse 3, 76187 Karlsruhe, Germany
| | - Stephan G Walch
- Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Strasse 3, 76187 Karlsruhe, Germany
| | - Franziska Grosch
- Karlsruhe Institute of Technology (KIT), Institute of Applied Bioscience, Department of Food Chemistry and Phytochemistry, Adenauerring 20a, 76131 Karlsruhe, Germany
| | - Mirko Bunzel
- Karlsruhe Institute of Technology (KIT), Institute of Applied Bioscience, Department of Food Chemistry and Phytochemistry, Adenauerring 20a, 76131 Karlsruhe, Germany
| | - Alex O Okaru
- University of Nairobi, Department of Pharmaceutical Chemistry, P.O. Box 19676-00202 Nairobi, Kenya
| | - Steffen Schwarz
- Coffee Consulate, Hans-Thoma-Straße 20, 68163 Mannheim, Germany
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19
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Okaru AO, Scharinger A, Rajcic de Rezende T, Teipel J, Kuballa T, Walch SG, Lachenmeier DW. Validation of a Quantitative Proton Nuclear Magnetic Resonance Spectroscopic Screening Method for Coffee Quality and Authenticity (NMR Coffee Screener). Foods 2020; 9:E47. [PMID: 31947906 PMCID: PMC7023380 DOI: 10.3390/foods9010047] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Revised: 12/23/2019] [Accepted: 01/01/2020] [Indexed: 11/16/2022] Open
Abstract
Monitoring coffee quality as a means of detecting and preventing economically motivated fraud is an important aspect of international commerce today. Therefore, there is a compelling need for rapid high throughput validated analytical techniques such as quantitative proton nuclear magnetic resonance (NMR) spectroscopy for screening and authenticity testing. For this reason, we sought to validate an 1H NMR spectroscopic method for the routine screening of coffee for quality and authenticity. A factorial experimental design was used to investigate the influence of the NMR device, extraction time, and nature of coffee on the content of caffeine, 16-O-methylcafestol (OMC), kahweol, furfuryl alcohol, and 5-hydroxymethylfurfural (HMF) in coffee. The method was successfully validated for specificity, selectivity, sensitivity, and linearity of detector response. The proposed method produced satisfactory precision for all analytes in roasted coffee, except for kahweol in canephora (robusta) coffee. The proposed validated method may be used for routine screening of roasted coffee for quality and authenticity control (i.e., arabica/robusta discrimination), as its applicability was demonstrated during the recent OPSON VIII Europol-Interpol operation on coffee fraud control.
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Affiliation(s)
- Alex O. Okaru
- Department of Pharmaceutical Chemistry, University of Nairobi, P.O. Box 19676-00202 Nairobi, Kenya;
| | - Andreas Scharinger
- Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Straße 3, 76187 Karlsruhe, Germany; (A.S.); (T.R.d.R.); (J.T.); (T.K.); (S.G.W.)
| | - Tabata Rajcic de Rezende
- Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Straße 3, 76187 Karlsruhe, Germany; (A.S.); (T.R.d.R.); (J.T.); (T.K.); (S.G.W.)
| | - Jan Teipel
- Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Straße 3, 76187 Karlsruhe, Germany; (A.S.); (T.R.d.R.); (J.T.); (T.K.); (S.G.W.)
| | - Thomas Kuballa
- Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Straße 3, 76187 Karlsruhe, Germany; (A.S.); (T.R.d.R.); (J.T.); (T.K.); (S.G.W.)
| | - Stephan G. Walch
- Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Straße 3, 76187 Karlsruhe, Germany; (A.S.); (T.R.d.R.); (J.T.); (T.K.); (S.G.W.)
| | - Dirk W. Lachenmeier
- Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Straße 3, 76187 Karlsruhe, Germany; (A.S.); (T.R.d.R.); (J.T.); (T.K.); (S.G.W.)
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20
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Giraudo A, Grassi S, Savorani F, Gavoci G, Casiraghi E, Geobaldo F. Determination of the geographical origin of green coffee beans using NIR spectroscopy and multivariate data analysis. Food Control 2019. [DOI: 10.1016/j.foodcont.2018.12.033] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
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21
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Innamorato V, Longobardi F, Lippolis V, Cortese M, Logrieco AF, Catucci L, Agostiano A, De Girolamo A. Tracing the Geographical Origin of Lentils (Lens culinaris Medik.) by Infrared Spectroscopy and Chemometrics. FOOD ANAL METHOD 2018. [DOI: 10.1007/s12161-018-1406-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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22
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Insights into Geographic and Temporal Variation in Fatty Acid Composition of Croton Nuts Using ATR-FTIR. Int J Anal Chem 2018; 2018:4739759. [PMID: 30254676 PMCID: PMC6140129 DOI: 10.1155/2018/4739759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2018] [Accepted: 08/15/2018] [Indexed: 11/17/2022] Open
Abstract
Croton megalocarpus seedcake oils from 30 different locations in south central Kenya were analyzed for their fatty acid composition using ATR-FTIR to determine the efficacy of a simple procedure for measuring initial geographic and subsequent temporal variation during five months of seed storage. To our knowledge, this is the first report showing variation in how oils in untreated nuts from different locations change during storage, and how these differences are correlated with local environments. These variations are important to forensic authentication efforts and they provide insights into ways to optimize Croton oil composition.
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