1
|
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
| | | |
Collapse
|
2
|
Lázaro MC, Ferreira EJ, Gomes Neto JA, Ferreira EC. Characterization and predictive modeling potential of aging time of roasted coffee using infrared spectroscopy. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2022; 14:3486-3492. [PMID: 36073986 DOI: 10.1039/d2ay00907b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Repackaging and tampering with labels of foods to extend their shelf life is an illegal practice, increasingly common in some Brazilian coffee retail markets. Fast, easy-to-use, and low-cost analytical techniques for the large-scale screening of aging time have been demanded lately to fight the growth of these frauds in retail coffee markets. In this work, Fourier transform infrared spectroscopy was evaluated as a provider of relevant regressors, chemically explainable, aiming for predictive models for estimating the aging of roasted and packaged coffees during their shelf life. Spectra of two Coffea arabica varieties (Bourbon and Obatã) were periodically acquired during eleven months of storage. The most relevant absorption bands were selected, which showed a moderate correlation with the storage time. They were identified as responses from lipids, phenolic compounds, and carbohydrates. From those responsive bands, logistic regression (sigmoid functions) models were fitted for each coffee variety, as well as for both together. Predictive models for Bourbon and Obatã showed high performances in validation data, with r (Pearson correlation) above 0.92 and root mean square error (RMSE) below 43 days. For both varieties, the logistic model showed r greater than 0.83 and RMSE equal to 56 days. Results corroborate the methodological approach efficacy towards agile technological innovations in the coffee value chain, as well as opening new application fronts for estimating the aging of other foods.
Collapse
Affiliation(s)
- Maisa Cristina Lázaro
- São Paulo State University - UNESP, Chemistry Institute of Araraquara, Dep. of Analytical, Physical-Chemical and Inorganic Chemistry, P.O. Box 355, 14801-970, Araraquara, SP, Brazil.
| | | | - José Anchieta Gomes Neto
- São Paulo State University - UNESP, Chemistry Institute of Araraquara, Dep. of Analytical, Physical-Chemical and Inorganic Chemistry, P.O. Box 355, 14801-970, Araraquara, SP, Brazil.
| | - Edilene Cristina Ferreira
- São Paulo State University - UNESP, Chemistry Institute of Araraquara, Dep. of Analytical, Physical-Chemical and Inorganic Chemistry, P.O. Box 355, 14801-970, Araraquara, SP, Brazil.
| |
Collapse
|
3
|
Comparison of Spectroscopy-Based Methods and Chemometrics to Confirm Classification of Specialty Coffees. Foods 2022; 11:foods11111655. [PMID: 35681405 PMCID: PMC9180846 DOI: 10.3390/foods11111655] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 05/31/2022] [Accepted: 06/02/2022] [Indexed: 01/27/2023] Open
Abstract
The Specialty Coffee Association (SCA) sensory analysis protocol is the methodology that is used to classify specialty coffees. However, because the sensory analysis is sensitive to the taster’s training, cognitive psychology, and physiology, among other parameters, the feasibility of instrumental approaches has been recently studied for complementing such analyses. Spectroscopic methods, mainly near infrared (NIR) and mid infrared (FTIR—Fourier Transform Infrared), have been extensively employed for food quality authentication. In view of the aforementioned, we compared NIR and FTIR to distinguish different qualities and sensory characteristics of specialty coffee samples in the present study. Twenty-eight green coffee beans samples were roasted (in duplicate), with roasting conditions following the SCA protocol for sensory analysis. FTIR and NIR were used to analyze the ground and roasted coffee samples, and the data then submitted to statistical analysis to build up PLS models in order to confirm the quality classifications. The PLS models provided good predictability and classification of the samples. The models were able to accurately predict the scores of specialty coffees. In addition, the NIR spectra provided relevant information on chemical bonds that define specialty coffee in association with sensory aspects, such as the cleanliness of the beverage.
Collapse
|
4
|
Use of convolutional neural network (CNN) combined with FT-NIR spectroscopy to predict food adulteration: A case study on coffee. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.108816] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
|
5
|
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.
Collapse
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.)
| |
Collapse
|
6
|
Mendes GDA, De Oliveira MAL, Rodarte MP, De Carvalho Dos Anjos V, Bell MJV. Origin geographical classification of green coffee beans (Coffea Arabica L.) produced in different regions of the Minas Gerais state by FT-MIR and chemometric. Curr Res Food Sci 2022; 5:298-305. [PMID: 35198988 PMCID: PMC8844797 DOI: 10.1016/j.crfs.2022.01.017] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 01/20/2022] [Accepted: 01/21/2022] [Indexed: 11/29/2022] Open
Abstract
The present work was proposal the potential evaluation of Fourier-Transform Mid-Infrared (FT-MIR) associated with chemometric approach in green beans, in order to discriminate the origin of special Arabica coffees in a single state that has heterogeneous environments. Partial Least Squares Discriminant Analysis (PLS-DA) model presented as result: 3 latent variables, R2X (cum) = 0.892, R2Y (cum) = 0.659; Q2Y (cum) = 0.494, RMSEP = 0.182387, p-value CV-Anova = 0.009, 100% of both sensitivity and specificity and the prediction classification obtained was: 100, 83.33, 100, 83.33% for class 1, class 2, class 3 and class 4, respectively. These results can be considered adequate for the proposed hypothesis. The obtained results that the regions have markers such as trigonelline, chlorogenic and fatty acids, sensitive to absorption in the mid-infrared and that are able to determine the origin of green coffee beans of Arabica. Thus, the FT-MIR associated with chemometrics has the potential to employ speed, modernity and cost reduction in the certification of origin of coffees. The origin of special arabica coffee beans in the same state was discriminated using MIR. The study identified green coffee beans of the same species from neighboring regions. Trigonelline, chlorogenic and fatty acid absorption bands are good origin markers. The coffee cultivation environment interferes decisively in the final composition.
Collapse
|
7
|
Yulia M, Suhandy D. Quantification of Corn Adulteration in Wet and Dry-Processed Peaberry Ground Roasted Coffees by UV-Vis Spectroscopy and Chemometrics. Molecules 2021; 26:molecules26206091. [PMID: 34684672 PMCID: PMC8539780 DOI: 10.3390/molecules26206091] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 09/19/2021] [Accepted: 10/06/2021] [Indexed: 11/28/2022] Open
Abstract
In this present research, a spectroscopic method based on UV–Vis spectroscopy is utilized to quantify the level of corn adulteration in peaberry ground roasted coffee by chemometrics. Peaberry coffee with two types of bean processing of wet and dry-processed methods was used and intentionally adulterated by corn with a 10–50% level of adulteration. UV–Vis spectral data are obtained for aqueous samples in the range between 250 and 400 nm with a 1 nm interval. Three multivariate regression methods, including partial least squares regression (PLSR), multiple linear regression (MLR), and principal component regression (PCR), are used to predict the level of corn adulteration. The result shows that all individual regression models using individual wet and dry samples are better than that of global regression models using combined wet and dry samples. The best calibration model for individual wet and dry and combined samples is obtained for the PLSR model with a coefficient of determination in the range of 0.83–0.93 and RMSE below 6% (w/w) for calibration and validation. However, the error prediction in terms of RMSEP and bias were highly increased when the individual regression model was used to predict the level of corn adulteration with differences in the bean processing method. The obtained results demonstrate that the use of the global PLSR model is better in predicting the level of corn adulteration. The error prediction for this global model is acceptable with low RMSEP and bias for both individual and combined prediction samples. The obtained RPDp and RERp in prediction for the global PLSR model are more than two and five for individual and combined samples, respectively. The proposed method using UV–Vis spectroscopy with a global PLSR model can be applied to quantify the level of corn adulteration in peaberry ground roasted coffee with different bean processing methods.
Collapse
Affiliation(s)
- Meinilwita Yulia
- Department of Agricultural Technology, Lampung State Polytechnic, Jl. Soekarno Hatta No. 10, Rajabasa, Bandar Lampung 35141, Indonesia;
| | - Diding Suhandy
- Department of Agricultural Engineering, Faculty of Agriculture, The University of Lampung, Jl. Soemantri Brojonegoro No.1, Bandar Lampung 35145, Indonesia
- Correspondence: ; Tel.: +62-0813-7334-7128
| |
Collapse
|
8
|
Three centuries on the science of coffee authenticity control. Food Res Int 2021; 149:110690. [PMID: 34600685 DOI: 10.1016/j.foodres.2021.110690] [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] [Received: 03/29/2021] [Revised: 08/28/2021] [Accepted: 08/31/2021] [Indexed: 12/14/2022]
Abstract
Food authenticity relies on genuineness and reliability according to the information displayed on the package. Since the 18th century, when coffee became popularized in the West, adulteration began. Several methods have been developed to detect different kinds of frauds and they have evolved as demands increased and new technologies were introduced. The evolution of the science of coffee authenticity control in the past three centuries is reviewed, focusing on the discrimination between coffee and other foods or between coffee and its by-products. The earliest chemical and physical methods are presented followed by methods developed in the 20th and 21st centuries using microscopy, chromatography and spectroscopy associated with advanced statistical tools, and DNA-based methods. In addition to non-food material, before the 20th century, chicory was the most studied food-adulterant. From the 20th century on, corn, coffee by-products, and barley were the most studied, followed by chicory, rice and other food items. Matrix effects seem to be among the most challenging problems in these approaches, associated with variations in roast degree, particle size (particularly in spectroscopy-based methods), and lack of control over reference samples regarding species and purity. Limits of detection vary considerably within each category, with most limits being too high for commercial use. DNA-based methods appear to be promising to assess coffee authenticity, given that the limits of detection and quantification are low, and specificity is higher than in other methods. Nevertheless, as roast intensity increases, the sensitivity of the method decreases. So far, most reported methods have not been validated and only a few have been tested on commercial brands, except for those involving microscopy which has been highly used for monitoring coffee authenticity although not always efficiently enough.
Collapse
|
9
|
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.
Collapse
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
| |
Collapse
|
10
|
Photoacoustic Laser System for Food Fraud Detection. SENSORS 2021; 21:s21124178. [PMID: 34207037 PMCID: PMC8235699 DOI: 10.3390/s21124178] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 06/11/2021] [Accepted: 06/14/2021] [Indexed: 11/16/2022]
Abstract
Economically motivated adulterations of food, in general, and spices, in particular, are an emerging threat to world health. Reliable techniques for the rapid screening of counterfeited ingredients in the supply chain need further development. Building on the experience gained with CO2 lasers, the Diagnostic and Metrology Laboratory of ENEA realized a compact and user-friendly photoacoustic laser system for food fraud detection, based on a quantum cascade laser. The sensor has been challenged with saffron adulteration. Multivariate data analysis tools indicated that the photoacoustic laser system was able to detect adulterants at mass ratios of 2% in less than two minutes.
Collapse
|
11
|
A smart spectral analysis strategy-based UV and FT-IR spectroscopy fingerprint: Application to quality evaluation of compound liquorice tablets. J Pharm Biomed Anal 2021; 202:114172. [PMID: 34082163 DOI: 10.1016/j.jpba.2021.114172] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Revised: 04/21/2021] [Accepted: 05/22/2021] [Indexed: 10/21/2022]
Abstract
This study focuses on development of a smart spectral analysis strategy for rapid quality evaluation of complex sample. Firstly, the ultraviolet (UV) and Fourier Transform Infrared (FT-IR) spectroscopy were established. Secondly, the second derivative UV spectral was obtained and showed 7 major absorption peaks, which was the projection of the 3D-spectrum profile. It can perform peak matching like chromatogram, thus, helpful for 3D UV spectrum analysis, qualitatively and quantitatively. The qualitative and quantitative similarity results based on systematic quantified fingerprint method displayed basically a consistency with their hierarchical cluster analysis results. Notably, the quality evaluation of the first proposed FT-IR spectral quantized fingerprints and the good correlation of Pm% with PA (R2 = 0.80296), as well as the excellent quantitative prediction model for liquiritin, glycyrrhizinic acid and sodium benzoate all indicated the promising of FT-IR spectral quantized fingerprint in quantitative analysis and QC of compound liquorice tablets. Finally, an integrated evaluate strategy was developed by mean algorithm to reduce the error caused by single technique. 54 samples integrally had a good quality consistency as their quality ranged grade 1-5. This study illustrated that the smart data analysis strategy based on spectral fingerprint has potential to enhance existing methodologies for further rapid and integrated studies evaluating the quality of herbal medicine and its related products.
Collapse
|
12
|
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]
|
13
|
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.
Collapse
|
14
|
Song XC, Canellas E, Asensio E, Nerín C. Predicting the antioxidant capacity and total phenolic content of bearberry leaves by data fusion of UV–Vis spectroscopy and UHPLC/Q-TOF-MS. Talanta 2020; 213:120831. [DOI: 10.1016/j.talanta.2020.120831] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Revised: 02/10/2020] [Accepted: 02/11/2020] [Indexed: 01/21/2023]
|
15
|
Du C, Dai S, Zhao A, Qiao Y, Wu Z. Optimization of PLS modeling parameters via quality by design concept for Gardenia jasminoides Ellis using online NIR sensor. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2019; 222:117267. [PMID: 31247389 DOI: 10.1016/j.saa.2019.117267] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Revised: 05/14/2019] [Accepted: 06/09/2019] [Indexed: 06/09/2023]
Abstract
This paper discussed the process parameters optimization of partial least-square (PLS) modeling according to quality by design (QbD) concept. D-optimal design and online near-infrared (NIR) sensor were proposed to analysis the Geniposide in Gardenia jasminoides Ellis using above process parameters to achieve robustness PLS model. Four critical model parameters (CMPs) were identified to construct a D-optimal design, which included the selection of sample set, spectra pre-processing, latent variables and variable selection methods. NIR sensor dataset was obtained under a pilot scale system. The D-optimal design optimization strategy resulted in a robust PLS model with the optimal parameters, 1/2 samples for calibration sets through Baseline spectra pre-processing with SiPLS-selecting variables under 8 factors. The critical evaluation attributes (CEAs) of PLS model were recommended as follows: the RMSEC and Rcal2 of the calibration set were 0.005901 and 0.9983. The RMSEP and Rpre2 of the validation set were 0.02002 and 0.9845. The multivariate detection limit (MDL) was 1.143 × 10-3. Therefore, design space of CMPs which affected CEAs of PLS model was established. The result demonstrated that the proposed method was beneficial for the robustness of PLS model, which also showed a significant guideline for the design and development of PLS model.
Collapse
Affiliation(s)
- Chenzhao Du
- Beijing University of Chinese Medicine, 100102 Beijing, China; Pharmaceutical Engineering and New Drug Development of Traditional Chinese Medicine (TCM) of Ministry of Education, 100102 Beijing, China; Key Laboratory of TCM-information Engineering of State Administration of TCM, 100102 Beijing, China
| | - Shengyun Dai
- Beijing University of Chinese Medicine, 100102 Beijing, China; Pharmaceutical Engineering and New Drug Development of Traditional Chinese Medicine (TCM) of Ministry of Education, 100102 Beijing, China; Key Laboratory of TCM-information Engineering of State Administration of TCM, 100102 Beijing, China
| | - Anbang Zhao
- Beijing University of Chinese Medicine, 100102 Beijing, China; Pharmaceutical Engineering and New Drug Development of Traditional Chinese Medicine (TCM) of Ministry of Education, 100102 Beijing, China; Key Laboratory of TCM-information Engineering of State Administration of TCM, 100102 Beijing, China; Traditional Chinese Medicine College of Xinjiang Medical University, 830011 Urumqi, China
| | - Yanjiang Qiao
- Beijing University of Chinese Medicine, 100102 Beijing, China; Pharmaceutical Engineering and New Drug Development of Traditional Chinese Medicine (TCM) of Ministry of Education, 100102 Beijing, China; Key Laboratory of TCM-information Engineering of State Administration of TCM, 100102 Beijing, China.
| | - Zhisheng Wu
- Beijing University of Chinese Medicine, 100102 Beijing, China; Pharmaceutical Engineering and New Drug Development of Traditional Chinese Medicine (TCM) of Ministry of Education, 100102 Beijing, China; Key Laboratory of TCM-information Engineering of State Administration of TCM, 100102 Beijing, China.
| |
Collapse
|
16
|
|
17
|
Baqueta MR, Coqueiro A, Valderrama P. Brazilian Coffee Blends: A Simple and Fast Method by Near-Infrared Spectroscopy for the Determination of the Sensory Attributes Elicited in Professional Coffee Cupping. J Food Sci 2019; 84:1247-1255. [PMID: 31116425 DOI: 10.1111/1750-3841.14617] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2018] [Revised: 02/24/2019] [Accepted: 03/22/2019] [Indexed: 12/14/2022]
Abstract
The diversity of compounds and variations in the aroma and flavor of ground and roasted coffee make the sensory evaluation by the "cupping test" a complex task to be performed. A total of 217 commercial coffee samples classified as different beverage type and with different roast degrees were evaluated by official cuppers in the "cupping test" and the responses for sensory attributes were used to verify the correlation to the near-infrared (NIR) spectra. Chemometric models based on partial least squares (PLS) were built for the powder fragrance, drink aroma, acidity, bitterness, flavor, body, astringency, residual flavor, and overall quality. The parameters of merit such as accuracy, fit, linearity, residual prediction deviation, sensitivity, analytical sensitivity, limits of detection, and quantification were evaluated. All sensory attributes were predicted with adequate values according to the parameters of merit. The proposed method, when compared to the "cupping test," is an alternative to the determination of the coffee sensory attributes. The results demonstrated that the use of NIR associated with chemometrics is efficient and recommended for the prediction of sensorial attributes of coffee by means of the direct analysis of roasted and ground samples, and without any additional preparation, it is a promising tool for the coffee industry. PRACTICAL APPLICATION: This study has shown potential use of near-infrared (NIR) spectroscopy coupled with a chemometric tool for the prediction of sensory attributes of commercial coffees. Prediction models for powder fragrance, drink aroma, acidity, bitterness, flavor, body, astringency, residual flavor, and overall quality were built and showed good predictive capacity. The use of NIR allows rapid analysis (1 min or less per sample), and it was possible to evaluate all sensory attributes directly in roasted and ground coffee, without beverage preparation.
Collapse
Affiliation(s)
- Michel Rocha Baqueta
- Universidade Tecnológica Federal do Paraná (UTFPR), CEP, 87301-899, P.O. Box 271, Campo Mourão, Paraná, Brazil
| | - Aline Coqueiro
- Universidade Tecnológica Federal do Paraná (UTFPR), CEP, 87301-899, P.O. Box 271, Campo Mourão, Paraná, Brazil
| | - Patrícia Valderrama
- Universidade Tecnológica Federal do Paraná (UTFPR), CEP, 87301-899, P.O. Box 271, Campo Mourão, Paraná, Brazil
| |
Collapse
|
18
|
Uncu AT, Uncu AO. Plastid trnH-psbA intergenic spacer serves as a PCR-based marker to detect common grain adulterants of coffee ( Coffea arabica L.). Food Control 2018. [DOI: 10.1016/j.foodcont.2018.03.029] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
|
19
|
Quantitative assessment of specific defects in roasted ground coffee via infrared-photoacoustic spectroscopy. Food Chem 2018; 255:132-138. [DOI: 10.1016/j.foodchem.2018.02.076] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2017] [Revised: 02/08/2018] [Accepted: 02/13/2018] [Indexed: 01/22/2023]
|
20
|
Vidal M, Garcia-Arrona R, Bordagaray A, Ostra M, Albizu G. Simultaneous determination of color additives tartrazine and allura red in food products by digital image analysis. Talanta 2018; 184:58-64. [DOI: 10.1016/j.talanta.2018.02.111] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Revised: 02/23/2018] [Accepted: 02/27/2018] [Indexed: 11/29/2022]
|
21
|
Su WH, Sun DW. Fourier Transform Infrared and Raman and Hyperspectral Imaging Techniques for Quality Determinations of Powdery Foods: A Review. Compr Rev Food Sci Food Saf 2017; 17:104-122. [DOI: 10.1111/1541-4337.12314] [Citation(s) in RCA: 92] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2017] [Revised: 09/12/2017] [Accepted: 09/14/2017] [Indexed: 12/13/2022]
Affiliation(s)
- Wen-Hao Su
- Food Refrigeration and Computerized Food Technology (FRCFT), School of Biosystems and Food Engineering, Agriculture & Food Science Centre, Univ. College Dublin (UCD); National Univ. of Ireland; Belfield Dublin 4 Ireland
| | - Da-Wen Sun
- Food Refrigeration and Computerized Food Technology (FRCFT), School of Biosystems and Food Engineering, Agriculture & Food Science Centre, Univ. College Dublin (UCD); National Univ. of Ireland; Belfield Dublin 4 Ireland
| |
Collapse
|
22
|
|
23
|
Simultaneous Detection of Multiple Adulterants in Ground Roasted Coffee by ATR-FTIR Spectroscopy and Data Fusion. FOOD ANAL METHOD 2017. [DOI: 10.1007/s12161-017-0832-3] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
|
24
|
Ground Roast Coffee: Review of Analytical Strategies to Estimate Geographic Origin, Species Authenticity and Adulteration by Dilution. FOOD ANAL METHOD 2017. [DOI: 10.1007/s12161-016-0756-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
|
25
|
Free tocopherols as chemical markers for Arabica coffee adulteration with maize and coffee by-products. Food Control 2016. [DOI: 10.1016/j.foodcont.2016.06.011] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
|
26
|
Assessing saffron (Crocus sativus L.) adulteration with plant-derived adulterants by diffuse reflectance infrared Fourier transform spectroscopy coupled with chemometrics. Talanta 2016; 162:558-566. [PMID: 27837871 DOI: 10.1016/j.talanta.2016.10.072] [Citation(s) in RCA: 84] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2016] [Revised: 10/16/2016] [Accepted: 10/18/2016] [Indexed: 01/05/2023]
Abstract
Saffron, the dried red stigmas of the plant Crocus sativus L., is well-known as one of the most important and expensive spices worldwide. It is thus highly susceptible to fraudulent practices that employ, among others, plant-derived adulterants. This study presents an application of diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and chemometric techniques for evaluating adulteration of saffron with six characteristic adulterants of plant origin, i.e. C. sativus stamens, calendula, safflower, turmeric, buddleja, and gardenia. The proposed method involved a three-step process for the detection of adulteration as well as for the identification and quantification of adulterants. Partial least squares discriminant analysis (PLS-DA) was applied to perform authentication of saffron based on mid-infrared fingerprints (4000-600cm-1), resulting in 99% correct classification of pure saffron and saffron adulterated at 5-20% (w/w) levels. Adulterant identification in positive samples was performed with high sensitivity and specificity by a six-class PLS-DA model, with spectroscopic data from the region 2000-600cm-1. Subsequently, partial least squares (PLS) regression models were built for the quantification of each adulterant. By using synergy interval PLS (siPLS) for variable selection, models with improved performance were developed, with detection limits ranging from 1.0% to 3.1% (w/w). The results obtained illustrate that this strategy based on DRIFTS has the potential to complement existing methodologies for the rapid and cost-effective assessment of typical saffron frauds.
Collapse
|
27
|
Winkler-Moser JK, Singh M, Rennick KA, Bakota EL, Jham G, Liu SX, Vaughn SF. Detection of Corn Adulteration in Brazilian Coffee (Coffea arabica) by Tocopherol Profiling and Near-Infrared (NIR) Spectroscopy. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2015; 63:10662-10668. [PMID: 26600312 DOI: 10.1021/acs.jafc.5b04777] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Coffee is a high-value commodity that is a target for adulteration, leading to loss of quality and causing significant loss to consumers. Therefore, there is significant interest in developing methods for detecting coffee adulteration and improving the sensitivity and accuracy of these methods. Corn and other lower value crops are potential adulterants, along with sticks and coffee husks. Fourteen pure Brazilian roasted, ground coffee bean samples were adulterated with 1-20% of roasted, ground corn and were analyzed for their tocopherol content and profile by HPLC. They were also analyzed by near-infrared (NIR) spectroscopy. Both proposed methods of detection of corn adulteration displayed a sensitivity of around 5%, thus representing simple and fast analytical methods for detecting adulteration at likely levels of contamination. Further studies should be conducted to verify the results with a much larger sample size and additional types of adulterants.
Collapse
Affiliation(s)
- Jill K Winkler-Moser
- Functional Foods Research Unit, National Center for Agricultural Utilization Research, Agricultural Research Service, U.S. Department of Agriculture , 1815 North University Street, Peoria, Illinois 61604, United States
| | - Mukti Singh
- Functional Foods Research Unit, National Center for Agricultural Utilization Research, Agricultural Research Service, U.S. Department of Agriculture , 1815 North University Street, Peoria, Illinois 61604, United States
| | - Kathy A Rennick
- Functional Foods Research Unit, National Center for Agricultural Utilization Research, Agricultural Research Service, U.S. Department of Agriculture , 1815 North University Street, Peoria, Illinois 61604, United States
| | - Erica L Bakota
- Functional Foods Research Unit, National Center for Agricultural Utilization Research, Agricultural Research Service, U.S. Department of Agriculture , 1815 North University Street, Peoria, Illinois 61604, United States
| | - Gulab Jham
- Departamento de Fitopatologia, Universidade Federal de Viçosa , Viçosa, Minas Gerais, Brazil
| | - Sean X Liu
- Functional Foods Research Unit, National Center for Agricultural Utilization Research, Agricultural Research Service, U.S. Department of Agriculture , 1815 North University Street, Peoria, Illinois 61604, United States
| | - Steven F Vaughn
- Functional Foods Research Unit, National Center for Agricultural Utilization Research, Agricultural Research Service, U.S. Department of Agriculture , 1815 North University Street, Peoria, Illinois 61604, United States
| |
Collapse
|
28
|
Optimization of Parameter Selection for Partial Least Squares Model Development. Sci Rep 2015; 5:11647. [PMID: 26166772 PMCID: PMC4499800 DOI: 10.1038/srep11647] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2015] [Accepted: 05/28/2015] [Indexed: 11/08/2022] Open
Abstract
In multivariate calibration using a spectral dataset, it is difficult to optimize nonsystematic parameters in a quantitative model, i.e., spectral pretreatment, latent factors and variable selection. In this study, we describe a novel and systematic approach that uses a processing trajectory to select three parameters including different spectral pretreatments, variable importance in the projection (VIP) for variable selection and latent factors in the Partial Least-Square (PLS) model. The root mean square errors of calibration (RMSEC), the root mean square errors of prediction (RMSEP), the ratio of standard error of prediction to standard deviation (RPD), and the determination coefficient of calibration (Rcal(2)) and validation (Rpre(2)) were simultaneously assessed to optimize the best modeling path. We used three different near-infrared (NIR) datasets, which illustrated that there was more than one modeling path to ensure good modeling. The PLS model optimizes modeling parameters step-by-step, but the robust model described here demonstrates better efficiency than other published papers.
Collapse
|
29
|
Fourier transform infrared spectroscopy and near infrared spectroscopy for the quantification of defects in roasted coffees. Talanta 2015; 134:379-386. [DOI: 10.1016/j.talanta.2014.11.038] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2014] [Revised: 11/17/2014] [Accepted: 11/18/2014] [Indexed: 11/18/2022]
|
30
|
Craig AP, Franca AS, Oliveira LS, Irudayaraj J, Ileleji K. Application of elastic net and infrared spectroscopy in the discrimination between defective and non-defective roasted coffees. Talanta 2014; 128:393-400. [DOI: 10.1016/j.talanta.2014.05.001] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2014] [Revised: 04/30/2014] [Accepted: 05/02/2014] [Indexed: 10/25/2022]
|
31
|
Toledo BR, Hantao LW, Ho TD, Augusto F, Anderson JL. A chemometric approach toward the detection and quantification of coffee adulteration by solid-phase microextraction using polymeric ionic liquid sorbent coatings. J Chromatogr A 2014; 1346:1-7. [DOI: 10.1016/j.chroma.2014.04.035] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2014] [Revised: 04/11/2014] [Accepted: 04/11/2014] [Indexed: 01/30/2023]
|