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Li Y, Wang X, Sa Y, Li L, Wang W, Yang L, Ding S, Wilson G, Yang Y, Zhang Y, Ma X. A comparative UHPLC-QTOF-MS/MS-based metabolomics approach reveals the metabolite profiling of wolfberry sourced from different geographical origins. Food Chem X 2024; 21:101221. [PMID: 38379804 PMCID: PMC10877177 DOI: 10.1016/j.fochx.2024.101221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/13/2024] [Accepted: 02/09/2024] [Indexed: 02/22/2024] Open
Abstract
Wolfberry, known as Goji berry, is the fruit of Lycium barbarum L. (LB). As a famous functional food and TCM, the cost and efficacy of LB are closely linked to its geographical origin. The present study aimed to establish an effective method for distinguishing LB from different geographical origins. By employing UHPLC-QTOF-MS/MS combined with multivariate analysis, the metabolite profiling of LB (199 batches) obtained from Ningxia, Gansu, Qinghai, and Xinjiang, was evaluated. The results demonstrated that the method effectively distinguished LB from the four regions, with a total of 148 different metabolites being detected. Subsequent assessment using heat maps, Venn analysis, receiver operating characteristics curves and dot plots revealed 21 of these metabolites exhibited exceptional sensitivity and specificity, with under-curve values approaching 1, thus indicating their potential as biomarkers for LB. These findings strongly support the suitability of UHPLC-QTOF-MS/MS-based metabolomics as an effective approach to identify the source of LB.
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Affiliation(s)
| | | | | | - Liuyan Li
- Department of Pharmaceutical Analysis, School of Pharmacy, Ningxia Medical University, 1160 Shenli Street, Yinchuan 750004, China
| | - Weibiao Wang
- Department of Pharmaceutical Analysis, School of Pharmacy, Ningxia Medical University, 1160 Shenli Street, Yinchuan 750004, China
| | - Lingling Yang
- Department of Pharmaceutical Analysis, School of Pharmacy, Ningxia Medical University, 1160 Shenli Street, Yinchuan 750004, China
| | - Shuqin Ding
- Department of Pharmaceutical Analysis, School of Pharmacy, Ningxia Medical University, 1160 Shenli Street, Yinchuan 750004, China
| | - Gidion Wilson
- Department of Pharmaceutical Analysis, School of Pharmacy, Ningxia Medical University, 1160 Shenli Street, Yinchuan 750004, China
| | - Youyue Yang
- Department of Pharmaceutical Analysis, School of Pharmacy, Ningxia Medical University, 1160 Shenli Street, Yinchuan 750004, China
| | - Yue Zhang
- Department of Pharmaceutical Analysis, School of Pharmacy, Ningxia Medical University, 1160 Shenli Street, Yinchuan 750004, China
| | - Xueqin Ma
- Department of Pharmaceutical Analysis, School of Pharmacy, Ningxia Medical University, 1160 Shenli Street, Yinchuan 750004, China
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2
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Sim KS, Kim H, Hur SH, Na TW, Lee JH, Kim HJ. Geographical origin discriminatory analysis of onions: Chemometrics methods applied to ICP-OES and ICP-MS analysis. Food Res Int 2024; 175:113676. [PMID: 38129025 DOI: 10.1016/j.foodres.2023.113676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 11/01/2023] [Accepted: 11/03/2023] [Indexed: 12/23/2023]
Abstract
Geographical origin is an important determinant of agricultural product quality and safety. Herein, inductively coupled plasma (ICP) analysis was applied to determine the inorganic elemental content of onions and identify their geographical origin (Korean or Chinese). Chemometric, including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least square discriminant analysis (OPLS-DA) were applied to the ICP results. OPLS-DA distinguished each group, and 17 elements with variable importance in projection (VIP) values of ≥ 1 were selected. The receiver operating characteristic (ROC) curve had an area under the curve (AUC) of 1, indicating excellent discriminatory power. Differences in elemental content between groups were visually observed in a heatmap, and the country of origin was determined with 100% accuracy using canonical discriminant analysis (CDA). This method accurately distinguishes between Korean and Chinese onions and is expected to be beneficial for identifying agricultural products.
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Affiliation(s)
- Kyu Sang Sim
- National Agricultural Products Quality Management Service, Gimcheon 39660, Republic of Korea
| | - Hyoyoung Kim
- National Agricultural Products Quality Management Service, Gimcheon 39660, Republic of Korea
| | - Suel Hye Hur
- National Agricultural Products Quality Management Service, Gimcheon 39660, Republic of Korea
| | - Tae Woong Na
- National Agricultural Products Quality Management Service, Gimcheon 39660, Republic of Korea
| | - Ji Hye Lee
- National Agricultural Products Quality Management Service, Gimcheon 39660, Republic of Korea
| | - Ho Jin Kim
- National Agricultural Products Quality Management Service, Gimcheon 39660, Republic of Korea.
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3
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Velázquez R, Rodríguez A, Hernández A, Casquete R, Benito MJ, Martín A. Spice and Herb Frauds: Types, Incidence, and Detection: The State of the Art. Foods 2023; 12:3373. [PMID: 37761082 PMCID: PMC10528162 DOI: 10.3390/foods12183373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 08/25/2023] [Accepted: 08/27/2023] [Indexed: 09/29/2023] Open
Abstract
There is a necessity to protect the quality and authenticity of herbs and spices because of the increase in the fraud and adulteration incidence during the last 30 years. There are several aspects that make herbs and spices quite vulnerable to fraud and adulteration, including their positive and desirable sensorial and health-related properties, the form in which they are sold, which is mostly powdered, and their economic relevance around the world, even in developing countries. For these reasons, sensitive, rapid, and reliable techniques are needed to verify the authenticity of these agri-food products and implement effective adulteration prevention measures. This review highlights why spices and herbs are highly valued ingredients, their economic importance, and the official quality schemes to protect their quality and authenticity. In addition to this, the type of frauds that can take place with spices and herbs have been disclosed, and the fraud incidence and an overview of scientific articles related to fraud and adulteration based on the Rapid Alert System Feed and Food (RASFF) and the Web of Science databases, respectively, during the last 30 years, is carried out here. Next, the methods used to detect adulterants in spices and herbs are reviewed, with DNA-based techniques and mainly spectroscopy and image analysis methods being the most recommended. Finally, the available adulteration prevention measurements for spices and herbs are presented, and future perspectives are also discussed.
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Affiliation(s)
- Rocío Velázquez
- Departamento de Ingeniería, Medio Agronómico y Forestal, Investigación Aplicada en Hortofruticultura y Jardinería, Escuela de Ingenierías Agrarias, Universidad de Extremadura, Avda. Adolfo Suárez s/n, 06007 Badajoz, Spain;
- Instituto Universitario de Investigación de Recursos Agrarios (INURA), Universidad de Extremadura, Avda. de la Investigación s/n, Campus Universitario, 06006 Badajoz, Spain; (A.H.); (R.C.); (M.J.B.); (A.M.)
| | - Alicia Rodríguez
- Instituto Universitario de Investigación de Recursos Agrarios (INURA), Universidad de Extremadura, Avda. de la Investigación s/n, Campus Universitario, 06006 Badajoz, Spain; (A.H.); (R.C.); (M.J.B.); (A.M.)
- Departamento de Producción Animal y Ciencia de los Alimentos, Nutrición y Bromatología, Escuela de Ingenierías Agrarias, Universidad de Extremadura, Avda. Adolfo Suárez s/n, 06007 Badajoz, Spain
| | - Alejandro Hernández
- Instituto Universitario de Investigación de Recursos Agrarios (INURA), Universidad de Extremadura, Avda. de la Investigación s/n, Campus Universitario, 06006 Badajoz, Spain; (A.H.); (R.C.); (M.J.B.); (A.M.)
- Departamento de Producción Animal y Ciencia de los Alimentos, Nutrición y Bromatología, Escuela de Ingenierías Agrarias, Universidad de Extremadura, Avda. Adolfo Suárez s/n, 06007 Badajoz, Spain
| | - Rocío Casquete
- Instituto Universitario de Investigación de Recursos Agrarios (INURA), Universidad de Extremadura, Avda. de la Investigación s/n, Campus Universitario, 06006 Badajoz, Spain; (A.H.); (R.C.); (M.J.B.); (A.M.)
- Departamento de Producción Animal y Ciencia de los Alimentos, Nutrición y Bromatología, Escuela de Ingenierías Agrarias, Universidad de Extremadura, Avda. Adolfo Suárez s/n, 06007 Badajoz, Spain
| | - María J. Benito
- Instituto Universitario de Investigación de Recursos Agrarios (INURA), Universidad de Extremadura, Avda. de la Investigación s/n, Campus Universitario, 06006 Badajoz, Spain; (A.H.); (R.C.); (M.J.B.); (A.M.)
- Departamento de Producción Animal y Ciencia de los Alimentos, Nutrición y Bromatología, Escuela de Ingenierías Agrarias, Universidad de Extremadura, Avda. Adolfo Suárez s/n, 06007 Badajoz, Spain
| | - Alberto Martín
- Instituto Universitario de Investigación de Recursos Agrarios (INURA), Universidad de Extremadura, Avda. de la Investigación s/n, Campus Universitario, 06006 Badajoz, Spain; (A.H.); (R.C.); (M.J.B.); (A.M.)
- Departamento de Producción Animal y Ciencia de los Alimentos, Nutrición y Bromatología, Escuela de Ingenierías Agrarias, Universidad de Extremadura, Avda. Adolfo Suárez s/n, 06007 Badajoz, Spain
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4
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Dinis K, Tsamba L, Jamin E, Camel V. Untargeted metabolomics-based approach using UHPLC-HRMS to authenticate carrots (Daucus carota L.) based on geographical origin and production mode. Food Chem 2023; 423:136273. [PMID: 37209545 DOI: 10.1016/j.foodchem.2023.136273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 04/08/2023] [Accepted: 04/27/2023] [Indexed: 05/22/2023]
Abstract
Carrots produced in different agricultural regions with organic or conventional mode were analyzed by untargeted UHPLC-HRMS using reversed-phase and HILIC modes. Data were first treated separately, and further combined to possibly improve results. An in-house data processing workflow was applied to identify relevant features after peak detection. Based on these features, discrimination models were built using chemometrics. A tentative annotation of chemical markers was performed using online databases and UHPLC-HRMS/MS analyses. An independent set of samples was analyzed to assess the discrimination potential of these markers. Carrots produced in the New Aquitaine region could be successfully discriminated from carrots originating from the Normandy region by an OLPS-DA model. Arginine and 6-methoxymellein could be identified as potential markers with the C18-silica column. Additional markers (N-acetylputrescine, l-carnitine) could be identified thanks to the polar column. Discrimination based on production mode was more challenging: some trend was observed but model metrics remained unsatisfactory.
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Affiliation(s)
- Katy Dinis
- Eurofins Analytics France, 9 rue Pierre Adolphe Bobierre, B.P. 42301, F-44323 Nantes Cedex 3, France; Université Paris-Saclay, INRAE, AgroParisTech, UMR SayFood, F-91120 Palaiseau, France
| | - Lucie Tsamba
- Eurofins Analytics France, 9 rue Pierre Adolphe Bobierre, B.P. 42301, F-44323 Nantes Cedex 3, France
| | - Eric Jamin
- Eurofins Analytics France, 9 rue Pierre Adolphe Bobierre, B.P. 42301, F-44323 Nantes Cedex 3, France
| | - Valérie Camel
- Université Paris-Saclay, INRAE, AgroParisTech, UMR SayFood, F-91120 Palaiseau, France.
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5
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Hye Hur S, Kim H, Kim YK, An JM, Hye Lee J, Jin Kim H. Discrimination between Korean and Chinese Kimchi using inductively coupled plasma-optical emission spectroscopy and mass spectrometry: A multivariate analysis of Kimchi. Food Chem 2023; 423:136235. [PMID: 37163917 DOI: 10.1016/j.foodchem.2023.136235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 04/18/2023] [Accepted: 04/21/2023] [Indexed: 05/12/2023]
Abstract
Kimchi has been designated as one of the world's five healthiest foods, and it is a traditional Korean fermented food. The purpose of this study was to investigate whether the origin of Kimchi can be discriminated against by using inorganic elements to develop a more accurate method. The OPLS-DA showed that the R2 and Q2 values were 0.908 and 0.81, a high-quality model. We selected 24 elements (133Cs, 238U, 88Sr, K, 157Gd, Na, Mg, 139La, P, 141Pr, 72Ge, 146Nd, 147Sm, 153Eu, 55Mn, 165Ho, 163Dy, 166Er, Fe, 172Yb, 169Tm, 185Re, 175Lu, and 118Sn) with VIP 1 or higher in the OPLS-DA model. In ROC, the selected elements had an accuracy of 100%. The heatmap confirmed the contents of rare earth elements (REEs) in Korean and Chinese Kimchi, the accuracy of distinguishing classification in CDA is 100%. Such results will help to distinguish the origin of agricultural products through inorganic analysis.
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Affiliation(s)
- Suel Hye Hur
- National Agricultural Products Quality Management Service, Gimcheon, 39660, Republic of Korea
| | - Hyoyoung Kim
- National Agricultural Products Quality Management Service, Gimcheon, 39660, Republic of Korea
| | - Yong-Kyoung Kim
- National Agricultural Products Quality Management Service, Gimcheon, 39660, Republic of Korea
| | - Jae-Min An
- National Agricultural Products Quality Management Service, Gimcheon, 39660, Republic of Korea
| | - Ji Hye Lee
- National Agricultural Products Quality Management Service, Gimcheon, 39660, Republic of Korea
| | - Ho Jin Kim
- National Agricultural Products Quality Management Service, Gimcheon, 39660, Republic of Korea.
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6
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Yu DX, Guo S, Zhang X, Yan H, Zhang ZY, Chen X, Chen JY, Jin SJ, Yang J, Duan JA. Rapid detection of adulteration in powder of ginger (Zingiber officinale Roscoe) by FT-NIR spectroscopy combined with chemometrics. Food Chem X 2022; 15:100450. [PMID: 36211746 PMCID: PMC9532869 DOI: 10.1016/j.fochx.2022.100450] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 09/04/2022] [Accepted: 09/16/2022] [Indexed: 11/25/2022] Open
Abstract
Rapid detection of adulteration in GP was realized by NIR spectroscopy. PCA and PLS-DA models were successfully explored to identify adulterants in GP. Three algorithms achieved satisfactory results for discrimination of adulteration. Adulteration levels in GP can be predicted by PLSR model. The optimal pretreatment methods were compared and selected for modeling.
Ginger powder (GP) is a popular spice in the world. Duo to its nutritional value, GP is regarded as an attractive target for adulteration, which is not easily detected. In this study, chromaticity analysis and Fourier transform near-infrared (FT-NIR) spectroscopy combined with chemometrics were developed to identify and quantify of GP and its adulterants. The result showed that GPs and adulterated GPs cannot be completely distinguished by chromaticity analysis. While, the optimized NIR spectra could accurately distinguish the authentic GPs from those adulterated samples. Random forest and gradient boosting algorithms exhibited the highest accuracies (100%) in classification. Moreover, a quantitative model was successfully established to predict the adulteration level in GP. The optimal parameters of prediction to deviation were 8.92, 13.68, 14.61, and 4.30, for pure and adulterated GPs. Overall, FT-NIR spectroscopy is a promising tool, which can quickly identify potential adulteration in GP and track the types of adulterants.
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7
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Authentication of typical Italian bell pepper spices by ICP-OES multi-elemental analysis combined with SIMCA class modelling. J Food Compost Anal 2022. [DOI: 10.1016/j.jfca.2022.104948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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8
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Combined hyperspectral imaging technology with 2D convolutional neural network for near geographical origins identification of wolfberry. JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION 2022. [DOI: 10.1007/s11694-022-01552-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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9
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Sun X, Zhang M, Wang P, Chen J, Yang S, Luo P, Gao X. Detection and Quantitation of Adulterated Paprika Samples Using Second-Order HPLC-FLD Fingerprints and Chemometrics. Foods 2022; 11:foods11152376. [PMID: 35954142 PMCID: PMC9368040 DOI: 10.3390/foods11152376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 07/22/2022] [Accepted: 08/05/2022] [Indexed: 11/16/2022] Open
Abstract
Paprika is a widely consumed spice in the world and its authentication has gained interest considering the increase in adulteration cases in recent years. In this study, second-order fingerprints acquired by liquid chromatography with fluorescence detection (HPLC-FLD) were first used to detect and quantify adulteration levels of Chinese paprika samples. Six different adulteration cases, involving paprika production region, cultivar, or both, were investigated by pairs. Two strategies were employed to reduce the data matrices: (1) chromatographic fingerprints collected at specific wavelengths and (2) fusion of the mean data profiles in both spectral and time dimensions. Afterward, the fingerprint data with different data orders were analyzed using partial least squares (PLS) and n-way partial least squares (N-PLS) regression models, respectively. For most adulteration cases, N-PLS based on second-order fingerprints provided the overall best quantitation results with cross-validation and prediction errors lower than 2.27% and 20.28%, respectively, for external validation sets with 15-85% adulteration levels. To conclude, second-order HPLC-FLD fingerprints coupled with chemometrics can be a promising screening technique to assess paprika quality and authenticity in the control and prevention of food frauds.
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Affiliation(s)
- Xiaodong Sun
- State Key Laboratory of Functions and Applications of Medicinal Plants, School of Pharmacy, Guizhou Medical University, Guiyang 550025, China
- Microbiology and Biochemical Pharmaceutical Engineering Research Center of Guizhou Provincial Department of Education, Guizhou Medical University, Guiyang 550004, China
| | - Min Zhang
- State Key Laboratory of Functions and Applications of Medicinal Plants, School of Pharmacy, Guizhou Medical University, Guiyang 550025, China
- Microbiology and Biochemical Pharmaceutical Engineering Research Center of Guizhou Provincial Department of Education, Guizhou Medical University, Guiyang 550004, China
| | - Pengjiao Wang
- State Key Laboratory of Functions and Applications of Medicinal Plants, School of Pharmacy, Guizhou Medical University, Guiyang 550025, China
- Microbiology and Biochemical Pharmaceutical Engineering Research Center of Guizhou Provincial Department of Education, Guizhou Medical University, Guiyang 550004, China
| | - Junhua Chen
- State Key Laboratory of Functions and Applications of Medicinal Plants, School of Pharmacy, Guizhou Medical University, Guiyang 550025, China
- Microbiology and Biochemical Pharmaceutical Engineering Research Center of Guizhou Provincial Department of Education, Guizhou Medical University, Guiyang 550004, China
| | - Shengjun Yang
- State Key Laboratory of Functions and Applications of Medicinal Plants, School of Pharmacy, Guizhou Medical University, Guiyang 550025, China
- Microbiology and Biochemical Pharmaceutical Engineering Research Center of Guizhou Provincial Department of Education, Guizhou Medical University, Guiyang 550004, China
| | - Peng Luo
- Guizhou Provincial Engineering Research Center of Food Nutrition and Health, School of Public Health, Guizhou Medical University, Guiyang 550025, China
| | - Xiuli Gao
- State Key Laboratory of Functions and Applications of Medicinal Plants, School of Pharmacy, Guizhou Medical University, Guiyang 550025, China
- Microbiology and Biochemical Pharmaceutical Engineering Research Center of Guizhou Provincial Department of Education, Guizhou Medical University, Guiyang 550004, China
- Guizhou Provincial Engineering Research Center of Food Nutrition and Health, School of Public Health, Guizhou Medical University, Guiyang 550025, China
- Correspondence:
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10
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Mialon N, Roig B, Capodanno E, Cadiere A. Untargeted metabolomic approaches in food authenticity: a review that showcases biomarkers. Food Chem 2022; 398:133856. [DOI: 10.1016/j.foodchem.2022.133856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 08/01/2022] [Accepted: 08/02/2022] [Indexed: 11/26/2022]
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11
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Monago-Maraña O, Durán-Merás I, Muñoz de la Peña A, Galeano-Díaz T. Analytical techniques and chemometrics approaches in authenticating and identifying adulteration of paprika powder using fingerprints: A review. Microchem J 2022. [DOI: 10.1016/j.microc.2022.107382] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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12
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Kolašinac S, Pećinar I, Danojević D, Stevanović ZD. Raman spectroscopy coupled with chemometric modeling approaches for authentication of different paprika varieties at physiological maturity. Lebensm Wiss Technol 2022. [DOI: 10.1016/j.lwt.2022.113402] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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13
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Campmajó G, Saurina J, Núñez O, Sentellas S. Differential mobility spectrometry coupled to mass spectrometry (DMS-MS) for the classification of Spanish PDO paprika. Food Chem 2022; 390:133141. [PMID: 35567973 DOI: 10.1016/j.foodchem.2022.133141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 04/04/2022] [Accepted: 05/01/2022] [Indexed: 11/04/2022]
Abstract
Ion mobility spectrometry (IMS) has proved its huge potential in many research areas, especially when hyphenated with chromatographic techniques or mass spectrometry (MS). However, focusing on food analysis, and particularly in classification and authentication issues, very few applications have been reported. In this study, differential mobility spectrometry coupled to mass spectrometry (DMS-MS) is presented for the first time as an alternative and high-throughput technique for food classification and authentication purposes using a fingerprinting strategy. As a study case, 70 Spanish paprika samples (from La Vera, Murcia, and Mallorca) were analyzed by DMS-MS to address their classification -using partial least squares regression-discriminant analysis (PLS-DA)- and authentication -through soft independent modeling of class analogy (SIMCA). As a result, after external validation, complete sample classification according to their geographical origin and excellent La Vera and Mallorca sample authentication were reached.
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Affiliation(s)
- Guillem Campmajó
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès 1-11, E08028 Barcelona, Spain; Research Institute in Food Nutrition and Food Safety, University of Barcelona, Av. Prat de la Riba 171, Edifici Recerca (Gaudí), E08921 Santa Coloma de Gramenet, Spain
| | - Javier Saurina
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès 1-11, E08028 Barcelona, Spain; Research Institute in Food Nutrition and Food Safety, University of Barcelona, Av. Prat de la Riba 171, Edifici Recerca (Gaudí), E08921 Santa Coloma de Gramenet, Spain
| | - Oscar Núñez
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès 1-11, E08028 Barcelona, Spain; Research Institute in Food Nutrition and Food Safety, University of Barcelona, Av. Prat de la Riba 171, Edifici Recerca (Gaudí), E08921 Santa Coloma de Gramenet, Spain
| | - Sonia Sentellas
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès 1-11, E08028 Barcelona, Spain; Research Institute in Food Nutrition and Food Safety, University of Barcelona, Av. Prat de la Riba 171, Edifici Recerca (Gaudí), E08921 Santa Coloma de Gramenet, Spain; Serra Húnter Fellow, Generalitat de Catalunya, Rambla de Catalunya 19-21, E08007 Barcelona, Spain.
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14
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Traceability of the geographical origin of Siraitia grosvenorii based on multielement contents coupled with chemometric techniques. Sci Rep 2021; 11:21150. [PMID: 34707170 PMCID: PMC8551321 DOI: 10.1038/s41598-021-00664-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 10/15/2021] [Indexed: 11/28/2022] Open
Abstract
Siraitia grosvenorii (LHG) is widely used as a medicinal and edible material around the world. The objective of this study was to develop an effective method for the authentication of the geographical origin of LHG in its main producing area Guangxi, China, which is identified as Chinese Protected Designation of Origin product, against other producing regions in China. The content of 14 elements (K, Na, Ca, P, Mg, Al, B, Ba, Cu, Fe, Mn, Ni, Zn, and Sr) of 114 LHG samples was determined by inductively coupled plasma optical emission spectrometry. Multivariate analysis was then performed to classify the geographical origin of LHG samples. The contents of multielement display an obvious trend of clustering according to the geographical origin of LHG samples based on radar plot and principal component analysis. Finally, three supervised statistical techniques, including linear discriminant analysis (LDA), k-nearest neighbours (k-NN), and support vector machine (SVM), were applied to develop classification models. Finally, 40 unknown LHG samples were used to evaluate the predictive ability of model and discrimination rate of 100%, 97.5% and 100% were obtained for LDA, k-NN, and SVM, respectively. This study indicated that it is feasible to attribute unknown LHG samples to its geographical origin based on its multielement content coupled with chemometric techniques.
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15
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Reale S, Biancolillo A, Gasparrini C, Di Martino L, Di Cecco V, Manzi A, Di Santo M, D’Archivio AA. Geographical Discrimination of Bell Pepper ( Capsicum annuum) Spices by (HS)-SPME/GC-MS Aroma Profiling and Chemometrics. Molecules 2021; 26:6177. [PMID: 34684758 PMCID: PMC8538362 DOI: 10.3390/molecules26206177] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 10/08/2021] [Accepted: 10/12/2021] [Indexed: 12/03/2022] Open
Abstract
Dried and ground red pepper is a spice used as seasoning in various traditional dishes all over the world; nevertheless, the pedoclimatic conditions of the diverse cultivation areas provide different chemical characteristics, and, consequently, diverse organoleptic properties to this product. In the present study, the volatile profiles of 96 samples of two different ground bell peppers harvested in diverse Italian geographical areas, Altino (Abruzzo) and Senise (Lucania), and a commercial sweet paprika, have been studied by means of headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). The investigation of their volatile profile has led to the identification of 59 analytes. Eventually, a discriminant classifier, Partial Least Squares Discriminant Analysis (PLS-DA), was exploited to discriminate samples according to their geographical origin. The model provided very accurate results in external validation; in fact, it correctly classified all the 30 test samples, achieving 100% correct classification (on the validation set). Furthermore, in order to understand which volatiles contribute the most at differentiating the bell peppers from the different origins, a variable selection approach, Variable Importance in Projection (VIP), was used. This strategy led to the selection of sixteen diverse compounds which characterize the different bell pepper spices.
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Affiliation(s)
- Samantha Reale
- Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell’Aquila, Via Vetoio, 67100 L’Aquila, Italy; (S.R.); (A.B.); (C.G.)
| | - Alessandra Biancolillo
- Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell’Aquila, Via Vetoio, 67100 L’Aquila, Italy; (S.R.); (A.B.); (C.G.)
| | - Chiara Gasparrini
- Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell’Aquila, Via Vetoio, 67100 L’Aquila, Italy; (S.R.); (A.B.); (C.G.)
| | - Luciano Di Martino
- Majella Seed Bank-Parco Nazionale della Majella, Via Badia 28, 67039 Sulmona, Italy; (L.D.M.); (V.D.C.); (M.D.S.)
| | - Valter Di Cecco
- Majella Seed Bank-Parco Nazionale della Majella, Via Badia 28, 67039 Sulmona, Italy; (L.D.M.); (V.D.C.); (M.D.S.)
| | | | - Marco Di Santo
- Majella Seed Bank-Parco Nazionale della Majella, Via Badia 28, 67039 Sulmona, Italy; (L.D.M.); (V.D.C.); (M.D.S.)
| | - Angelo Antonio D’Archivio
- Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell’Aquila, Via Vetoio, 67100 L’Aquila, Italy; (S.R.); (A.B.); (C.G.)
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Ponder A, Kulik K, Hallmann E. Occurrence and Determination of Carotenoids and Polyphenols in Different Paprika Powders from Organic and Conventional Production. Molecules 2021; 26:2980. [PMID: 34067891 PMCID: PMC8156602 DOI: 10.3390/molecules26102980] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 04/30/2021] [Accepted: 05/11/2021] [Indexed: 11/16/2022] Open
Abstract
Paprika powder is a good source of different carotenoids and polyphenols, which play a key role in preventing certain diseases (some kinds of cancer and cardiovascular diseases). They can also be used as natural food colorants. Organic production is characterized by strict rules, but products obtained in this way contain more bioactive compounds, such as carotenoids and polyphenols. The aim of this study was to measure and identify carotenoids and polyphenols in different paprika samples (sweet, hot, smoked, and chili) obtained by organic and conventional production. Quantitative and qualitative carotenoid and polyphenols analysis showed that the experimental samples contained different concentrations of these compounds.
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Affiliation(s)
- Alicja Ponder
- Department of Functional and Organic Food, Institute of Human Nutrition Sciences, Warsaw University of Life Sciences, Nowoursynowska 159c, 02-776, Warsaw, Poland; (K.K.); (E.H.)
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