1
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Wei H, Yang D, Mao J, Zhang Q, Cheng L, Yang X, Li P. Accurate quantification of TAGs to identify adulteration of edible oils by ultra-high performance liquid chromatography-quadrupole-time of flight-tandem mass spectrometry. Food Res Int 2023; 165:112544. [PMID: 36869531 DOI: 10.1016/j.foodres.2023.112544] [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: 08/31/2022] [Revised: 12/13/2022] [Accepted: 01/29/2023] [Indexed: 02/05/2023]
Abstract
Edible oils play important roles in biological functions, and triacylglycerols (TAGs) in edible oils are complex mixtures. This makes accurate TAGs quantitation quite difficult that bring economically motivated food adulteration. Herein, we demonstrated a strategy for accurate quantification of TAGs in edible oils, which could be applied in identification of olive oil adulteration. The results showed that the proposed strategy could significantly improve the accuracy of TAG content determination, reduce the relative error of fatty acids (FAs) content determination, and present a wider accurate quantitative range than that of gas chromatography-flame ionization detection. Most important, this strategy coupled with principal component analysis could be used to identify adulteration of high-priced olive oil with cheaper soybean oils, rapeseed oils or camellia oils at a lower concentration of 2%. These findings indicated that the proposed strategy could be regarded as a potential method for edible oils quality and authenticity analysis.
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Affiliation(s)
- Hailian Wei
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Dandan Yang
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Jin Mao
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China; National Reference Laboratory for Agricultural Testing P.R. China, Key Laboratory of Detection for Mycotoxins, Laboratory of Quality & Safety Risk Assessment for Oilseed Products (Wuhan), Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Hubei Hongshan Laboratory, Wuhan, China.
| | - Qi Zhang
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China; National Reference Laboratory for Agricultural Testing P.R. China, Key Laboratory of Detection for Mycotoxins, Laboratory of Quality & Safety Risk Assessment for Oilseed Products (Wuhan), Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Hubei Hongshan Laboratory, Wuhan, China
| | - Ling Cheng
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China; National Reference Laboratory for Agricultural Testing P.R. China, Key Laboratory of Detection for Mycotoxins, Laboratory of Quality & Safety Risk Assessment for Oilseed Products (Wuhan), Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Hubei Hongshan Laboratory, Wuhan, China
| | - Xianglong Yang
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China; National Reference Laboratory for Agricultural Testing P.R. China, Key Laboratory of Detection for Mycotoxins, Laboratory of Quality & Safety Risk Assessment for Oilseed Products (Wuhan), Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Hubei Hongshan Laboratory, Wuhan, China
| | - Peiwu Li
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China; National Reference Laboratory for Agricultural Testing P.R. China, Key Laboratory of Detection for Mycotoxins, Laboratory of Quality & Safety Risk Assessment for Oilseed Products (Wuhan), Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Hubei Hongshan Laboratory, Wuhan, China
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2
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Srata L, Farres S, Chikri M, Addou S, Fethi F. Detection of the Adulteration of Motor Oil by Laser Induced Fluorescence Spectroscopy and Chemometric Techniques. J Fluoresc 2023; 33:713-720. [PMID: 36504275 DOI: 10.1007/s10895-022-03108-9] [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: 04/22/2022] [Accepted: 11/28/2022] [Indexed: 12/14/2022]
Abstract
Petroleum products are the target of fraudulent practices due to their high commercial value. The aim of this study is to provide a new analysis system to assess motor oil adulteration. For this purpose, Laser Induced Fluorescence (LIF) spectroscopy was exploited coupled with chemometric tools to detect motor oil adulteration by three types of cheap motor oils. Principal Component Analysis (PCA) was able to distinguish samples in three groups according to the type of adulterant. Besides, Partial Least Squares Regression (PLSR) was exploited to determine the percentage of adulteration. The best model was obtained with a regression coefficient of 0.96, Root Mean Square Error of Prediction (RMSEP) of 2.83, Standard Error of Prediction (SEP) of 2.83 and Bias of 0.40. The main results of this work provide new analysis system using the combination of LIF spectroscopy combined to PCA and PLS as an efficient and fast method for motor oil analysis.
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Affiliation(s)
- Loubna Srata
- Laboratory of Physics of Matter and Radiations (LPMR), Physics Department, Mohammed First University, Oujda, Morocco
| | - Sofia Farres
- Laboratory of Physics of Matter and Radiations (LPMR), Physics Department, Mohammed First University, Oujda, Morocco
| | - Mounim Chikri
- Laboratory of Physics of Matter and Radiations (LPMR), Physics Department, Mohammed First University, Oujda, Morocco
| | - Sihame Addou
- Laboratory of Physics of Matter and Radiations (LPMR), Physics Department, Mohammed First University, Oujda, Morocco
| | - Fouad Fethi
- Laboratory of Physics of Matter and Radiations (LPMR), Physics Department, Mohammed First University, Oujda, Morocco.
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3
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Zhang G, Li H, Sun L, Liu Y, Cao Y, Ren X, Liu Y. Study on the Correlation Between the Appearance Traits and Intrinsic Chemical Quality of Bitter Almonds Based on Fingerprint-Chemometrics. J Chromatogr Sci 2023; 61:110-118. [PMID: 35396599 DOI: 10.1093/chromsci/bmac026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Indexed: 11/14/2022]
Abstract
Bitter almond is a well-known and commonly used traditional Chinese medicine (TCM) for relieving coughs and asthma. However, the bioactive chemical composition of bitter almonds, especially their amygdalin content, which determines their quality for TCM use, is variable and this can cause problems with formulating and prescribing TCMs based on bitter almonds. Therefore, a simple method was developed to evaluate the compositional quality of bitter almonds from their appearance traits, based on a combination of chromatographic fingerprinting and chemometrics. Bitter almonds were analyzed by high-performance liquid chromatography (HPLC). Hierarchical cluster analysis (HCA) and principal components analysis (PCA) were applied to classify bitter almonds, which split the samples into two independent clusters. Three chemical markers (amygdalin, prunasin, and one unidentified component) were found by partial least squares-discriminant analysis (PLS-DA). What's more, a new PLS-DA model was reconstructed to confirm the obtained chemical markers from PLS-DA. Additionally, the appearance trait indices and amygdalin content of bitter almond were determined and the classification was confirmed by one-way analysis of variance. This method can easily determine the quality of bitter almonds from their appearance alone, high quality correlated closely with kernels that were larger, oblong in shape and heavier.
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Affiliation(s)
- Guoqin Zhang
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, No. 10, Poyang Lake Road, Tuanbo New City West District, Jinghai District, Tianjin 301617, China
| | - Huanhuan Li
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, No. 10, Poyang Lake Road, Tuanbo New City West District, Jinghai District, Tianjin 301617, China
| | - Lili Sun
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, No. 10, Poyang Lake Road, Tuanbo New City West District, Jinghai District, Tianjin 301617, China
| | - Yi Liu
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, No. 10, Poyang Lake Road, Tuanbo New City West District, Jinghai District, Tianjin 301617, China
| | - Ying Cao
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, No. 10, Poyang Lake Road, Tuanbo New City West District, Jinghai District, Tianjin 301617, China
| | - Xiaoliang Ren
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, No. 10, Poyang Lake Road, Tuanbo New City West District, Jinghai District, Tianjin 301617, China
| | - Yanan Liu
- School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, No. 10, Poyang Lake Road, Tuanbo New City West District, Jinghai District, Tianjin 301617, China
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4
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Rovira G, Miaw CSW, Martins MLC, Sena MM, de Souza SVC, Callao MP, Ruisánchez I. One-class model with two decision thresholds for the rapid detection of cashew nuts adulteration by other nuts. Talanta 2023; 253:123916. [PMID: 36126522 DOI: 10.1016/j.talanta.2022.123916] [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: 06/28/2022] [Revised: 09/01/2022] [Accepted: 09/03/2022] [Indexed: 12/15/2022]
Abstract
A green screening method to determine cashew nut adulteration with Brazilian nut, pecan nut, macadamia nut and peanut was proposed. The method was based on the development of a one-class soft independent modelling of class analogy (SIMCA) model for non-adulterated cashew nuts using near-infrared (NIR) spectra obtained with portable equipment. Once the model is established, the assignment of unknown samples depends on the threshold established for the authentic class, which is a key aspect in any screening approach. The authors propose innovatively to define two thresholds: lower model distance limit and upper model distance limit. Samples with distances below the lower threshold are assigned as non-adulterated with a 100% probability; samples with distance values greater than the upper threshold are assigned as adulterated with a 100% probability; and samples with distances within these two thresholds will be considered uncertain and should be submitted to a confirmatory analysis. Thus, the possibility of error in the sample assignment significantly decreases. In the present study, when just one threshold was defined, values greater than 95% for the optimized threshold were obtained for both selectivity and specificity. When two class thresholds were defined, the percentage of samples with uncertain assignment changes according to the adulterant considered, highlighting the case of peanuts, in which 0% of uncertain samples was obtained. Considering all adulterants, the number of samples that were submitted to a confirmatory analysis was quite low, 5 of 224 adulterated samples and 3 of 56 non-adulterated samples.
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Affiliation(s)
- Glòria Rovira
- Chemometrics, Qualimetric and Nanosensors Group, Department of Analytical and Organic Chemistry, Rovira I Virgili University, Marcel·lí Domingo s/n, 43007 Tarragona, Spain
| | - Carolina Sheng Whei Miaw
- Department of Food Science, Faculty of Pharmacy (FAFAR), Federal University of Minas Gerais (UFMG), Av. Antônio Carlos, 6627, Campus da UFMG, Pampulha, 31270-010, Belo Horizonte, MG, Brazil
| | - Mário Lúcio Campos Martins
- Department of Food Science, Faculty of Pharmacy (FAFAR), Federal University of Minas Gerais (UFMG), Av. Antônio Carlos, 6627, Campus da UFMG, Pampulha, 31270-010, Belo Horizonte, MG, Brazil
| | - Marcelo Martins Sena
- Chemistry Department, Institute of Exact Sciences (ICEX), Federal University of Minas Gerais (UFMG), Av. Antônio Carlos, 6627, Campus da UFMG, Pampulha, 31270-010, Belo Horizonte, MG, Brazil; Instituto Nacional de Ciência e Tecnologia em Bioanalítica (INCT-Bio), Campinas, SP, 13083-970, Brazil
| | - Scheilla Vitorino Carvalho de Souza
- Department of Food Science, Faculty of Pharmacy (FAFAR), Federal University of Minas Gerais (UFMG), Av. Antônio Carlos, 6627, Campus da UFMG, Pampulha, 31270-010, Belo Horizonte, MG, Brazil
| | - M Pilar Callao
- Chemometrics, Qualimetric and Nanosensors Group, Department of Analytical and Organic Chemistry, Rovira I Virgili University, Marcel·lí Domingo s/n, 43007 Tarragona, Spain.
| | - Itziar Ruisánchez
- Chemometrics, Qualimetric and Nanosensors Group, Department of Analytical and Organic Chemistry, Rovira I Virgili University, Marcel·lí Domingo s/n, 43007 Tarragona, Spain
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5
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Yao G, Wu M, Ge M, Zhang M, Cao X, Zhu Y, Wei S, Chang Y, Ouyang H, He J. A multi-evaluating strategy for raw and processed Veratrum nigrum L.: fingerprinting combined with quantitative analysis based on multivariate chemometric methods. ARAB J CHEM 2023. [DOI: 10.1016/j.arabjc.2023.104639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
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6
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Kang MJ, Suh JH. Metabolomics as a tool to evaluate nut quality and safety. Trends Food Sci Technol 2022. [DOI: 10.1016/j.tifs.2022.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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7
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Avila-Sosa R, Nevárez-Moorillón GV, Ochoa-Velasco CE, Navarro-Cruz AR, Hernández-Carranza P, Cid-Pérez TS. Detection of Saffron’s Main Bioactive Compounds and Their Relationship with Commercial Quality. Foods 2022. [PMCID: PMC9601577 DOI: 10.3390/foods11203245] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
This review aims to evaluate the state of saffron’s main bioactive compounds and their relationship with its commercial quality. Saffron is the commercial name for the dried red stigmas of the Crocus sativus L. flower. It owes its sensory and functional properties mainly to the presence of its carotenoid derivatives, synthesized throughout flowering and also during the whole production process. These compounds include crocin, crocetin, picrocrocin, and safranal, which are bioactive metabolites. Saffron’s commercial value is determined according to the ISO/TS3632 standard that determines their main apocatotenoids. Other techniques such as chromatography (gas and liquid) are used to detect the apocarotenoids. This, together with the determination of spectral fingerprinting or chemo typing are essential for saffron identification. The determination of the specific chemical markers coupled with chemometric methods favors the discrimination of adulterated samples, possible plants, or adulterating compounds and even the concentrations at which these are obtained. Chemical characterization and concentration of various compounds could be affected by saffron’s geographical origin and harvest/postharvest characteristics. The large number of chemical compounds found in the by-products (flower parts) of saffron (catechin, quercetin, delphinidin, etc.) make it an interesting aromatic spice as a colorant, antioxidant, and source of phytochemicals, which can also bring additional economic value to the most expensive aromatic species in the world.
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Affiliation(s)
- Raul Avila-Sosa
- Facultad de Ciencias Químicas, Benemérita Universidad Autónoma de Puebla, Edificio 105E, 14 Sur y Av. San Claudio, Ciudad Universitaria, Col. San Manuel, Puebla 72420, Mexico
| | | | - Carlos Enrique Ochoa-Velasco
- Facultad de Ciencias Químicas, Benemérita Universidad Autónoma de Puebla, Edificio 105E, 14 Sur y Av. San Claudio, Ciudad Universitaria, Col. San Manuel, Puebla 72420, Mexico
| | - Addí Rhode Navarro-Cruz
- Facultad de Ciencias Químicas, Benemérita Universidad Autónoma de Puebla, Edificio 105E, 14 Sur y Av. San Claudio, Ciudad Universitaria, Col. San Manuel, Puebla 72420, Mexico
| | - Paola Hernández-Carranza
- Facultad de Ciencias Químicas, Benemérita Universidad Autónoma de Puebla, Edificio 105E, 14 Sur y Av. San Claudio, Ciudad Universitaria, Col. San Manuel, Puebla 72420, Mexico
| | - Teresa Soledad Cid-Pérez
- Facultad de Ciencias Químicas, Benemérita Universidad Autónoma de Puebla, Edificio 105E, 14 Sur y Av. San Claudio, Ciudad Universitaria, Col. San Manuel, Puebla 72420, Mexico
- Correspondence:
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8
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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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9
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In-depth chemometric strategy to detect up to four adulterants in cashew nuts by IR spectroscopic techniques. Microchem J 2022. [DOI: 10.1016/j.microc.2022.107816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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10
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Zhang F, Gao C, Bai L, Chen Y, Liang S, Lv X, Sun J, Wang S. Dual-color blending based visual LAMP for food allergen detection: A strategy with enlarged color variation range and contrast. Food Chem X 2022; 13:100201. [PMID: 35498982 PMCID: PMC9039889 DOI: 10.1016/j.fochx.2021.100201] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 12/27/2021] [Accepted: 12/30/2021] [Indexed: 02/07/2023] Open
Abstract
A near contrast color change was obtained by blending HNB and CR colorimetric LAMP detection process. The sensitivity of the dual-color blending method was comparable to the real-time LAMP. The ratio between the two visual dyes in the dual-color blending method is crucial. The reaction is conducted in one tube and no lid-opening was needed.
Food allergy has been a serious public health problem around the world. Its prevention relies heavily on the effective avoidance of any contaminated food, making clear and accurate detection very important. LAMP is one of the most potent methods for allergen rapid detection. However, its current colorimetric readouts usually have low color contrast and narrow color variation range. Thus, here we proposed a strategy based on color evolution to enlarge the variation range as well as the contrast to improve its suitability for naked-eye observation. By simply blending two commonly used color change processes during amplification, a wider color variation window, and a near contrast color change, purple-to-green with a hues difference of 10 were obtained. Three important allergens (walnuts, hazelnuts, and peanuts) were tested with a comparable sensitivity towards fluorescent real-time LAMP. Its feasibility for practical use has also been studied. This simple but effective strategy provides a new idea for the colorimetric detection of LAMP amplicons and can be applied to various fields.
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Affiliation(s)
- Fang Zhang
- College of Biological Science and Engineering, Fuzhou University, Fuzhou 350108, China
| | - Chenshan Gao
- College of Biological Science and Engineering, Fuzhou University, Fuzhou 350108, China.,Beijing Laboratory of Food Quality and Safety, Beijing Technology and Business University, Beijing 100048, China
| | - Linlin Bai
- College of Biological Science and Engineering, Fuzhou University, Fuzhou 350108, China
| | - Yiquan Chen
- Clinical Laboratory, Nanan Hospital, Nanan 362300, China
| | - Shuying Liang
- College of Biological Science and Engineering, Fuzhou University, Fuzhou 350108, China
| | - Xucong Lv
- College of Biological Science and Engineering, Fuzhou University, Fuzhou 350108, China
| | - Jinyuan Sun
- Beijing Laboratory of Food Quality and Safety, Beijing Technology and Business University, Beijing 100048, China
| | - Shaoyun Wang
- College of Biological Science and Engineering, Fuzhou University, Fuzhou 350108, China
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11
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Bai Z, Tian J, Hu X, Sun T, Luo H, Huang D. A
back‐propagation neural network
model using hyperspectral imaging applied to variety nondestructive detection of cereal. J FOOD PROCESS ENG 2022. [DOI: 10.1111/jfpe.13973] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Zhizhen Bai
- School of Mechanical Engineering Sichuan University of Science and Engineering Zigong China
| | - Jianping Tian
- School of Mechanical Engineering Sichuan University of Science and Engineering Zigong China
| | - Xinjun Hu
- School of Mechanical Engineering Sichuan University of Science and Engineering Zigong China
| | - Ting Sun
- School of Mechanical Engineering Sichuan University of Science and Engineering Zigong China
| | - Huibo Luo
- College of Bioengineering Sichuan University of Science and Engineering Zigong China
| | - Dan Huang
- College of Bioengineering Sichuan University of Science and Engineering Zigong China
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12
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Screening Method for the Detection of Other Allergenic Nuts in Cashew Nuts Using Chemometrics and a Portable Near-Infrared Spectrophotometer. FOOD ANAL METHOD 2022. [DOI: 10.1007/s12161-021-02184-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
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13
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14
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Wang L, Ren X, Wang Y, Liu X, Dong Y, Ma J, Song R, Yu AX, Wei J, Fan Q, Wang X, She G. HPLC fingerprint and UV–Vis spectroscopy coupled with chemometrics for Curcumae radix species discrimination and three bioactive compounds prediction. Microchem J 2021. [DOI: 10.1016/j.microc.2021.106254] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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15
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Non-targeted HPLC-FLD fingerprinting for the detection and quantitation of adulterated coffee samples by chemometrics. Food Control 2021. [DOI: 10.1016/j.foodcont.2021.107912] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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16
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Yao CL, Wang J, Li ZW, Qu H, Pan HQ, Li JY, Wei WL, Zhang JQ, Bi QR, Guo DA. Characteristic Malonyl Ginsenosides from the Leaves of Panax notoginseng as Potential Quality Markers for Adulteration Detection. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2021; 69:4849-4857. [PMID: 33849274 DOI: 10.1021/acs.jafc.1c00382] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Due to the high price and limited supply of Panax notoginseng, a large number of samples adulterated with the leaves appear in the market. A group of new malonyl ginsenosides were exclusively detected in the P. notoginseng leaves (PNL). Targeted isolation of the malonyl ginsenosides was guided by UPLC-QDa MS. HRMS, 1D/2D NMR, and chemical methods were used for structural identification. A selected ion monitoring method was developed based on UPLC-QDa MS to detect the adulterations. In addition, the anti-inflammatory activities and the collision-induced dissociation features of the isolated saponins were studied. As a result, eight new 3-OH malonylated dammarane-type triterpene oligoglycosides (notoginsenosides L3-L10) were obtained from PNL. Adulteration with PNL can be easily detected with limit of detection as low as 0.06%. To sum up, the isolated ginsenosides can be used as quality markers for fraud detection, which will promote the quality control of the notoginseng products.
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Affiliation(s)
- Chang-Liang Yao
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 501 Haike Road, Shanghai 201203, China
| | - Jing Wang
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 501 Haike Road, Shanghai 201203, China
| | - Zhen-Wei Li
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 501 Haike Road, Shanghai 201203, China
| | - Hua Qu
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 501 Haike Road, Shanghai 201203, China
| | - Hui-Qin Pan
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 501 Haike Road, Shanghai 201203, China
| | - Jia-Yuan Li
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 501 Haike Road, Shanghai 201203, China
| | - Wen-Long Wei
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 501 Haike Road, Shanghai 201203, China
| | - Jian-Qing Zhang
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 501 Haike Road, Shanghai 201203, China
| | - Qi-Rui Bi
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 501 Haike Road, Shanghai 201203, China
| | - De-An Guo
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 501 Haike Road, Shanghai 201203, China
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17
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Zhang Y, Wu M, Xi J, Pan C, Xu Z, Xia W, Zhang W. Multiple-fingerprint analysis of Poria cocos polysaccharide by HPLC combined with chemometrics methods. J Pharm Biomed Anal 2021; 198:114012. [PMID: 33713882 DOI: 10.1016/j.jpba.2021.114012] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 03/01/2021] [Accepted: 03/04/2021] [Indexed: 01/02/2023]
Abstract
In this study, the multiple fingerprints, which were integrated with HPGFC-ELSD (high performance gel filtration chromatography - evaporative light scattering detector) fingerprint, PMP-HPLC-DAD (1-phenyl-3-methyl-5-pyrazolone-high performance liquid chromatography - diode array detector) fingerprint of complete acid hydrolysates and HILIC-HPLC-ELSD (hydrophilic interaction - high performance liquid chromatography - evaporative light scattering detector) fingerprint of enzyme hydrolysates, were established to evaluate the quality of polysaccharides from Poria cocos (PCPs). The similarity evaluation showed that 16 batches of PCPs from different origins had high similarity in structural characteristics based on the multiple fingerprints. The chromatographic data of multiple fingerprints of PCPs were fused, processed and analyzed by chemometric methods including HCA (hierarchical cluster analysis), PCA (principal component analysis) and PLS-DA (partial least squares discriminant analysis). The 16 batches of PCPs were divided into 3 categories in PCA, indicating a certain relationship between the structural characteristics and the origins. PLS-DA analysis indicated that Man, Glc, Gal, Fuc, the components with m/z of 2.22 × 104∼1.53 × 104 Da and 3.46 × 103∼2.69 × 103 Da, oligosaccharides with DPs of 6 and 7, respectively, could be regarded as potential chemical markers for the classification of PCPs from different origins. According to the multiple fingerprints and chemometric analysis, the two commercial samples were proved to be adulterants.
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Affiliation(s)
- Yilin Zhang
- Shanghai Key Laboratory of Functional Materials Chemistry, School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai, 200237, China
| | - Mengqi Wu
- Shanghai Key Laboratory of Functional Materials Chemistry, School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai, 200237, China
| | - Jingrui Xi
- Shanghai Key Laboratory of Functional Materials Chemistry, School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai, 200237, China
| | - Chen Pan
- Shanghai Institute for Food and Drug Control, National Medical Products Administration Key Laboratory for Monitoring and Evaluation of Cosmetics, Shanghai, 201203, China
| | - Zhizhen Xu
- Shanghai Key Laboratory of Functional Materials Chemistry, School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai, 200237, China
| | - Wei Xia
- Shanghai Key Laboratory of Functional Materials Chemistry, School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai, 200237, China.
| | - Wenqing Zhang
- Shanghai Key Laboratory of Functional Materials Chemistry, School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai, 200237, China.
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18
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Campmajó G, Rodríguez-Javier LR, Saurina J, Núñez O. Assessment of paprika geographical origin fraud by high-performance liquid chromatography with fluorescence detection (HPLC-FLD) fingerprinting. Food Chem 2021; 352:129397. [PMID: 33667925 DOI: 10.1016/j.foodchem.2021.129397] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 02/02/2021] [Accepted: 02/14/2021] [Indexed: 12/20/2022]
Abstract
Paprika production under the protected designation of origin (PDO) standardized procedures leads to more quality products. However, it is also related to higher retail prices, making them susceptible to adulteration with low-quality paprika or its agricultural origin's mislabeling. Therefore, in this study, high-performance liquid chromatography with fluorescence detection (HPLC-FLD) fingerprints, strongly related to phenolic acid and polyphenolic compounds, were proposed as chemical markers to assess the classification of paprika from five European regions (three Spanish PDO, Hungary, and the Czech Republic), through a classification decision tree constructed by partial least squares regression-discriminant analysis (PLS-DA) models. After external validation, an excellent classification accuracy of 97.9% was achieved. Moreover, the chromatographic fingerprints were also proposed to detect and quantitate two different paprika geographical origin blend scenarios by partial least squares (PLS) regression. Low external validation and prediction errors -with values below 1.6 and 10.7%, respectively- were obtained.
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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.
| | - Luis R Rodríguez-Javier
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès 1-11, E08028 Barcelona, 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; Serra Húnter Fellow, Generalitat de Catalunya, Rambla de Catalunya 19-21, E08007 Barcelona, Spain
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19
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Núñez N, Martínez C, Saurina J, Núñez O. High-performance liquid chromatography with fluorescence detection fingerprints as chemical descriptors to authenticate the origin, variety and roasting degree of coffee by multivariate chemometric methods. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2021; 101:65-73. [PMID: 32608518 DOI: 10.1002/jsfa.10615] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 06/23/2020] [Accepted: 07/01/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Coffee is one of the most popular beverages around the world, consumed as an infusion of ground roasting coffee beans with a characteristic taste and flavor. Two main varieties, Arabica and Robusta, are produced worldwide. Furthermore, interest of consumers in quality attributes related to coffee production region and varieties is increasing. Thus, it is necessary to encourage the development of simple methodologies to authenticate and guarantee the coffee origin, variety and roasting degree, aiming to prevent fraudulent practices. RESULTS C18 high-performance liquid chromatography with fluorescence detection (HPLC-FLD) fingerprints obtained after brewing coffees without any sample treatment other than filtration (i.e. considerably reducing sample manipulation) were employed as sample chemical descriptors for subsequent coffee characterization and classification by principal component analysis (PCA) and partial least squares regression-discriminant analysis (PLS-DA). PLS-DA showed good classification capabilities regarding coffee origin, variety and roasting degree when employing HPLC-FLD fingerprints, although overlapping occurred for some sample groups. However, the discrimination power increased when selecting HPLC-FLD fingerprinting segments richer in discriminant features, which were deduced from PLS-DA loading plots. In this case, excellent separation was observed and 100% classification rates for both PLS-DA calibrations and predictions were obtained (all samples were correctly classified within their corresponding groups). CONCLUSION HPLC-FLD fingerprinting segments were3 found to be suitable chemical descriptors for discriminating the origin (country of production), variety (Arabica and Robusta) and roasting degree of coffee. Therefore, HPLC-FLD fingerprinting can be proposed as a feasible, simple and cheap methodology to address coffee authentication, especially for developing coffee production countries. © 2020 Society of Chemical Industry.
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Affiliation(s)
- Nerea Núñez
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Barcelona, Spain
| | - Clara Martínez
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Barcelona, Spain
| | - Javier Saurina
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Barcelona, Spain
- Research Institute in Food Nutrition and Food Safety, University of Barcelona, Barcelona, Spain
| | - Oscar Núñez
- Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Barcelona, Spain
- Research Institute in Food Nutrition and Food Safety, University of Barcelona, Barcelona, Spain
- Serra Hunter Fellow. Generalitat de Catalunya, Barcelona, Spain
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20
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Gao B, Xu S, Han L, Liu X. FT-IR-based quantitative analysis strategy for target adulterant in fish oil multiply adulterated with terrestrial animal lipid. Food Chem 2020; 343:128420. [PMID: 33143969 DOI: 10.1016/j.foodchem.2020.128420] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 08/27/2020] [Accepted: 10/14/2020] [Indexed: 11/15/2022]
Abstract
The interference of nontarget adulterant on FT-IR-based target adulterant quantitative analysis was explored and a sequential strategy was proposed to improve the prediction accuracy of the quantitative analysis model. Based on the FT-IR data of fish oil adulterated with terrestrial animal lipid, PLS and PLS-DA results show that quantitative analysis modeled by multiple and single adulteration data do not apply to each other; quantitative models based on the fusion of single and multiple adulteration data were established and showed a low quantitative analysis precision (higher RSD); and the sensitivity and specificity of discrimination analysis for multiply and singly adulterated fish oils both all exceed 0.910. To enhance the detection accuracy, a sequential strategy was proposed; identifying singly or multiply adulterated fish oil and then quantifying the content of adulterant was considered an efficient approach.
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Affiliation(s)
- Bing Gao
- College of Engineering, China Agricultural University, Beijing 100083, China.
| | - Shuai Xu
- College of Engineering, China Agricultural University, Beijing 100083, China.
| | - Lujia Han
- College of Engineering, China Agricultural University, Beijing 100083, China.
| | - Xian Liu
- College of Engineering, China Agricultural University, Beijing 100083, China.
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21
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Comparison of Targeted (HPLC) and Nontargeted (GC-MS and NMR) Approaches for the Detection of Undeclared Addition of Protein Hydrolysates in Turkey Breast Muscle. Foods 2020; 9:foods9081084. [PMID: 32784468 PMCID: PMC7465048 DOI: 10.3390/foods9081084] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 08/04/2020] [Accepted: 08/06/2020] [Indexed: 11/30/2022] Open
Abstract
The adulteration of fresh turkey meat by the undeclared addition of protein hydrolysates is of interest for fraudsters due to the increase of the economic gain by substituting meat with low cost ingredients. The aim of this study was to compare the suitability of three different analytical techniques such as GC-MS and 1H-NMR with HPLC-UV/VIS as a targeted method, for the detection of with protein hydrolysates adulterated turkey meat. For this, turkey breast muscles were treated with different plant- (e.g., wheat) and animal-based (e.g., gelatin, casein) protein hydrolysates with different hydrolyzation degrees (15–53%: partial; 100%: total), which were produced by enzymatic and acidic hydrolysis. A water- and a nontreated sample (REF) served as controls. The data analyses revealed that the hydrolysate-treated samples had significantly higher levels of amino acids (e.g., leucine, phenylalanine, lysine) compared with REF observed with all three techniques concordantly. Furthermore, the nontargeted metabolic profiling (GC-MS and NMR) showed that sugars (glucose, maltose) and/or by-products (build and released during acidic hydrolyses, e.g., levulinic acid) could be used for the differentiation between control and hydrolysates (type, degrees). The combination of amino acid profiling and additional compounds gives stronger evidence for the detection and classification of adulteration in turkey breast meat.
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