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Fakhlaei R, Babadi AA, Sun C, Ariffin NM, Khatib A, Selamat J, Xiaobo Z. Application, challenges and future prospects of recent nondestructive techniques based on the electromagnetic spectrum in food quality and safety. Food Chem 2024; 441:138402. [PMID: 38218155 DOI: 10.1016/j.foodchem.2024.138402] [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: 11/15/2023] [Revised: 12/26/2023] [Accepted: 01/06/2024] [Indexed: 01/15/2024]
Abstract
Safety and quality aspects of food products have always been critical issues for the food production and processing industries. Since conventional quality measurements are laborious, time-consuming, and expensive, it is vital to develop new, fast, non-invasive, cost-effective, and direct techniques to eliminate those challenges. Recently, non-destructive techniques have been applied in the food sector to improve the quality and safety of foodstuffs. The aim of this review is an effort to list non-destructive techniques (X-ray, computer tomography, ultraviolet-visible spectroscopy, hyperspectral imaging, infrared, Raman, terahertz, nuclear magnetic resonance, magnetic resonance imaging, and ultrasound imaging) based on the electromagnetic spectrum and discuss their principle and application in the food sector. This review provides an in-depth assessment of the different non-destructive techniques used for the quality and safety analysis of foodstuffs. We also discussed comprehensively about advantages, disadvantages, challenges, and opportunities for the application of each technique and recommended some solutions and developments for future trends.
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Affiliation(s)
- Rafieh Fakhlaei
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.
| | - Arman Amani Babadi
- School of Energy and Power Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Chunjun Sun
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China; International Joint Research Laboratory of Intelligent Agriculture and Agri-products Processing, Jiangsu University, Zhenjiang 212013, China
| | - Naziruddin Mat Ariffin
- Department of Food Science, Faculty of Food Science and Technology, University Putra Malaysia, Serdang 43400, Selangor, Malaysia
| | - Alfi Khatib
- Pharmacognosy Research Group, Department of Pharmaceutical Chemistry, Kulliyyah of Pharmacy, International Islamic University Malaysia, Kuantan 25200, Pahang Darul Makmur, Malaysia; Faculty of Pharmacy, Airlangga University, Surabaya 60155, Indonesia
| | - Jinap Selamat
- Food Safety and Food Integrity (FOSFI), Institute of Tropical Agriculture and Food Security, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
| | - Zou Xiaobo
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.
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2
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Haider A, Iqbal SZ, Bhatti IA, Alim MB, Waseem M, Iqbal M, Mousavi Khaneghah A. Food authentication, current issues, analytical techniques, and future challenges: A comprehensive review. Compr Rev Food Sci Food Saf 2024; 23:e13360. [PMID: 38741454 DOI: 10.1111/1541-4337.13360] [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: 02/05/2024] [Revised: 03/29/2024] [Accepted: 04/16/2024] [Indexed: 05/16/2024]
Abstract
Food authentication and contamination are significant concerns, especially for consumers with unique nutritional, cultural, lifestyle, and religious needs. Food authenticity involves identifying food contamination for many purposes, such as adherence to religious beliefs, safeguarding health, and consuming sanitary and organic food products. This review article examines the issues related to food authentication and food fraud in recent periods. Furthermore, the development and innovations in analytical techniques employed to authenticate various food products are comprehensively focused. Food products derived from animals are susceptible to deceptive practices, which can undermine customer confidence and pose potential health hazards due to the transmission of diseases from animals to humans. Therefore, it is necessary to employ suitable and robust analytical techniques for complex and high-risk animal-derived goods, in which molecular biomarker-based (genomics, proteomics, and metabolomics) techniques are covered. Various analytical methods have been employed to ascertain the geographical provenance of food items that exhibit rapid response times, low cost, nondestructiveness, and condensability.
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Affiliation(s)
- Ali Haider
- Food Safety and Toxicology Lab, Department of Applied Chemistry, Government College University, Faisalabad, Punjab, Pakistan
| | - Shahzad Zafar Iqbal
- Food Safety and Toxicology Lab, Department of Applied Chemistry, Government College University, Faisalabad, Punjab, Pakistan
| | - Ijaz Ahmad Bhatti
- Department of Chemistry, University of Agriculture, Faisalabad, Pakistan
| | | | - Muhammad Waseem
- Food Safety and Toxicology Lab, Department of Applied Chemistry, Government College University, Faisalabad, Punjab, Pakistan
| | - Munawar Iqbal
- Department of Chemistry, Division of Science and Technology, University of Education, Lahore, Pakistan
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3
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Zhang Z, Li Y, Zhao S, Qie M, Bai L, Gao Z, Liang K, Zhao Y. Rapid analysis technologies with chemometrics for food authenticity field: A review. Curr Res Food Sci 2024; 8:100676. [PMID: 38303999 PMCID: PMC10830540 DOI: 10.1016/j.crfs.2024.100676] [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: 07/24/2023] [Revised: 12/15/2023] [Accepted: 01/07/2024] [Indexed: 02/03/2024] Open
Abstract
In recent years, the problem of food adulteration has become increasingly rampant, seriously hindering the development of food production, consumption, and management. The common analytical methods used to determine food authenticity present challenges, such as complicated analysis processes and time-consuming procedures, necessitating the development of rapid, efficient analysis technology for food authentication. Spectroscopic techniques, ambient ionization mass spectrometry (AIMS), electronic sensors, and DNA-based technology have gradually been applied for food authentication due to advantages such as rapid analysis and simple operation. This paper summarizes the current research on rapid food authenticity analysis technology from three perspectives, including breeds or species determination, quality fraud detection, and geographical origin identification, and introduces chemometrics method adapted to rapid analysis techniques. It aims to promote the development of rapid analysis technology in the food authenticity field.
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Affiliation(s)
- Zixuan Zhang
- Institute of Food and Nutrition Development, Ministry of Agriculture and Rural Affairs, Beijing, China
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-Product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yalan Li
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-Product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Shanshan Zhao
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-Product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Mengjie Qie
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-Product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lu Bai
- Institute of Food and Nutrition Development, Ministry of Agriculture and Rural Affairs, Beijing, China
| | - Zhiwei Gao
- Hangzhou Nutritome Biotech Co., Ltd., Hangzhou, China
| | - Kehong Liang
- Institute of Food and Nutrition Development, Ministry of Agriculture and Rural Affairs, Beijing, China
| | - Yan Zhao
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-Product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing, China
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4
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Biswas A, Hazra SK, Chaudhari SR. Detection of barley malt syrup as an adulterant in honey by 1H NMR profile. Food Chem 2023; 429:136842. [PMID: 37454619 DOI: 10.1016/j.foodchem.2023.136842] [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: 02/24/2023] [Revised: 06/21/2023] [Accepted: 07/06/2023] [Indexed: 07/18/2023]
Abstract
Currently, Barley Malt Syrup (BMS) is one of the forms of growing adulteration in honey. However, there have been no reports regarding its identification by NMR. In this aspect, we proposed a 1H NMR profiling method to discriminate between authentic and honey adulterated with BMS. The authenticated honey samples were artificially adulterated with varying percentages of BMS. It was found that a marker peak primarily falling around the 5.40 ppm region exhibited discrimination between pure and adulterated samples. Furthermore, NMR data of the samples were analyzed using statistical models. The findings demonstrate that NMR sugar profiles region, when combined with PCA analysis, can effectively detect varying degrees of adulteration. Despite qualitative nature of the outcomes, spiking studies have revealed that approach can reliably identify sugar addition at levels as low as 5-10%. Overall, NMR-based approach proves to be effective in detecting BMS as an adulterant in honey.
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Affiliation(s)
- Anisha Biswas
- Department of Plantation Products, Spice and Flavor Technology, CSIR-Central Food Technological Research Institute, Mysore, Karnataka 570020, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Sudipta Kumar Hazra
- Department of Plantation Products, Spice and Flavor Technology, CSIR-Central Food Technological Research Institute, Mysore, Karnataka 570020, India
| | - Sachin R Chaudhari
- Department of Plantation Products, Spice and Flavor Technology, CSIR-Central Food Technological Research Institute, Mysore, Karnataka 570020, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India.
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5
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Zhang XH, Gu HW, Liu RJ, Qing XD, Nie JF. A comprehensive review of the current trends and recent advancements on the authenticity of honey. Food Chem X 2023; 19:100850. [PMID: 37780275 PMCID: PMC10534224 DOI: 10.1016/j.fochx.2023.100850] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 08/15/2023] [Accepted: 08/26/2023] [Indexed: 10/03/2023] Open
Abstract
The authenticity of honey currently poses challenges to food quality control, thus requiring continuous modernization and improvement of related analytical methodologies. This review provides a comprehensively overview of honey authenticity challenges and related analytical methods. Firstly, direct and indirect methods of honey adulteration were described in detail, commenting the existing challenges in current detection methods and market supervision approaches. As an important part, the integrated metabolomic workflow involving sample processing procedures, instrumental analysis techniques, and chemometric tools in honey authenticity studies were discussed, with a focus on their advantages, disadvantages, and scopes. Among them, various improved microscale extraction methods, combined with hyphenated instrumental analysis techniques and chemometric data processing tools, have broad application potential in honey authenticity research. The future of honey authenticity determination will involve the use of simplified and portable methods, which will enable on-site rapid detection and transfer detection technologies from the laboratory to the industry.
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Affiliation(s)
- Xiao-Hua Zhang
- Department of Chemistry and Chemical Engineering, Hunan Institute of Science and Technology, Yueyang, China
- Henan Key Laboratory of Biomarker Based Rapid-detection Technology for Food Safety, Food and Pharmacy College, Xuchang University, Xuchang, China
| | - Hui-Wen Gu
- College of Chemistry and Environmental Engineering, Yangtze University, Jingzhou, China
| | - Ren-Jun Liu
- Collaborative Innovation Center for Water Pollution Control and Water Safety in Karst Area, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, China
| | - Xiang-Dong Qing
- Hunan Provincial Key Laboratory of Dark Tea and Jin-hua, College of Materials and Chemical Engineering, Hunan City University, Yiyang, China
| | - Jin-Fang Nie
- Collaborative Innovation Center for Water Pollution Control and Water Safety in Karst Area, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, China
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6
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Biswas A, Naresh KS, Jaygadkar SS, Chaudhari SR. Enabling honey quality and authenticity with NMR and LC-IRMS based platform. Food Chem 2023; 416:135825. [PMID: 36924528 DOI: 10.1016/j.foodchem.2023.135825] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 12/22/2022] [Accepted: 02/27/2023] [Indexed: 03/04/2023]
Abstract
Honey has been known for economically motivated adulteration around the world, because of its high demand and short supply. As consequence increasing honey production using the deliberate addition of sugar syrups while claiming a fictitious origin and diversifying it to increase its value. Generally, honey testing is supervised by a set of guidelines and quality parameters to ensure its quality and authenticity. As per the many regulatory bodies, current honey scams have been challenging to identify with conventional methods, so quality control labs require sophisticated technology. With these paradigm shifts, the aim of the present review is focused on the authenticity of honey through two important cutting-edge methods viz LC-IRMS and NMR. The LC-IRMS aids in the detection of added C3 and C4 sugars. Whereas NMR has provided a potent solution by allowing the classification of botanical varieties and geographical origin along with the quantification of a set of quality parameters in a single experiment.
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Affiliation(s)
- Anisha Biswas
- Department of Plantation Products, Spice and Flavor Technology, CSIR-Central Food Technological Research Institute, Mysore, Karnataka 570020, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - K S Naresh
- Department of Plantation Products, Spice and Flavor Technology, CSIR-Central Food Technological Research Institute, Mysore, Karnataka 570020, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | | | - Sachin R Chaudhari
- Department of Plantation Products, Spice and Flavor Technology, CSIR-Central Food Technological Research Institute, Mysore, Karnataka 570020, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India.
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Silva JR, Henrique-Bana FC, Villas-Bôas JK, Colombo Pimentel T, Spinosa WA, Prudencio SH. Maturation of honey from Uruçú-Amarela ( Melipona mondury): Metagenomics, metabolomics by NMR 1H, physicochemical and antioxidant properties. FOOD CHEMISTRY. MOLECULAR SCIENCES 2023; 6:100157. [PMID: 36588603 PMCID: PMC9794890 DOI: 10.1016/j.fochms.2022.100157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 11/17/2022] [Accepted: 12/11/2022] [Indexed: 06/17/2023]
Abstract
The objective of this study was to characterize the microbiota biodiversity of Uruçú-Amarela honey through metagenomics. Furthermore, the impact of maturation temperatures (20 and 30 °C) and time (0-180 days) on the physicochemical and antioxidant properties was investigated. 1H NMR was performed to verify metabolites formed during maturation. Uruçú-Amarela honey was mainly composed by lactic acid bacteria and osmophilic yeasts of genus Zygosaccharomyces. Maturation at 30 °C led to a higher fermentation activity, resulting in greater carbohydrate consumption, ethanol formation (0.0-0.6 %) and increased acidity (34.78-45.74 meq/kg) over the 180 days. It also resulted in honey with higher brown color (a* 0.7 to 3.89, b* 17.50-25.29) and antioxidant capacity, corroborating that the maturation is a suitable preservation technique for stingless bee honey, because it does not cause negative changes as it extends the shelf life of the stingless bee honey.
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Affiliation(s)
- José Renato Silva
- Department of Food Science and Technology, Center of Agricultural Sciences, State University of Londrina, Londrina-PR 86057-970, Brazil
| | - Fernanda Carla Henrique-Bana
- Department of Food Science and Technology, Center of Agricultural Sciences, State University of Londrina, Londrina-PR 86057-970, Brazil
| | | | - Tatiana Colombo Pimentel
- Department of Food Science and Technology, Center of Agricultural Sciences, State University of Londrina, Londrina-PR 86057-970, Brazil
- Federal Institute of Paraná, Campus Paranavaí, Paranavaí-PR, Brazil
| | - Wilma Aparecida Spinosa
- Department of Food Science and Technology, Center of Agricultural Sciences, State University of Londrina, Londrina-PR 86057-970, Brazil
| | - Sandra Helena Prudencio
- Department of Food Science and Technology, Center of Agricultural Sciences, State University of Londrina, Londrina-PR 86057-970, Brazil
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8
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Lin Q, Meng C, Liu J, Liu F, Zhou Q, Liu J, Peng C, Xiong L. An Optimized Two-Dimensional Quantitative Nuclear Magnetic Resonance Strategy for the Rapid Quantitation of Diester-Type C 19-Diterpenoid Alkaloids from Aconitum carmichaelii. Anal Chem 2023. [PMID: 37209123 DOI: 10.1021/acs.analchem.2c05109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
With the development of nuclear magnetic resonance (NMR) spectrometers and probes, two-dimensional quantitative nuclear magnetic resonance (2D qNMR) technology with a high signal resolution and great application potential has become increasingly accessible for the quantitation of complex mixtures. However, the requirement that the relaxation recovery time be equal to at least five times T1 (longitudinal relaxation time) makes it difficult for 2D qNMR to simultaneously achieve high quantitative accuracy and high data acquisition efficiency. By comprehensively using relaxation optimization and nonuniform sampling, we successfully established an optimized 2D qNMR strategy for HSQC experiments at the half-hour level and then accurately quantified the diester-type C19-diterpenoid alkaloids in Aconitum carmichaelii. The optimized strategy had the advantages of high efficiency, high accuracy, good reproducibility, and low cost and thus could serve as a reference to optimize 2D qNMR experiments for quantitative analysis of natural products, metabolites, and other complex mixtures.
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Affiliation(s)
- Qiao Lin
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
- Institute of Innovative Medicine Ingredients of Southwest Specialty Medicinal Materials, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
| | - Chunwang Meng
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
- Institute of Innovative Medicine Ingredients of Southwest Specialty Medicinal Materials, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
| | - Jie Liu
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
- Institute of Innovative Medicine Ingredients of Southwest Specialty Medicinal Materials, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
| | - Fei Liu
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
- Institute of Innovative Medicine Ingredients of Southwest Specialty Medicinal Materials, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
| | - Qinmei Zhou
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
- Institute of Innovative Medicine Ingredients of Southwest Specialty Medicinal Materials, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
- Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
| | - Juan Liu
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
- Institute of Innovative Medicine Ingredients of Southwest Specialty Medicinal Materials, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
| | - Cheng Peng
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
| | - Liang Xiong
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
- Institute of Innovative Medicine Ingredients of Southwest Specialty Medicinal Materials, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
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Tarapoulouzi M, Mironescu M, Drouza C, Mironescu ID, Agriopoulou S. Insight into the Recent Application of Chemometrics in Quality Analysis and Characterization of Bee Honey during Processing and Storage. Foods 2023; 12:473. [PMID: 36766000 PMCID: PMC9914568 DOI: 10.3390/foods12030473] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 12/30/2022] [Accepted: 01/16/2023] [Indexed: 01/20/2023] Open
Abstract
The application of chemometrics, a widely used science in food studies (and not only food studies) has begun to increase in importance with chemometrics being a very powerful tool in analyzing large numbers of results. In the case of honey, chemometrics is usually used for assessing honey authenticity and quality control, combined with well-established analytical methods. Research related to investigation of the quality changes in honey due to modifications after processing and storage is rare, with a visibly increasing tendency in the last decade (and concentrated on investigating novel methods to preserve the honey quality, such as ultrasound or high-pressure treatment). This review presents the evolution in the last few years in using chemometrics in analyzing honey quality during processing and storage. The advantages of using chemometrics in assessing honey quality during storage and processing are presented, together with the main characteristics of some well-known chemometric methods. Chemometrics prove to be a successful tool to differentiate honey samples based on changes of characteristics during storage and processing.
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Affiliation(s)
- Maria Tarapoulouzi
- Department of Chemistry, Faculty of Pure and Applied Science, University of Cyprus, P.O. Box 20537, Nicosia 1678, Cyprus
| | - Monica Mironescu
- Faculty of Agricultural Sciences Food Industry and Environmental Protection, Lucian Blaga University of Sibiu, Bv. Victoriei 10, 550024 Sibiu, Romania
| | - Chryssoula Drouza
- Department of Agricultural Production, Biotechnology and Food Science, Cyprus University of Technology, P.O. Box 50329, Limassol 3036, Cyprus
| | - Ion Dan Mironescu
- Faculty of Agricultural Sciences Food Industry and Environmental Protection, Lucian Blaga University of Sibiu, Bv. Victoriei 10, 550024 Sibiu, Romania
| | - Sofia Agriopoulou
- Department of Food Science and Technology, University of the Peloponnese, Antikalamos, 24100 Kalamata, Greece
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10
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Yan S, Wang W, Zhao W, Tian W, Wang X, Wu L, Xue X. Identification of the maturity of acacia honey by an endogenous oligosaccharide: A preliminary study. Food Chem 2023; 399:134005. [DOI: 10.1016/j.foodchem.2022.134005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 07/05/2022] [Accepted: 08/21/2022] [Indexed: 11/16/2022]
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11
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Brar DS, Pant K, Krishna R, Kaur S, Rasane P, Nanda V, Saxena S, Gautam S. A comprehensive review on unethical honey: Validation by emerging techniques. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.109482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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12
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Quality assessment and chemical diversity of Australian propolis from Apis mellifera bees. Sci Rep 2022; 12:13574. [PMID: 35945451 PMCID: PMC9362168 DOI: 10.1038/s41598-022-17955-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 08/03/2022] [Indexed: 11/12/2022] Open
Abstract
The propolis industry is well established in European, South American and East Asian countries. Within Australia, this industry is beginning to emerge with a few small-scale producers. To contribute to the development of the Australian propolis industry, the present study aimed to examine the quality and chemical diversity of propolis collected from various regions across Australia. The results of testing 158 samples indicated that Australian propolis had pure resin yielding from 2 to 81% by weight, total phenolic content and total flavonoid content in one gram of dry extract ranging from a few up to 181 mg of gallic acid equivalent and 145 mg of quercetin equivalent, respectively. Some Australian propolis showed more potent antioxidant activity than the well-known Brazilian green, Brazilian red, and Uruguayan and New Zealand poplar-type propolis in an in vitro DPPH assay. In addition, an HPLC–UV analysis resulted in the identification of 16 Australian propolis types which can be considered as high-grade propolis owing to their high total phenolic content. Chemometric analysis of their 1H NMR spectra revealed that propolis originating from the eastern and western coasts of Australia could be significantly discriminated based on their chemical composition.
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14
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Martins FCOL, Alcantara GMRN, Silva AFS, Melchert WR, Rocha FRP. The role of 5-hydroxymethylfurfural in food and recent advances in analytical methods. Food Chem 2022; 395:133539. [PMID: 35779506 DOI: 10.1016/j.foodchem.2022.133539] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 05/09/2022] [Accepted: 06/18/2022] [Indexed: 11/18/2022]
Abstract
The thermal processing, storage, and transportation of foodstuffs (e.g., fruit juices, coffee, honey, and vinegar) generate 5-hydroxymethylfurfural (HMF). The food industry uses this compound as a quality marker, thus increasing the demand for fast and reliable analytical methods for its determination. This review focuses on the formation of HMF in food, its desirable and toxic effects, and recent advances in analytical methods for its determination in foodstuffs. The advantages and limitations of these analytical approaches are discussed relative to the main analytical features.
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Affiliation(s)
- Fernanda C O L Martins
- Center for Nuclear Energy in Agriculture, University of São Paulo, P.O. Box 96, Piracicaba, SP, 13416-000, Brazil; College of Agriculture "Luiz de Queiroz", University of São Paulo, P.O. Box 9, Piracicaba, SP, 13418-970, Brazil
| | - Gabriela M R N Alcantara
- Center for Nuclear Energy in Agriculture, University of São Paulo, P.O. Box 96, Piracicaba, SP, 13416-000, Brazil; College of Agriculture "Luiz de Queiroz", University of São Paulo, P.O. Box 9, Piracicaba, SP, 13418-970, Brazil
| | - Anna Flavia S Silva
- Center for Nuclear Energy in Agriculture, University of São Paulo, P.O. Box 96, Piracicaba, SP, 13416-000, Brazil
| | - Wanessa R Melchert
- College of Agriculture "Luiz de Queiroz", University of São Paulo, P.O. Box 9, Piracicaba, SP, 13418-970, Brazil.
| | - Fábio R P Rocha
- Center for Nuclear Energy in Agriculture, University of São Paulo, P.O. Box 96, Piracicaba, SP, 13416-000, Brazil
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15
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Wu X, Xu B, Ma R, Niu Y, Gao S, Liu H, Zhang Y. Identification and quantification of adulterated honey by Raman spectroscopy combined with convolutional neural network and chemometrics. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2022; 274:121133. [PMID: 35299093 DOI: 10.1016/j.saa.2022.121133] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 02/23/2022] [Accepted: 03/07/2022] [Indexed: 06/14/2023]
Abstract
In this study, Raman spectroscopy combined with convolutional neural network (CNN) and chemometrics was used to achieve the identification and quantification of honey samples adulterated with high fructose corn syrup, rice syrup, maltose syrup and blended syrup, respectively. The shallow CNNs utilized to analyze honey mixed with single-variety syrup classified samples into four categories by the adulteration concentration with more than 97% accuracy, and the general CNN model for simultaneously detecting honey adulterated with any type of syrup obtained an accuracy of 94.79%. The established CNNs had the best performance compared with several chemometric classification algorithms. In addition, partial least square regression (PLS) successfully predicted the purity of honey mixed with single syrup, while coefficients of determination and root mean square errors of prediction were greater than 0.98 and less than 3.50, respectively. Therefore, the proposed methods based on Raman spectra have important practical significance for food safety and quality control of honey products.
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Affiliation(s)
- Xijun Wu
- Measurement Technology & Instrumentation Key Laboratory of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004 China
| | - Baoran Xu
- Measurement Technology & Instrumentation Key Laboratory of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004 China.
| | - Renqi Ma
- Measurement Technology & Instrumentation Key Laboratory of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004 China
| | - Yudong Niu
- Measurement Technology & Instrumentation Key Laboratory of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004 China
| | - Shibo Gao
- Measurement Technology & Instrumentation Key Laboratory of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004 China
| | - Hailong Liu
- Measurement Technology & Instrumentation Key Laboratory of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004 China
| | - Yungang Zhang
- Measurement Technology & Instrumentation Key Laboratory of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004 China
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16
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Discriminant Analysis of the Nutritional Components between Organic Eggs and Conventional Eggs: A 1H NMR-Based Metabolomics Study. Molecules 2022; 27:molecules27093008. [PMID: 35566355 PMCID: PMC9102658 DOI: 10.3390/molecules27093008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 04/14/2022] [Accepted: 05/05/2022] [Indexed: 02/01/2023] Open
Abstract
The difference of nutrient composition between organic eggs and conventional eggs has always been a concern of people. In this study, 1H nuclear magnetic resonance (NMR) technique combined with multivariate statistical analyses was conducted to identify the metabolite different in egg yolk and egg white in order to reveal the nutritional components information between organic and conventional eggs. The results showed that the nutrient content and composition characteristics were different between organic and conventional eggs, among which the content of glucose, putrescine, amino acids and their derivatives were found higher in the organic eggs yolk, while phospholipids were demonstrated higher in conventional eggs yolk. Organic acid, alcohol, amine, choline and amino acids were higher in conventional eggs white, but glucose and lactate in organic egg were higher. Our study demonstrated that there are more nutritive components and higher nutritional value in organic eggs than conventional eggs, especially for the growth and development of infants and young children, and conventional eggs have more advantages in promoting lipid metabolism, preventing fatty liver, and reducing serum cholesterol. Eggs have important nutritional value to human body, and these two kinds of eggs can be selected according to the actual nutrient needs.
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17
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Li Y, Lu Z, Abrahamsson DP, Song W, Yang C, Huang Q, Wang J. Non-targeted analysis for organic components of microplastic leachates. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 816:151598. [PMID: 34774944 DOI: 10.1016/j.scitotenv.2021.151598] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 11/05/2021] [Accepted: 11/07/2021] [Indexed: 06/13/2023]
Abstract
Organic components of microplastic leachates were investigated in an integrated non-targeted analysis study that included statistical analysis on leachates generated under different leaching scenarios. Leaching experiments were undertaken with simulated gastric fluid (SGF), river water, and seawater with common polymer types, including polyethylene, polypropylene, polyvinyl chloride, polyethylene terephthalate, and polyester fabrics comprising both raw and recycled materials. Totals of 111.0 ± 26.7, 98.5 ± 20.3, and 53.5 ± 4.7 different features were tentatively identified as compounds in SGF, freshwater, and seawater leachates, respectively, of which 5 compounds were confirmed by reference standards. The leaching capacities of the media were compared, and the clusters of structurally related features leached in the same medium were studied. For leachates generated from raw and recycled plastics, volcano plots and Pearson's Chi-squared tests were used to identify characteristic features. More characteristic features (3-20) had an average intensity across all recycled plastics that were significantly higher (p < 0.05) than that (1-3) of raw plastics under different conditions. The results indicate that gastric solution is more likely to leach components from microplastics, and there exists the difference of leachate's organic composition between raw and recycled materials, providing new insights into understanding microplastic environmental effects.
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Affiliation(s)
- Yubo Li
- College of Environmental Science and Engineering, Tongji University, Shanghai 200092, PR China; State Key Laboratory of Pollution Control and Resource Reuse, Shanghai 200092, PR China
| | - Zhibo Lu
- College of Environmental Science and Engineering, Tongji University, Shanghai 200092, PR China; State Key Laboratory of Pollution Control and Resource Reuse, Shanghai 200092, PR China.
| | - Dimitri Panagopoulos Abrahamsson
- Program on Reproductive Health and the Environment, Department of Obstetrics and Gynecology, University of California, San Francisco, CA 94158, USA
| | - Weihua Song
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, PR China
| | - Chao Yang
- College of Environmental Science and Engineering, Tongji University, Shanghai 200092, PR China; State Key Laboratory of Pollution Control and Resource Reuse, Shanghai 200092, PR China
| | - Qinghui Huang
- College of Environmental Science and Engineering, Tongji University, Shanghai 200092, PR China; State Key Laboratory of Pollution Control and Resource Reuse, Shanghai 200092, PR China
| | - Juan Wang
- College of Environmental Science and Engineering, Tongji University, Shanghai 200092, PR China; State Key Laboratory of Pollution Control and Resource Reuse, Shanghai 200092, PR China
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18
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Origin verification of Chinese concentrated apple juice using stable isotopic and mineral elemental fingerprints coupled with chemometrics. J Food Compost Anal 2022. [DOI: 10.1016/j.jfca.2022.104424] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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19
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Labsvards KD, Rudovica V, Kluga R, Rusko J, Busa L, Bertins M, Eglite I, Naumenko J, Salajeva M, Viksna A. Determination of Floral Origin Markers of Latvian Honey by Using IRMS, UHPLC-HRMS, and 1H-NMR. Foods 2021; 11:foods11010042. [PMID: 35010167 PMCID: PMC8750591 DOI: 10.3390/foods11010042] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 12/20/2021] [Accepted: 12/22/2021] [Indexed: 12/26/2022] Open
Abstract
The economic significance of honey production is crucial; therefore, modern and efficient methods of authentication are needed. During the last decade, various data processing methods and a combination of several instrumental methods have been increasingly used in food analysis. In this study, the chemical composition of monofloral buckwheat (Fagopyrum esculentum), clover (Trifolium repens), heather (Calluna vulgaris), linden (Tilia cordata), rapeseed (Brassica napus), willow (Salix cinerea), and polyfloral honey samples of Latvian origin were investigated using several instrumental analysis methods. The data from light stable isotope ratio mass spectrometry (IRMS), ultra-high performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS), and nuclear magnetic resonance (NMR) analysis methods were used in combination with multivariate analysis to characterize honey samples originating from Latvia. Results were processed using the principal component analysis (PCA) to study the potential possibilities of evaluating the differences between honey of different floral origins. The results indicate the possibility of strong differentiation of heather and buckwheat honeys, and minor differentiation of linden honey from polyfloral honey types. The main indicators include depleted δ15N values for heather honey protein, elevated concentration levels of rutin for buckwheat honey, and qualitative presence of specific biomarkers within NMR for linden honey.
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Affiliation(s)
- Kriss Davids Labsvards
- Department of Chemistry, University of Latvia, Jelgavas Street 1, LV-1004 Riga, Latvia; (V.R.); (R.K.); (J.R.); (L.B.); (M.B.); (J.N.); (M.S.); (A.V.)
- Institute of Food Safety, Animal Health and Environment “BIOR”, Lejupes Street 3, LV-1076 Riga, Latvia
- Correspondence: ; Tel.: +371-26395784
| | - Vita Rudovica
- Department of Chemistry, University of Latvia, Jelgavas Street 1, LV-1004 Riga, Latvia; (V.R.); (R.K.); (J.R.); (L.B.); (M.B.); (J.N.); (M.S.); (A.V.)
| | - Rihards Kluga
- Department of Chemistry, University of Latvia, Jelgavas Street 1, LV-1004 Riga, Latvia; (V.R.); (R.K.); (J.R.); (L.B.); (M.B.); (J.N.); (M.S.); (A.V.)
| | - Janis Rusko
- Department of Chemistry, University of Latvia, Jelgavas Street 1, LV-1004 Riga, Latvia; (V.R.); (R.K.); (J.R.); (L.B.); (M.B.); (J.N.); (M.S.); (A.V.)
- Institute of Food Safety, Animal Health and Environment “BIOR”, Lejupes Street 3, LV-1076 Riga, Latvia
| | - Lauma Busa
- Department of Chemistry, University of Latvia, Jelgavas Street 1, LV-1004 Riga, Latvia; (V.R.); (R.K.); (J.R.); (L.B.); (M.B.); (J.N.); (M.S.); (A.V.)
| | - Maris Bertins
- Department of Chemistry, University of Latvia, Jelgavas Street 1, LV-1004 Riga, Latvia; (V.R.); (R.K.); (J.R.); (L.B.); (M.B.); (J.N.); (M.S.); (A.V.)
| | - Ineta Eglite
- Latvian Beekeeping Association, Rigas Street 22, LV-3004 Jelgava, Latvia;
| | - Jevgenija Naumenko
- Department of Chemistry, University of Latvia, Jelgavas Street 1, LV-1004 Riga, Latvia; (V.R.); (R.K.); (J.R.); (L.B.); (M.B.); (J.N.); (M.S.); (A.V.)
| | - Marina Salajeva
- Department of Chemistry, University of Latvia, Jelgavas Street 1, LV-1004 Riga, Latvia; (V.R.); (R.K.); (J.R.); (L.B.); (M.B.); (J.N.); (M.S.); (A.V.)
| | - Arturs Viksna
- Department of Chemistry, University of Latvia, Jelgavas Street 1, LV-1004 Riga, Latvia; (V.R.); (R.K.); (J.R.); (L.B.); (M.B.); (J.N.); (M.S.); (A.V.)
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20
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Islam MK, Vinsen K, Sostaric T, Lim LY, Locher C. Detection of syrup adulterants in manuka and jarrah honey using HPTLC-multivariate data analysis. PeerJ 2021; 9:e12186. [PMID: 34616629 PMCID: PMC8464195 DOI: 10.7717/peerj.12186] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 08/30/2021] [Indexed: 11/25/2022] Open
Abstract
High-Performance Thin-Layer Chromatography (HPTLC) was used in a chemometric investigation of the derived sugar and organic extract profiles of two different honeys (Manuka and Jarrah) with adulterants. Each honey was adulterated with one of six different sugar syrups (rice, corn, golden, treacle, glucose and maple syrups) in five different concentrations (10%, 20%, 30%, 40%, and 50% w/w). The chemometric analysis was based on the combined sugar and organic extract profiles’ datasets. To obtain the respective sugar profiles, the amount of fructose, glucose, maltose, and sucrose present in the honey was quantified and for the organic extract profile, the honey’s dichloromethane extract was investigated at 254 and 366 nm, as well as at T (Transmittance) white light and at 366 nm after derivatisation. The presence of sugar syrups, even at a concentration of only 10%, significantly influenced the honeys’ sugar and organic extract profiles and multivariate data analysis of these profiles, in particular cluster analysis (CA), principal component analysis (PCA), principal component regression (PCR), partial least-squares regression (PLSR) and Machine Learning using an artificial neural network (ANN), were able to detect post-harvest syrup adulterations and to discriminate between neat and adulterated honey samples. Cluster analysis and principal component analysis, for instance, could easily differentiate between neat and adulterated honeys through the use of CA or PCA plots. In particular the presence of excess amounts of maltose and sucrose allowed for the detection of sugar adulterants and adulterated honeys by HPTLC-multivariate data analysis. Partial least-squares regression and artificial neural networking were employed, with augmented datasets, to develop optimal calibration for the adulterated honeys and to predict those accurately, which suggests a good predictive capacity of the developed model.
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Affiliation(s)
- Md Khairul Islam
- Division of Pharmacy, School of Allied Health, University of Western Australia, Crawley, WA, Australia.,Cooperative Research Centre for Honey Bee Products Limited (CRC HBP), Perth, WA, Australia
| | - Kevin Vinsen
- International Centre for Radio Astronomy Research (ICRAR), University of Western Australia, Crawley, WA, Australia
| | - Tomislav Sostaric
- Division of Pharmacy, School of Allied Health, University of Western Australia, Crawley, WA, Australia
| | - Lee Yong Lim
- Division of Pharmacy, School of Allied Health, University of Western Australia, Crawley, WA, Australia
| | - Cornelia Locher
- Division of Pharmacy, School of Allied Health, University of Western Australia, Crawley, WA, Australia.,Cooperative Research Centre for Honey Bee Products Limited (CRC HBP), Perth, WA, Australia
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21
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Composition Profiling and Authenticity Assessment of Camellia Oil Using High Field and Low Field 1H NMR. Molecules 2021; 26:molecules26164738. [PMID: 34443325 PMCID: PMC8400449 DOI: 10.3390/molecules26164738] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 07/28/2021] [Accepted: 08/03/2021] [Indexed: 11/17/2022] Open
Abstract
Camellia oil (CA), mainly produced in southern China, has always been called Oriental olive oil (OL) due to its similar physicochemical properties to OL. The high nutritional value and high selling price of CA make mixing it with other low-quality oils prevalent, in order to make huge profits. In this paper, the transverse relaxation time (T2) distribution of different brands of CA and OL, and the variation in transverse relaxation parameters when adulterated with corn oil (CO), were assessed via low field nuclear magnetic resonance (LF-NMR) imagery. The nutritional compositions of CA and OL and their quality indices were obtained via high field NMR (HF-NMR) spectroscopy. The results show that the fatty acid evaluation indices values, including for squalene, oleic acid, linolenic acid and iodine, were higher in CA than in OL, indicating the nutritional value of CA. The adulterated CA with a content of CO more than 20% can be correctly identified by principal component analysis or partial least squares discriminant analysis, and the blended oils could be successfully classified by orthogonal partial least squares discriminant analysis, with an accuracy of 100% when the adulteration ratio was above 30%. These results indicate the practicability of LF-NMR in the rapid screening of food authenticity.
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22
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Ghidotti M, Papoci S, Dumitrascu C, Zdiniakova T, Fiamegos Y, Gutiñas MBDLC. ED-XRF as screening tool to help customs laboratories in their fight against fraud. State-of-the-art. TALANTA OPEN 2021. [DOI: 10.1016/j.talo.2021.100040] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
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23
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Shen S, Yang Y, Wang J, Chen X, Liu T, Zhuo Q. [Analysis of differences between unifloral honeys from different botanical origins based on non-targeted metabolomics by ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry]. Se Pu 2021; 39:291-300. [PMID: 34227310 PMCID: PMC9403802 DOI: 10.3724/sp.j.1123.2020.06029] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
不同的蜜源植物具有结构多样的次生代谢产物。该研究以8种不同蜜源单花蜜(洋槐蜜、枣花蜜、荆条蜜、椴树蜜、荞麦蜜、麦卢卡蜜、枸杞蜜、益母草蜜)为研究对象,建立了基于超高效液相色谱-四极杆飞行时间质谱技术(UPLC-Q-TOF-MSE)的非靶向代谢组学方法,考察了不同蜜源中次生代谢产物的差异。该研究采用固相萃取前处理方法和UPLC-Q-TOF-MSE方法,获得不同蜜源单花蜜的植物代谢组信息,并构建了多变量统计分析模型,对不同来源的单花蜜进行模式识别和差异分析,发现洋槐蜜、枣花蜜、荆条蜜、椴树蜜、荞麦蜜、麦卢卡蜜相互间存在不同程度的显著差异。结合模型的变量重要性投影、方差分析与最大差异倍数值,根据精确前体离子和碎片离子质量信息检索Chemspider、HMDB数据库,该研究筛选并鉴定出32个代谢差异化合物,其中黄酮类化合物18个、酚酸类化合物7个、苯苷与萜苷类化合物6个、甾体类化合物1个;研究发现麦卢卡蜜和荞麦蜜以黄酮类化合物为主要差异代谢物,荆条蜜中酚酸类化合物为特征性表达,苯苷与萜苷类化合物主要为椴树蜜的特征代谢物。该研究从植物代谢组学角度初步揭示了不同单花蜜的代谢产物差异性以及特征化合物,为基于化学分析技术的蜂蜜溯源识别与质量评价提供了有效的研究策略。
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Affiliation(s)
- Shi Shen
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Key Laboratory of Trace Element Nutrition, National Health Commission of the People's Republic of China, Beijing 100050, China
| | - Yi Yang
- Beijing Center for Disease Control and Prevention, Beijing 100013, China
| | - Jingbo Wang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Key Laboratory of Trace Element Nutrition, National Health Commission of the People's Republic of China, Beijing 100050, China
| | - Xi Chen
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Key Laboratory of Trace Element Nutrition, National Health Commission of the People's Republic of China, Beijing 100050, China
| | - Tingting Liu
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Key Laboratory of Trace Element Nutrition, National Health Commission of the People's Republic of China, Beijing 100050, China
| | - Qin Zhuo
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Key Laboratory of Trace Element Nutrition, National Health Commission of the People's Republic of China, Beijing 100050, China
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24
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Herbert-Pucheta JE, Lozada-Ramírez JD, Ortega-Regules AE, Hernández LR, Anaya de Parrodi C. Nuclear Magnetic Resonance Metabolomics with Double Pulsed-Field-Gradient Echo and Automatized Solvent Suppression Spectroscopy for Multivariate Data Matrix Applied in Novel Wine and Juice Discriminant Analysis. Molecules 2021; 26:molecules26144146. [PMID: 34299421 PMCID: PMC8307358 DOI: 10.3390/molecules26144146] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 06/21/2021] [Accepted: 06/23/2021] [Indexed: 12/03/2022] Open
Abstract
The quality of foods has led researchers to use various analytical methods to determine the amounts of principal food constituents; some of them are the NMR techniques with a multivariate statistical analysis (NMR-MSA). The present work introduces a set of NMR-MSA novelties. First, the use of a double pulsed-field-gradient echo (DPFGE) experiment with a refocusing band-selective uniform response pure-phase selective pulse for the selective excitation of a 5–10-ppm range of wine samples reveals novel broad 1H resonances. Second, an NMR-MSA foodomics approach to discriminate between wine samples produced from the same Cabernet Sauvignon variety fermented with different yeast strains proposed for large-scale alcohol reductions. Third a comparative study between a nonsupervised Principal Component Analysis (PCA), supervised standard partial (PLS-DA), and sparse (sPLS-DA) least squares discriminant analysis, as well as orthogonal projections to a latent structures discriminant analysis (OPLS-DA), for obtaining holistic fingerprints. The MSA discriminated between different Cabernet Sauvignon fermentation schemes and juice varieties (apple, apricot, and orange) or juice authentications (puree, nectar, concentrated, and commercial juice fruit drinks). The new pulse sequence DPFGE demonstrated an enhanced sensitivity in the aromatic zone of wine samples, allowing a better application of different unsupervised and supervised multivariate statistical analysis approaches.
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Affiliation(s)
- José Enrique Herbert-Pucheta
- Consejo Nacional de Ciencia y Tecnología-Laboratorio Nacional de Investigación y Servicio Agroalimentario y Forestal, Universidad Autónoma Chapingo, Carretera México-Texcoco km 38.5, Chapingo, Estado de México 56230, Mexico;
- Departamento de Química Orgánica, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Prolongación de Carpio y Plan de Ayala s/n, Colonia Santo Tomás, Ciudad de México 11340, Mexico
| | - José Daniel Lozada-Ramírez
- Departamento de Ciencias Químico Biológicas, Universidad de las Américas Puebla, San Andrés Cholula 72810, Mexico;
| | - Ana E. Ortega-Regules
- Departamento de Ciencias de la Salud, Universidad de las Américas Puebla, San Andrés Cholula 72810, Mexico;
| | - Luis Ricardo Hernández
- Departamento de Ciencias Químico Biológicas, Universidad de las Américas Puebla, San Andrés Cholula 72810, Mexico;
- Correspondence: (L.R.H.); (C.A.d.P.); Tel.: +52-222-2292412 (L.R.H.); +52-222-2292005 (C.A.d.P.)
| | - Cecilia Anaya de Parrodi
- Departamento de Ciencias Químico Biológicas, Universidad de las Américas Puebla, San Andrés Cholula 72810, Mexico;
- Correspondence: (L.R.H.); (C.A.d.P.); Tel.: +52-222-2292412 (L.R.H.); +52-222-2292005 (C.A.d.P.)
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25
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Tan Y, Chen B, Ren C, Guo M, Wang J, Shi K, Wu X, Feng Y. Rapid identification model based on decision tree algorithm coupling with 1H NMR and feature analysis by UHPLC-QTOFMS spectrometry for sandalwood. J Chromatogr B Analyt Technol Biomed Life Sci 2020; 1161:122449. [PMID: 33246279 DOI: 10.1016/j.jchromb.2020.122449] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 10/25/2020] [Accepted: 11/04/2020] [Indexed: 12/01/2022]
Abstract
Sandalwood is one of the most valuable woods in the world. However, today's counterfeits are widespread, it is difficult to distinguish authenticity. In this paper, similar genus (Dalbergia and Pterocarpus) and confused species (Gluta sp.) of sandalwood were quickly and efficiently identified. Rapid identification model based on 1H NMR and decision tree (DT) algorithm was firstly developed for the identification of sandalwood, and the accuracy was improved by introducing the AdaBoost algorithm. The accuracy of the final model was above 95%. And the feature components between different species of sandalwood were further explored using UHPLC-QTOFMS and NMR spectrometry. The results showed that 183 compounds were identified, among which 99 were known components, 84 were unknown components. The 1H NMR and 13C NMR signals of 505 samples were assigned, among them, 14 compounds were attributed, characteristic chemical shift intervals with great differences in the model were analysed. Furthermore, the fragmentation pattern of different compounds from sandalwood, in both positive and negative ion ESI modes, was summarized. The results showed a potential and rapid tool based on DT, NMR spectroscopy and UHPLC-QTOFMS, which had performed great potential for rapid identification and feature analysis of sandalwood.
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Affiliation(s)
- Youzhen Tan
- New Drug Reserach And Development Center, Guangdong Pharmaceutical University, Guangzhou, Guangdong, PR China
| | - Biying Chen
- New Drug Reserach And Development Center, Guangdong Pharmaceutical University, Guangzhou, Guangdong, PR China
| | - Cui Ren
- New Drug Reserach And Development Center, Guangdong Pharmaceutical University, Guangzhou, Guangdong, PR China
| | - Mingxin Guo
- New Drug Reserach And Development Center, Guangdong Pharmaceutical University, Guangzhou, Guangdong, PR China
| | - Juanxia Wang
- New Drug Reserach And Development Center, Guangdong Pharmaceutical University, Guangzhou, Guangdong, PR China
| | - Kexing Shi
- New Drug Reserach And Development Center, Guangdong Pharmaceutical University, Guangzhou, Guangdong, PR China
| | - Xia Wu
- New Drug Reserach And Development Center, Guangdong Pharmaceutical University, Guangzhou, Guangdong, PR China
| | - Yifan Feng
- New Drug Reserach And Development Center, Guangdong Pharmaceutical University, Guangzhou, Guangdong, PR China.
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26
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Zhang J, Chen H, Fan C, Gao S, Zhang Z, Bo L. Classification of the botanical and geographical origins of Chinese honey based on 1H NMR profile with chemometrics. Food Res Int 2020; 137:109714. [PMID: 33233286 DOI: 10.1016/j.foodres.2020.109714] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 09/07/2020] [Accepted: 09/07/2020] [Indexed: 12/21/2022]
Abstract
In this paper, we report a newly developed non-target 1H NMR detection associated with chemometrics method to classify the botanical and geographical origins of the monofloral Chinese honey. 1H NMR tests of 218 monofloral honey samples of 8 classes (Acacia, Jujube, Linden, Longan, Orange, Rape, Sunflower, Vitex) collected in 2017-2019 across China were conducted under the optimal sample preparation conditions and NMR acquisition parameters. The whole profiles of NMR spectra instead of individual or partial signals from specific components were processed and extracted, then fed to SIMCA-P to classify the botanical and geographical origins through non-target statistical analysis. For the botanical origins, most of them could be classified clearly according to Principal Component Analysis (PCA) with both R2 and Q2 close to 1. Orthogonal Partial Least Squares Discrimination Analysis (OPLS-DA) model could classify the honey floral types successfully with R2Y and Q2 greater than 0.85. It is found that the integral bin for data extraction has no obvious influence on the classification. For the geographical origins, the classification at different geographical levels (providence and town) could be successfully distinguished by OPLS-DA model. The promising preliminary results with the geographical classification at 40 km level unambiguously demonstrate the application of this NMR-based multi-species non-targeted method for the honey authenticity. Successful result is obtained on a pilot prediction of the geographical classification. Comparing with the methods based on other techniques, the advantages of this reported one are less sample amount needed, simple preparation, short test time, and non-targeted multi-species detection.
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Affiliation(s)
- Jialin Zhang
- Agro-product Safety Research Center, Chinese Academy of Inspection and Quarantine, China
| | - Hui Chen
- Agro-product Safety Research Center, Chinese Academy of Inspection and Quarantine, China
| | - Chunlin Fan
- Agro-product Safety Research Center, Chinese Academy of Inspection and Quarantine, China
| | - Shuai Gao
- Agro-product Safety Research Center, Chinese Academy of Inspection and Quarantine, China
| | - Zijuan Zhang
- Agro-product Safety Research Center, Chinese Academy of Inspection and Quarantine, China.
| | - Lin Bo
- Agro-product Safety Research Center, Chinese Academy of Inspection and Quarantine, China
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Use of elemental profiles to verify geographical origin and botanical variety of Spanish honeys with a protected denomination of origin. Food Chem 2020; 342:128350. [PMID: 33092922 PMCID: PMC7930469 DOI: 10.1016/j.foodchem.2020.128350] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 10/06/2020] [Accepted: 10/07/2020] [Indexed: 11/24/2022]
Abstract
Honey with Protected Denomination of Origin (PDO) could be an attractive target for fraudsters. Elemental profiles by Energy Dispersive-X Ray Fluorescence were processed by multivariate methods to classify 183 PDO honeys produced in three regions of Spain (Liébana, Granada, Tenerife). Additional honey samples (18) produced in a fourth region without PDO (El Bierzo) separated well from the PDO clusters. The manganese content was a discriminant marker of Liébana PDO and El Bierzo, that could also be differentiated from each other. Within each region, distinct clusters revealed differences between dark vs light varieties, multi- vs uni-floral honey and producers of the same PDO. The developed models were validated with 131 samples produced outside the PDO regions and El Bierzo. The proposed classification approach could be implemented as a fast screening tool to support pollen analysis in honey authentication. The reduced number of observations in some light honey models affected their performance.
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Zhang X, Li X, Su M, Du J, Zhou H, Li X, Ye Z. A comparative UPLC-Q-TOF/MS-based metabolomics approach for distinguishing peach (Prunus persica (L.) Batsch) fruit cultivars with varying antioxidant activity. Food Res Int 2020; 137:109531. [PMID: 33233161 DOI: 10.1016/j.foodres.2020.109531] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 07/04/2020] [Accepted: 07/08/2020] [Indexed: 01/12/2023]
Abstract
Peaches (Prunus persica (L.) Batsch) are nutritionally and economically important and they are one of the most popular fruits consumed worldwide. Understanding metabolite-caused bioactivity differences among cultivars is essential for designing a peach with enhanced nutritional traits. In this study, we report an untargeted UPLC-Q-TOF/MS-based metabolomics approach for comprehensively discriminating between peaches with different antioxidant activities. Mature fruit from 40 peach cultivars were distinguished using principal component analysis and orthogonal partial least squares discrimination analysis. Seventeen differential metabolites were tentatively identified between peach cultivars with high and low antioxidant potency composite indices, and eight metabolites, including procyanidin C1, procyanidin trimer isomer 1, procyanidin trimer isomer 2, procyanidin B1, procyanidin B2, procyanidin B3, prunus inhibitor b, and phloridzin, were identified as marker compounds responsible for the discrimination of the cultivars base on potential antioxidant activity. Our study highlights the essence and predictive power of metabolomics for detecting small differences and for identifying potential marker metabolites based on their levels and composition in plants exhibiting varying bioactivities. Overall, the variations in the metabolites in peach pulp reflected the diversity in the peach germplasm, and these eight compounds are good candidate markers for future genetic breeding of peach fruit with enhanced antioxidant activity.
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Affiliation(s)
- Xianan Zhang
- Forestry and Fruit Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai 201403, PR China; Shanghai Key Laboratory of Protected Horticultural Technology, Shanghai 201403, PR China
| | - Xin Li
- Instrumental Analysis Center, Shanghai Jiao Tong University, Shanghai 200240, PR China
| | - Mingshen Su
- Forestry and Fruit Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai 201403, PR China; Shanghai Key Laboratory of Protected Horticultural Technology, Shanghai 201403, PR China
| | - Jihong Du
- Forestry and Fruit Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai 201403, PR China; Shanghai Key Laboratory of Protected Horticultural Technology, Shanghai 201403, PR China
| | - Huijuan Zhou
- Forestry and Fruit Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai 201403, PR China; Shanghai Key Laboratory of Protected Horticultural Technology, Shanghai 201403, PR China
| | - Xiongwei Li
- Forestry and Fruit Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai 201403, PR China; Shanghai Key Laboratory of Protected Horticultural Technology, Shanghai 201403, PR China
| | - Zhengwen Ye
- Forestry and Fruit Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai 201403, PR China; Shanghai Key Laboratory of Protected Horticultural Technology, Shanghai 201403, PR China.
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Creydt M, Fischer M. Food authentication in real life: How to link nontargeted approaches with routine analytics? Electrophoresis 2020; 41:1665-1679. [PMID: 32249434 DOI: 10.1002/elps.202000030] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 03/19/2020] [Accepted: 03/23/2020] [Indexed: 12/20/2022]
Abstract
In times of increasing globalization and the resulting complexity of trade flows, securing food quality is an increasing challenge. The development of analytical methods for checking the integrity and, thus, the safety of food is one of the central questions for actors from science, politics, and industry. Targeted methods, for the detection of a few selected analytes, still play the most important role in routine analysis. In the past 5 years, nontargeted methods that do not aim at individual analytes but on analyte profiles that are as comprehensive as possible have increasingly come into focus. Instead of investigating individual chemical structures, data patterns are collected, evaluated and, depending on the problem, fed into databases that can be used for further nontargeted approaches. Alternatively, individual markers can be extracted and transferred to targeted methods. Such an approach requires (i) the availability of authentic reference material, (ii) the corresponding high-resolution laboratory infrastructure, and (iii) extensive expertise in processing and storing very large amounts of data. Probably due to the requirements mentioned above, only a few methods have really established themselves in routine analysis. This review article focuses on the establishment of nontargeted methods in routine laboratories. Challenges are summarized and possible solutions are presented.
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Affiliation(s)
- Marina Creydt
- Hamburg School of Food Science, Institute of Food Chemistry, University of Hamburg, Hamburg, Germany
| | - Markus Fischer
- Hamburg School of Food Science, Institute of Food Chemistry, University of Hamburg, Hamburg, Germany
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