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Sharma R, Nath PC, Lodh BK, Mukherjee J, Mahata N, Gopikrishna K, Tiwari ON, Bhunia B. Rapid and sensitive approaches for detecting food fraud: A review on prospects and challenges. Food Chem 2024; 454:139817. [PMID: 38805929 DOI: 10.1016/j.foodchem.2024.139817] [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: 11/25/2023] [Revised: 05/13/2024] [Accepted: 05/22/2024] [Indexed: 05/30/2024]
Abstract
Precise and reliable analytical techniques are required to guarantee food quality in light of the expanding concerns regarding food safety and quality. Because traditional procedures are expensive and time-consuming, quick food control techniques are required to ensure product quality. Various analytical techniques are used to identify and detect food fraud, including spectroscopy, chromatography, DNA barcoding, and inotrope ratio mass spectrometry (IRMS). Due to its quick findings, simplicity of use, high throughput, affordability, and non-destructive evaluations of numerous food matrices, NI spectroscopy and hyperspectral imaging are financially preferred in the food business. The applicability of this technology has increased with the development of chemometric techniques and near-infrared spectroscopy-based instruments. The current research also discusses the use of several multivariate analytical techniques in identifying food fraud, such as principal component analysis, partial least squares, cluster analysis, multivariate curve resolutions, and artificial intelligence.
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Affiliation(s)
- Ramesh Sharma
- Bioproducts Processing Research Laboratory (BPRL), Department of Bio Engineering, National Institute of Technology, Agartala 799046, India; Department of Food Technology, Sri Shakthi Institute of Engineering and Technology, Coimbatore, Tamil Nadu-641062, India.
| | - Pinku Chandra Nath
- Bioproducts Processing Research Laboratory (BPRL), Department of Bio Engineering, National Institute of Technology, Agartala 799046, India.
| | - Bibhab Kumar Lodh
- Department of Chemical Engineering, National Institute of Technology, Agartala-799046, India.
| | - Jayanti Mukherjee
- Department of Pharmaceutical Chemistry, CMR College of Pharmacy, Hyderabad- 501401, Telangana, India.
| | - Nibedita Mahata
- Department of Biotechnology, National Institute of Technology Durgapur, Durgapur-713209.
| | - Konga Gopikrishna
- SEED Division, Department of Science and Technology, New Delhi, 110016, India.
| | - Onkar Nath Tiwari
- Centre for Conservation and Utilisation of Blue Green Algae (CCUBGA), Division of Microbiology, ICAR-Indian Agricultural Research Institute (IARI), New Delhi, 110012, India.
| | - Biswanath Bhunia
- Bioproducts Processing Research Laboratory (BPRL), Department of Bio Engineering, National Institute of Technology, Agartala 799046, India.
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Li MX, Shi YB, Zhang JB, Wan X, Fang J, Wu Y, Fu R, Li Y, Li L, Su LL, Ji D, Lu TL, Bian ZH. Rapid evaluation of Ziziphi Spinosae Semen and its adulterants based on the combination of FT-NIR and multivariate algorithms. Food Chem X 2023; 20:101022. [PMID: 38144802 PMCID: PMC10740088 DOI: 10.1016/j.fochx.2023.101022] [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: 09/07/2023] [Revised: 11/09/2023] [Accepted: 11/19/2023] [Indexed: 12/26/2023] Open
Abstract
Ziziphi Spinosae Semen (ZSS) is a valued seed renowned for its sedative and sleep-enhancing properties. However, the price increase has been accompanied by adulteration. In this study, chromaticity analysis and Fourier transform near-infrared (FT-NIR) combined with multivariate algorithms were employed to identify the adulteration and quantitatively predict the adulteration ratio. The findings suggested that the utilization of chromaticity extractor was insufficient for identification of adulteration ratio. The raw spectrum of ZMS and HAS adulterants extracted by FT-NIR was processed by SNV + CARS and 1d + SG + ICO respectively, the average accuracy of machine learning classification model was improved from 77.06 % to 97.58 %. Furthermore, the R2 values of the calibration and prediction set of the two quantitative prediction regression models of adulteration ratio are greater than 0.99, demonstrating excellent linearity and predictive accuracy. Overall, this study demonstrated that FT-NIR combined with multivariate algorithms provided a significant approach to addressing the growing issue of ZSS adulteration.
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Affiliation(s)
- Ming-xuan Li
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Ya-bo Shi
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Jiu-ba Zhang
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Xin Wan
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Jun Fang
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Yi Wu
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Rao Fu
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Yu Li
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Lin Li
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Lian-lin Su
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - De Ji
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Tu-lin Lu
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Zhen-hua Bian
- Department of Pharmacy, Wuxi TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Wuxi, 214071, China
- Jiangsu CM Clinical Innovation Center of Degenerative Bone & Joint Disease, Wuxi TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Wuxi, 214071, China
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3
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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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4
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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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Razavi R, Kenari RE. Ultraviolet-visible spectroscopy combined with machine learning as a rapid detection method to the predict adulteration of honey. Heliyon 2023; 9:e20973. [PMID: 37886742 PMCID: PMC10597822 DOI: 10.1016/j.heliyon.2023.e20973] [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: 01/28/2023] [Revised: 10/10/2023] [Accepted: 10/12/2023] [Indexed: 10/28/2023] Open
Abstract
Honey is often adulterated with inexpensive and artificial sweeteners. To overcome the time-consuming honey adulteration tests, which require precision, chemicals, and sample preparation, it is needful to develop trustworthy analytical methods to assure its authenticity. In the present study, the potential of ultraviolet-visible spectroscopy (UV-Vis) in predicting the sucrose content was evaluated by using Support Vector Regression (SVR) and Partial Least Square Regression (PLSR). To predict the sucrose content based on diagnostic wavelengths, a Point Spectro Transfer Function (PSTF) was evaluated using Multiple Linear Regression (MLR). For this purpose, the spectra of authentic (n = 12), commercial (n = 12), and adulterated (n = 16) honey samples were recorded. Four distinguished wavelengths from correlation analysis between sucrose content and spectra absorption were 216, 280, 316, and 603 nm. The SVR performed better calibration model than the PLSR estimations (RMSE = 0.97, and R2 = 0.98). The predictive models result revealed that both models had high accuracy for the sucrose content estimation. This study proved that UV-Vis spectroscopy provides an economical alternative for the rapid quantification of adulterated honey samples with sucrose.
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Affiliation(s)
- Razie Razavi
- Department of Food Science and Technology, Sari Agricultural Sciences and Natural Resources University, Sari, Mazandaran, Iran, Postal code: 48181-68984
| | - Reza Esmaeilzadeh Kenari
- Department of Food Science and Technology, Sari Agricultural Sciences and Natural Resources University, Sari, Mazandaran, Iran, Postal code: 48181-68984
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6
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Cui C, Xia M, Chen J, Shi B, Peng C, Cai H, Jin L, Hou R. 1H NMR-based metabolomics combined with chemometrics to detect edible oil adulteration in huajiao (Zanthoxylum bungeanum Maxim.). Food Chem 2023; 423:136305. [PMID: 37178597 DOI: 10.1016/j.foodchem.2023.136305] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 04/29/2023] [Accepted: 05/01/2023] [Indexed: 05/15/2023]
Abstract
Huajiao is a highly valued spice that is susceptible to fraudulent adulteration, particularly the addition of edible oils to increase weight and improve color. Nuclear magnetic resonance (1H NMR) and chemometrics were used to analyze 120 huajiao samples adulterated with different types and levels of edible oils. Using untargeted data and partial least squares-discriminant analysis (PLS-DA), the discrimination rate between types of adulteration reached 100% accuracy, and the R2 value of the prediction set for the level of adulteration using the targeted analysis dataset combined with PLS-regression methods reached 0.99. Triacylglycerols, major components of edible oils, were identified as a marker of adulteration through the variable importance in projection of the PLS-regression. A quantitative method based on the sn-3 triacylglycerol signal was developed that can achieve a detection limit of 0.11%. Testing of 28 market samples showed adulteration with various edible oils, with adulteration rates ranging from 0.96% to 4.41%.
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Affiliation(s)
- Chuanjian Cui
- State Key Laboratory of Tea Plant Biology and Utilization, School of Tea and Food Science & Technology, Anhui Agricultural University, Hefei 230036, China
| | - Mingyue Xia
- State Key Laboratory of Tea Plant Biology and Utilization, School of Tea and Food Science & Technology, Anhui Agricultural University, Hefei 230036, China
| | | | - Biwen Shi
- Qiaqia Food Co., Ltd., Hefei 230601, China
| | - Chuanyi Peng
- State Key Laboratory of Tea Plant Biology and Utilization, School of Tea and Food Science & Technology, Anhui Agricultural University, Hefei 230036, China
| | - Huimei Cai
- State Key Laboratory of Tea Plant Biology and Utilization, School of Tea and Food Science & Technology, Anhui Agricultural University, Hefei 230036, China
| | - Long Jin
- Qiaqia Food Co., Ltd., Hefei 230601, China.
| | - Ruyan Hou
- State Key Laboratory of Tea Plant Biology and Utilization, School of Tea and Food Science & Technology, Anhui Agricultural University, Hefei 230036, China.
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7
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Urbas AA, Corbett CA, Mazzola EP. NMR in forensics. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2023; 61:59-65. [PMID: 36114596 DOI: 10.1002/mrc.5312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 09/06/2022] [Accepted: 09/12/2022] [Indexed: 06/15/2023]
Affiliation(s)
- Aaron A Urbas
- National Institute of Standards and Technology, Gaithersburg, Maryland, USA
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8
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NMR-Based Characterization of Citrus Tacle Juice and Low-Level NMR and UV-Vis Data Fusion for Monitoring Its Fractions from Membrane-Based Operations. Antioxidants (Basel) 2022; 12:antiox12010002. [PMID: 36670864 PMCID: PMC9854473 DOI: 10.3390/antiox12010002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 12/07/2022] [Accepted: 12/16/2022] [Indexed: 12/24/2022] Open
Abstract
Tacle is a citrus variety which recently gained further interest due to its antioxidant and biological properties. This study suggests using Nuclear Magnetic Resonance (NMR) imaging to characterize Tacle juice's metabolic composition as it is intimately linked to its quality. First, polar and apolar solvent systems were used to identify a significant fraction of the Tacle metabolome. Furthermore, the antioxidant capacity and the total content of flavonoids, polyphenols and β-carotene in the juice were investigated with UV-Visible spectroscopy. Tacle juice was clarified and fractionated by ultrafiltration (UF) and nanofiltration (NF) membranes in order to recover and purify its bioactive principles. Finally, the second part of this work sheds light on the spectrophotometric assays and 1H-NMR spectra of fractions coming from membrane operations coupled with a multivariate data analysis technique, PCA, to explore the impact of UF and NF processes on the metabolic profile of the juice.
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9
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Yan S, Wang X, Zhao H, Lu H, Tian W, Wu L, Xue X. Metabolomics-based screening and chemically identifying abundant stachydrine as quality characteristic of rare Leucosceptrum canum Smith honey. J Food Compost Anal 2022. [DOI: 10.1016/j.jfca.2022.104759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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10
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Sobolev AP, Ingallina C, Spano M, Di Matteo G, Mannina L. NMR-Based Approaches in the Study of Foods. Molecules 2022; 27:7906. [PMID: 36432006 PMCID: PMC9697393 DOI: 10.3390/molecules27227906] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 11/07/2022] [Accepted: 11/14/2022] [Indexed: 11/17/2022] Open
Abstract
In this review, the three different NMR-based approaches usually used to study foodstuffs are described, reporting specific examples. The first approach starts with the food of interest that can be investigated using different complementary NMR methodologies to obtain a comprehensive picture of food composition and structure; another approach starts with the specific problem related to a given food (frauds, safety, traceability, geographical and botanical origin, farming methods, food processing, maturation and ageing, etc.) that can be addressed by choosing the most suitable NMR methodology; finally, it is possible to start from a single NMR methodology, developing a broad range of applications to tackle common food-related challenges and different aspects related to foods.
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Affiliation(s)
- Anatoly P. Sobolev
- Magnetic Resonance Laboratory “Segre-Capitani”, Institute for Biological Systems, CNR, Via Salaria, Km 29.300, 00015 Monterotondo, Italy
| | - Cinzia Ingallina
- Laboratory of Food Chemistry, Department of Chemistry and Technology of Drugs, Sapienza University of Rome, P.le Aldo Moro 5, 00185 Rome, Italy
| | - Mattia Spano
- Laboratory of Food Chemistry, Department of Chemistry and Technology of Drugs, Sapienza University of Rome, P.le Aldo Moro 5, 00185 Rome, Italy
| | - Giacomo Di Matteo
- Laboratory of Food Chemistry, Department of Chemistry and Technology of Drugs, Sapienza University of Rome, P.le Aldo Moro 5, 00185 Rome, Italy
| | - Luisa Mannina
- Laboratory of Food Chemistry, Department of Chemistry and Technology of Drugs, Sapienza University of Rome, P.le Aldo Moro 5, 00185 Rome, Italy
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Vit P, van der Meulen J, Diaz M, Pedro SR, Esperança I, Zakaria R, Beckh G, Maza F, Meccia G, Engel MS. Impact of genus ( Geotrigona, Melipona, Scaptotrigona) in the targeted 1H-NMR organic profile, and authenticity test by interphase emulsion of honey processed in cerumen pots by stingless bees in Ecuador. Curr Res Food Sci 2022; 6:100386. [PMID: 36846470 PMCID: PMC9947262 DOI: 10.1016/j.crfs.2022.11.005] [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: 12/30/2021] [Revised: 09/08/2022] [Accepted: 11/02/2022] [Indexed: 11/13/2022] Open
Abstract
The biodiversity of Ecuadorian stingless bees is almost 200 species. Traditional pot-honey harvest in Ecuador is mostly done from nests of the three genera selected here Geotrigona Moure, 1943, Melipona Illiger, 1806, and Scaptotrigona Moure, 1942. The 20 pot-honey samples collected from cerumen pots and three ethnic honeys "abeja de tierra", "bermejo", and "cushillomishki" were analyzed for qualitative and quantitative targeted 1H-NMR honey profiling, and for the Honey Authenticity Test by Interphase Emulsion (HATIE). Extensive data of targeted organic compounds (41 parameters) were identified, quantified, and described. The three honey types were compared by ANOVA. Amino acids, ethanol, hydroxymethylfurfural, aliphatic organic acids, sugars, and markers of botanical origin. The number of phases observed with the HATIE were one in Scaptotrigona and three in Geotrigona and Melipona honeys. Acetic acid (19.60 ± 1.45 g/kg) and lactic acid (24.30 ± 1.65 g/kg) were particularly high in Geotrigona honey (in contrast to 1.3 g/kg acetic acid and 1.6 g/kg lactic acid in Melipona and Scaptotrigona), and with the lowest fructose + glucose (18.39 ± 1.68) g/100g honey compared to Melipona (52.87 ± 1.75) and Scaptotrigona (52.17 ± 0.60). Three local honeys were tested using PCA (Principal Component Analysis), two were assigned with a correct declared bee origin, but "bermejo" was not a Melipona and grouped with the Scaptotrigona cluster. However after HCA (Hierarchical Cluster Analysis) the three honeys were positioned in the Melipona-Scaptotrigona cluster. This research supports targeted 1H-NMR-based profiling of pot-honey metabolomics approach for multi-parameter visualization of organic compounds, as well as descriptive and pertained multivariate statistics (HCA and PCA) to discriminate the stingless bee genus in a set of Geotrigona, Melipona and Scaptotrigona honey types. The NMR characterization of Ecuadorian honey produced by stingless bees emphasizes the need for regulatory norms. A final note on stingless bee markers in pot-honey metabolites which should be screened for those that may extract phylogenetic signals from nutritional traits of honey. Scaptotrigona vitorum honey revealed biosurfactant activity in the HATIE, originating a fingerprint Honey Biosurfactant Test (HBT) for the genus in this set of pot-honeys.
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Affiliation(s)
- Patricia Vit
- Food Science Department, Faculty of Pharmacy and Bioanalysis, Universidad de Los Andes, Mérida, 5101, Venezuela
| | | | - Maria Diaz
- Quality Services International GmbH, 28199, Bremen, Germany
| | - Silvia R.M. Pedro
- Biology Department, Universidade de São Paulo, Ribeirão Preto, Brazil
| | - Isabelle Esperança
- Institute of Chemistry, Universidad Federal de Rio de Janeiro, Rio de Janeiro, RJ, 21945970, Brazil
| | - Rahimah Zakaria
- Department of Physiology, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Gudrun Beckh
- Quality Services International GmbH, 28199, Bremen, Germany
| | - Favian Maza
- Faculty of Agricultural and Livestock Sciences, Universidad Técnica de Machala, Machala, El Oro province, Ecuador
| | - Gina Meccia
- Research Institute, Faculty of Pharmacy and Bioanalysis, Universidad de Los Andes, Mérida 5101, Venezuela
| | - Michael S. Engel
- Division of Entomology, Natural History Museum, Department of Ecology & Evolutionary Biology, 1501 Crestline Drive-Suite 140, University of Kansas, Lawrence, KS, USA
- Division of Invertebrate Zoology, American Museum of Natural History, Central Park West at 79th Street, New York, NY, 10024, USA
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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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13
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Classification of Polish Natural Bee Honeys Based on Their Chemical Composition. Molecules 2022; 27:molecules27154844. [PMID: 35956789 PMCID: PMC9369904 DOI: 10.3390/molecules27154844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 07/20/2022] [Accepted: 07/27/2022] [Indexed: 12/04/2022] Open
Abstract
The targeted quantitative NMR (qNMR) approach is a powerful analytical tool, which can be applied to classify and/or determine the authenticity of honey samples. In our study, this technique was used to determine the chemical profiles of different types of Polish honey samples, featured by variable contents of main sugars, free amino acids, and 5-(hydroxymethyl)furfural. One-way analysis of variance (ANOVA) was performed on concentrations of selected compounds to determine significant differences in their levels between all types of honey. For pattern recognition, principal component analysis (PCA) was conducted and good separations between all honey samples were obtained. The results of present studies allow the differentiation of honey samples based on the content of sucrose, glucose, and fructose, as well as amino acids such as tyrosine, phenylalanine, proline, and alanine. Our results indicated that the combination of qNMR with chemometric analysis may serve as a supplementary tool in specifying honeys.
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Qualitative and Quantitative Detection of Monofloral, Polyfloral, and Honeydew Honeys Adulteration by Employing Mid-Infrared Spectroscopy and Chemometrics. FOOD ANAL METHOD 2022. [DOI: 10.1007/s12161-022-02266-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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15
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McDevitt JC, Gupta RA, Dickinson SG, Martin PL, Rieuthavorn J, Freund A, Pizzorno MC, Capaldi EA, Rovnyak D. Methodology for Single Bee and Bee Brain 1H-NMR Metabolomics. Metabolites 2021; 11:metabo11120864. [PMID: 34940622 PMCID: PMC8704342 DOI: 10.3390/metabo11120864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 12/07/2021] [Accepted: 12/07/2021] [Indexed: 11/16/2022] Open
Abstract
The feasibility of metabolomic 1H NMR spectroscopy is demonstrated for its potential to help unravel the complex factors that are impacting honeybee health and behavior. Targeted and non-targeted 1H NMR metabolic profiles of liquid and tissue samples of organisms could provide information on the pathology of infections and on environmentally induced stresses. This work reports on establishing extraction methods for NMR metabolic characterization of Apis mellifera, the European honeybee, describes the currently assignable aqueous metabolome, and gives examples of diverse samples (brain, head, body, whole bee) and biologically meaningful metabolic variation (drone, forager, day old, deformed wing virus). Both high-field (600 MHz) and low-field (80 MHz) methods are applicable, and 1H NMR can observe a useful subset of the metabolome of single bees using accessible NMR instrumentation (600 MHz, inverse room temperature probe) in order to avoid pooling several bees. Metabolite levels and changes can be measured by NMR in the bee brain, where dysregulation of metabolic processes has been implicated in colony collapse. For a targeted study, the ability to recover 10-hydroxy-2-decenoic acid in mandibular glands is shown, as well as markers of interest in the bee brain such as GABA (4-aminobutyrate), proline, and arginine. The findings here support the growing use of 1H NMR more broadly in bees, native pollinators, and insects.
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Affiliation(s)
- Jayne C. McDevitt
- Department of Chemistry, Bucknell University, 1 Dent Drive, Lewisburg, PA 17837, USA; (J.C.M.); (R.A.G.); (S.G.D.); (P.L.M.)
| | - Riju A. Gupta
- Department of Chemistry, Bucknell University, 1 Dent Drive, Lewisburg, PA 17837, USA; (J.C.M.); (R.A.G.); (S.G.D.); (P.L.M.)
| | - Sydney G. Dickinson
- Department of Chemistry, Bucknell University, 1 Dent Drive, Lewisburg, PA 17837, USA; (J.C.M.); (R.A.G.); (S.G.D.); (P.L.M.)
| | - Phillip L. Martin
- Department of Chemistry, Bucknell University, 1 Dent Drive, Lewisburg, PA 17837, USA; (J.C.M.); (R.A.G.); (S.G.D.); (P.L.M.)
| | - Jean Rieuthavorn
- Department of Biology, Bucknell University, 1 Dent Drive, Lewisburg, PA 17837, USA; (J.R.); (M.C.P.); (E.A.C.)
| | - Amy Freund
- Bruker Biospin, 15 Fortune Drive, Billerica, MA 01821, USA;
| | - Marie C. Pizzorno
- Department of Biology, Bucknell University, 1 Dent Drive, Lewisburg, PA 17837, USA; (J.R.); (M.C.P.); (E.A.C.)
| | - Elizabeth A. Capaldi
- Department of Biology, Bucknell University, 1 Dent Drive, Lewisburg, PA 17837, USA; (J.R.); (M.C.P.); (E.A.C.)
- Program in Animal Behavior, Bucknell University, 1 Dent Drive, Lewisburg, PA 17837, USA
| | - David Rovnyak
- Department of Chemistry, Bucknell University, 1 Dent Drive, Lewisburg, PA 17837, USA; (J.C.M.); (R.A.G.); (S.G.D.); (P.L.M.)
- Correspondence:
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