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Fakhlaei R, Selamat J, Abdull Razis AF, Sukor R, Ahmad S, Khatib A, Zou X. Development of a zebrafish model for toxicity evaluation of adulterated Apis mellifera honey. CHEMOSPHERE 2024; 356:141736. [PMID: 38554873 DOI: 10.1016/j.chemosphere.2024.141736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 03/09/2024] [Accepted: 03/15/2024] [Indexed: 04/02/2024]
Abstract
Since ancient times, honey has been used for medical purposes and the treatment of various disorders. As a high-quality food product, the honey industry is prone to fraud and adulteration. Moreover, limited experimental studies have investigated the impact of adulterated honey consumption using zebrafish as the animal model. The aims of this study were: (1) to calculate the lethal concentration (LC50) of acid-adulterated Apis mellifera honey on embryos, (2) to investigate the effect of pure and acid-adulterated A. mellifera honey on hatching rate (%) and heart rate of zebrafish (embryos and larvae), (3) to elucidate toxicology of selected adulterated honey based on lethal dose (LD50) using adult zebrafish and (4) to screen the metabolites profile of adulterated honey from blood serum of adult zebrafish. The result indicated the LC50 of 31.10 ± 1.63 (mg/ml) for pure A. mellifera honey, while acetic acid demonstrates the lowest LC50 (4.98 ± 0.06 mg/ml) among acid adulterants with the highest mortality rate at 96 hpf. The treatment of zebrafish embryos with adulterated A. mellifera honey significantly (p ≤ 0.05) increased the hatching rate (%) and decreased the heartbeat rate. Acute, prolong-acute, and sub-acute toxicology tests on adult zebrafish were conducted at a concentration of 7% w/w of acid adulterants. Furthermore, the blood serum metabolite profile of adulterated-honey-treated zebrafish was screened by LC-MS/MS analysis and three endogenous metabolites have been revealed: (1) Xanthotoxol or 8-Hydroxypsoralen, (2) 16-Oxoandrostenediol, and (3) 3,5-Dicaffeoyl-4-succinoylquinic acid. These results prove that employed honey adulterants cause mortality that contributes to higher toxicity. Moreover, this study introduces the zebrafish toxicity test as a new promising standard technique for the potential toxicity assessment of acid-adulterated honey in this study and hazardous food adulterants for future studies.
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Affiliation(s)
- Rafieh Fakhlaei
- School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd, 212013, Zhenjiang, Jiangsu, China; Food Safety and Food Integrity (FOSFI), Institute of Tropical Agriculture and Food Security, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia
| | - Jinap Selamat
- Department of Food Science, Faculty of Food Science and Technology, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia.
| | - Ahmad Faizal Abdull Razis
- Department of Food Science, Faculty of Food Science and Technology, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia; Natural Medicines and Products Research Laboratory, Universiti Putra Malaysia, Serdang, 43400, Selangor, Malaysia
| | - Rashidah Sukor
- Food Safety and Food Integrity (FOSFI), Institute of Tropical Agriculture and Food Security, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia; Department of Food Science, Faculty of Food Science and Technology, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia
| | - Syahida Ahmad
- Department of Biochemistry, Faculty of Biotechnology & Biomolecular Sciences, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia
| | - Alfi Khatib
- Department of Pharmaceutical Chemistry, Kulliyyah of Pharmacy, International Islamic University Malaysia, 25200, Kuantan, Pahang, Malaysia
| | - Xiaobo Zou
- School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd, 212013, Zhenjiang, Jiangsu, China
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Wu Q, Xu J, Yao L, Chen Q, Yao B, Zhang Y, Chen W. Accuracy and stability enhanced honey authenticity visual tracing method via false positive-eradicating PCR assisted nucleic acid-capturing lateral flow strip. Food Chem 2024; 435:137587. [PMID: 37778253 DOI: 10.1016/j.foodchem.2023.137587] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 08/23/2023] [Accepted: 09/22/2023] [Indexed: 10/03/2023]
Abstract
Honey authenticity guarantee is crucial for consumer health and fair-trading commerce. New visual false-positive-free molecular lateral flow strip (LFS), termed 5'-3' exonuclease activity -directed false positive-eradicating PCR assisted lateral flow strip (FPE-PCR-LFS) was developed. This FPE-PCR-LFS explored the availability of using a signal-probe as the mediator to integrate the efficient amplification module with visual LFS module. With the genomic DNA extracted from target honey, the designed signal probe would be hydrolyzed and exhausted by the 5'-3' exonuclease activity of Taq DNA polymerase in the amplification process. The hydrolyzed signal probe would not be recognized and capture on the T line with only C line of LFS, reflecting the authenticity of the tested honey. And as low as 0.5% authenticity can be accurately identified in commercial honey samples. Significantly, the false-positive-interference was successfully eradicated for the final visual results judgement, which would greatly widen the application of molecular PCR-LFS in various fields.
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Affiliation(s)
- Qian Wu
- Engineering Research Center of Bio-process, MOE, School of Food and Biological Engineering, Hefei University of Technology, Hefei 230009, PR China
| | - Jianguo Xu
- Engineering Research Center of Bio-process, MOE, School of Food and Biological Engineering, Hefei University of Technology, Hefei 230009, PR China
| | - Li Yao
- Engineering Research Center of Bio-process, MOE, School of Food and Biological Engineering, Hefei University of Technology, Hefei 230009, PR China; College of Chemistry and Food Engineering, Changsha University of Science & Technology, Changsha 410114, China
| | - Qi Chen
- Engineering Research Center of Bio-process, MOE, School of Food and Biological Engineering, Hefei University of Technology, Hefei 230009, PR China
| | - Bangben Yao
- Engineering Research Center of Bio-process, MOE, School of Food and Biological Engineering, Hefei University of Technology, Hefei 230009, PR China; Anhui Province Institute of Product Quality Supervision & Inspection, Hefei 230051, PR China
| | - Yan Zhang
- Key Laboratory of Special Food Supervision Technology for State Market Regulation, Hebei Food Inspection and Research Institute, Shijiazhuang 050227, PR China
| | - Wei Chen
- Engineering Research Center of Bio-process, MOE, School of Food and Biological Engineering, Hefei University of Technology, Hefei 230009, PR China.
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Calle JLP, Punta-Sánchez I, González-de-Peredo AV, Ruiz-Rodríguez A, Ferreiro-González M, Palma M. Rapid and Automated Method for Detecting and Quantifying Adulterations in High-Quality Honey Using Vis-NIRs in Combination with Machine Learning. Foods 2023; 12:2491. [PMID: 37444229 DOI: 10.3390/foods12132491] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 06/20/2023] [Accepted: 06/21/2023] [Indexed: 07/15/2023] Open
Abstract
Honey is one of the most adulterated foods, usually through the addition of sweeteners or low-cost honeys. This study presents a method based on visible near infrared spectroscopy (Vis-NIRs), in combination with machine learning (ML) algorithms, for the correct identification and quantification of adulterants in honey. Honey samples from two botanical origins (orange blossom and sunflower) were evaluated and adulterated with low-cost honey in different percentages (5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, and 50%). The results of the exploratory analysis showed a tendency to group the samples according to botanical origin, as well as the presence of adulteration. A supervised analysis was performed to detect the presence of adulterations. The best performance with 100% accuracy was achieved by support vector machines (SVM) and random forests (RF). A regression study was also carried out to quantify the percentage of adulteration. The best result was obtained by support vector regression (SVR) with a coefficient of determination (R2) of 0.991 and a root mean squared error (RMSE) of 1.894. These results demonstrate the potential of combining ML with spectroscopic data as a method for the automated quality control of honey.
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Affiliation(s)
- José Luis P Calle
- Department of Analytical Chemistry, Faculty of Sciences, University of Cadiz, Agrifood Campus of International Excellence (ceiA3), IVAGRO, 11510 Puerto Real, Spain
| | - Irene Punta-Sánchez
- Department of Analytical Chemistry, Faculty of Sciences, University of Cadiz, Agrifood Campus of International Excellence (ceiA3), IVAGRO, 11510 Puerto Real, Spain
| | - Ana Velasco González-de-Peredo
- Department of Analytical Chemistry, Faculty of Sciences, University of Cadiz, Agrifood Campus of International Excellence (ceiA3), IVAGRO, 11510 Puerto Real, Spain
| | - Ana Ruiz-Rodríguez
- Department of Analytical Chemistry, Faculty of Sciences, University of Cadiz, Agrifood Campus of International Excellence (ceiA3), IVAGRO, 11510 Puerto Real, Spain
| | - Marta Ferreiro-González
- Department of Analytical Chemistry, Faculty of Sciences, University of Cadiz, Agrifood Campus of International Excellence (ceiA3), IVAGRO, 11510 Puerto Real, Spain
| | - Miguel Palma
- Department of Analytical Chemistry, Faculty of Sciences, University of Cadiz, Agrifood Campus of International Excellence (ceiA3), IVAGRO, 11510 Puerto Real, Spain
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Tulu D, Aleme M, Mengistu G, Bogale A, Bezabeh A, Mendesil E. Melissopalynological analysis and floral spectra of Apis mellifera scutellata Lepeletier bees in different agroecologies of southwest Ethiopia. Heliyon 2023; 9:e16047. [PMID: 37215831 PMCID: PMC10199175 DOI: 10.1016/j.heliyon.2023.e16047] [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: 10/07/2022] [Revised: 04/17/2023] [Accepted: 05/03/2023] [Indexed: 05/24/2023] Open
Abstract
The availability of bee forage limits honeybee productivity and is very important for beekeepers. Therefore, the current study aimed to identify the major botanical resources of honeybee, A. mellifera scutellata, in Southwest Ethiopia. Between October 2019 and October 2020, 69 group discussions (8-12 beekeepers), field observations, and pollen analysis were used to collect data. A total of 72 honey samples were collected from five districts at different seasons for pollen analysis. Most of the honey samples tested (93.06%) were multifloral, while 6.94% were monofloral. Melissopalynological analysis indicated that Eucalyptus camaldulensis (52.02%) was the predominant pollen type and is considered monofloral honey. Terminalia spp. (25.96%), Guizotia spp. (17.80%), and Bidens spp. (17.61%) were secondary pollen types and classified as multifloral honey. Terminalia spp., Guizotia spp., Vernonia spp., Bidens ssp., Plantago spp., and E. camaldulensis were pollen types recorded in honey samples in all agroecologies. Beekeepers ranked Schefflera abyssinica, Vernonia amygdalina, and Cordia africana as the first source of pollen and nectar for honeybees in highland, midland, and lowland, respectively. Additionally, V. amygdalina, Coffea arabica, Croton macrostachyus, and C. africana were commonly observed bee flora in all agroecologies. Honey bee management, such as bee forage shortages, the occurrence of brood and swarming, varied significantly (P < 0.05) among different agroecologies. In the present study, 53 honeybee plants were identified as pollen and nectar sources for honeybees. Various herbs (41.50%), trees (30.20%), and shrubs (28.30%) played a major role in honey production. Thus, beekeeping should be integrated with vegetation conservation for livelihood improvement and food security. Furthermore, existing bee flora should be cultivated in areas to increase the harvesting of honeybee products and improve the apiculture industry.
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Affiliation(s)
- Dereje Tulu
- Ethiopian Institute of Agricultural Research, Tepi Agricultural Research Center, P.O. Box 34, Tepi, Ethiopia
| | - Melkam Aleme
- Ethiopian Institute of Agricultural Research, Tepi Agricultural Research Center, P.O. Box 34, Tepi, Ethiopia
| | - Gezahegn Mengistu
- Ethiopian Institute of Agricultural Research, Tepi Agricultural Research Center, P.O. Box 34, Tepi, Ethiopia
| | - Ararsa Bogale
- Ethiopian Institute of Agricultural Research, Tepi Agricultural Research Center, P.O. Box 34, Tepi, Ethiopia
| | - Amsalu Bezabeh
- Holeta National Bee Research Center, P.O. Box 22, Holeta, Ethiopia
| | - Esayas Mendesil
- Department of Horticulture and Plant Sciences, Jimma University College of Agriculture & Veterinary Medicine, P.O. Box 307, Jimma, Ethiopia
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Gulino F, Calà E, Cozzani C, Vaccari L, Oddone M, Aceto M. On the Traceability of Honey by Means of Lanthanide Distribution. Foods 2023; 12:foods12091803. [PMID: 37174340 PMCID: PMC10178145 DOI: 10.3390/foods12091803] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 04/24/2023] [Accepted: 04/25/2023] [Indexed: 05/15/2023] Open
Abstract
Honey is a natural food appreciated all over the world since antiquity due to its well-recognised beneficial properties. However, it is also considered among the most counterfeited foods. Therefore, analytical methods are currently being developed to allow the verifying of its geographic provenance and its botanical origin. Trace- and ultra-trace elements are usually exploited as chemical descriptors in authentication studies, as they allow the properties declared in the label to be verified. A different matter is to trace a food by means of traceability, that is, to find the link between a food and the soil in which this food originates. For traceability, it has been demonstrated in several studies that the lanthanides are particularly useful to find this link. In the present study, the traceability of the honey chain has been studied by means of ICP-MS and ICP-OES analysis, by comparing the lanthanide distributions of 17 different monofloral honey chains, each one composed of honey, flowers and soil in which such flowers grew. The results show that, while the fingerprint of soil, described by the lanthanide distribution, is transmitted unaltered from soil to flowers, a slight fractionation on the heavier lanthanides (from Dy to Lu) occurs in the passage from flowers to honey.
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Affiliation(s)
- Federica Gulino
- Dipartimento per lo Sviluppo Sostenibile e la Transizione Ecologica, Università degli Studi del Piemonte Orientale, Piazza S. Eusebio, 5, 13100 Vercelli, VC, Italy
| | - Elisa Calà
- Dipartimento per lo Sviluppo Sostenibile e la Transizione Ecologica, Università degli Studi del Piemonte Orientale, Piazza S. Eusebio, 5, 13100 Vercelli, VC, Italy
| | - Christian Cozzani
- Dipartimento per lo Sviluppo Sostenibile e la Transizione Ecologica, Università degli Studi del Piemonte Orientale, Piazza S. Eusebio, 5, 13100 Vercelli, VC, Italy
| | - Lorenzo Vaccari
- Dipartimento per lo Sviluppo Sostenibile e la Transizione Ecologica, Università degli Studi del Piemonte Orientale, Piazza S. Eusebio, 5, 13100 Vercelli, VC, Italy
| | - Matteo Oddone
- Thermo Fisher Scientific, Strada Rivoltana, 20090 Rodano, MI, Italy
| | - Maurizio Aceto
- Dipartimento per lo Sviluppo Sostenibile e la Transizione Ecologica, Università degli Studi del Piemonte Orientale, Piazza S. Eusebio, 5, 13100 Vercelli, VC, Italy
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Determination of Possible Adulteration and Quality Assessment in Commercial Honey. Foods 2023; 12:foods12030523. [PMID: 36766052 PMCID: PMC9914500 DOI: 10.3390/foods12030523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 01/18/2023] [Accepted: 01/19/2023] [Indexed: 01/26/2023] Open
Abstract
This study aims to predict several quality traits in commercial honey samples simultaneously and to reveal possible honey adulteration using a field-deployable portable infrared spectrometer without any sample preparation. A total of one hundred and forty-seven commercial honey samples were purchased from local and online markets in Turkey and the United States of America (USA), and their soluble solids (°Brix), pH, free acidity, moisture, water activity (aw), glucose, fructose, sucrose, and hydroxymethyl furfural (HMF) contents were determined using reference methods. The HMF (n = 11 samples) and sucrose (n = 21) concentrations were higher than the regulatory limits in some tested samples. The exceeding HMF content may imply temperature abuse during storage and prolonged storing. On the other hand, high sucrose content may indicate possible adulteration with commercial sweeteners. Therefore, soft independent modeling of class analogies (SIMCA) analysis was conducted to reveal this potential sweetener adulteration in the samples, and the SIMCA model was able to identify all the flagged samples. The suggested FT-IR technique may be helpful in regulatory bodies in determining honey authenticity issues as well as assessing the quality characteristics of honey samples in a shorter period and at a lower cost.
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Momeny M, Neshat AA, Jahanbakhshi A, Mahmoudi M, Ampatzidis Y, Radeva P. Grading and fraud detection of saffron via learning-to-augment incorporated Inception-v4 CNN. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.109554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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LC-HRMS-Based Non-Targeted Metabolomics for the Assessment of Honey Adulteration with Sugar Syrups: A Preliminary Study. Metabolites 2022; 12:metabo12100985. [PMID: 36295887 PMCID: PMC9607529 DOI: 10.3390/metabo12100985] [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: 09/16/2022] [Revised: 10/11/2022] [Accepted: 10/15/2022] [Indexed: 11/17/2022] Open
Abstract
Honey is a natural product that is in great demand and has a relatively high price, thus making it one of the most common targets of economically motivated adulteration. Its adulteration can be obtained by adding cheaper honey or sugar syrups or by overfeeding honeybees with sugar syrups. Adulteration techniques are constantly evolving and advanced techniques and instruments are required for its detection. We used non-targeted metabolomics to underscore potential markers of honey adulteration with sugar syrups. The metabolomic profiles of unadulterated honeys and sugar beet, corn and wheat syrups were obtained using hydrophilic interaction liquid chromatography high-resolution mass spectrometry (LC-HRMS). The potential markers have been selected after data processing. Fortified honey (5%, 10% and 20%), honey obtained from overfeeding, and 58 commercial honeys were analyzed. One potential marker appeared with a specific signal for syrups and not for honey. This targeted analysis showed a linear trend in fortified honeys with a calculated limit of quantification around 5% of fortification.
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Jagtap S, Trollman H, Trollman F, Garcia-Garcia G, Parra-López C, Duong L, Martindale W, Munekata PES, Lorenzo JM, Hdaifeh A, Hassoun A, Salonitis K, Afy-Shararah M. The Russia-Ukraine Conflict: Its Implications for the Global Food Supply Chains. Foods 2022; 11:foods11142098. [PMID: 35885340 PMCID: PMC9318935 DOI: 10.3390/foods11142098] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 06/29/2022] [Accepted: 07/08/2022] [Indexed: 11/16/2022] Open
Abstract
Food is one of the most traded goods, and the conflict in Ukraine, one of the European breadbaskets, has triggered a significant additional disruption in the global food supply chains after the COVID-19 impact. The disruption to food output, supply chains, availability, and affordability could have a long-standing impact. As a result, the availability and supply of a wide range of food raw materials and finished food products are under threat, and global markets have seen recent increases in food prices. Furthermore, the Russian-Ukrainian conflict has adversely affected food supply chains, with significant effects on production, sourcing, manufacturing, processing, logistics, and significant shifts in demand between nations reliant on imports from Ukraine. This paper aims to analyze the impacts of the conflict between Russia and Ukraine on the effectiveness and responsiveness of the global food supply chains. A PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach, including grey literature, was deployed to investigate six key areas of the food supply chains that would be impacted most due to the ongoing war. Findings include solutions and strategies to mitigate supply chain impacts such as alternative food raw materials, suppliers and supply chain partners supported by technological innovations to ensure food safety and quality in warlike situations.
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Affiliation(s)
- Sandeep Jagtap
- Sustainable Manufacturing Systems Centre, School of Aerospace, Transport & Manufacturing, Cranfield University, Cranfield MK43 0AL, UK; (K.S.); (M.A.-S.)
- Correspondence:
| | - Hana Trollman
- Department of Work, Employment, Management and Organisations, School of Business, The University of Leicester, University Road, Leicester LE1 7RH, UK;
| | - Frank Trollman
- Glenfield Hospital, University Hospitals of Leicester, NHS Trust, Leicester LE3 9QP, UK;
| | - Guillermo Garcia-Garcia
- Department of Agrifood System Economics, Centre ‘Camino de Purchil’, Institute of Agricultural and Fisheries Research and Training (IFAPA), 18080 Granada, Spain; (G.G.-G.); (C.P.-L.)
| | - Carlos Parra-López
- Department of Agrifood System Economics, Centre ‘Camino de Purchil’, Institute of Agricultural and Fisheries Research and Training (IFAPA), 18080 Granada, Spain; (G.G.-G.); (C.P.-L.)
| | - Linh Duong
- Faculty of Business and Law, The University of the West of England, Bristol BS16 1QY, UK;
| | - Wayne Martindale
- National Centre for Food Manufacturing, University of Lincoln, Holbeach PE12 7PT, UK;
| | - Paulo E. S. Munekata
- Centro Tecnológico de la Carne de Galicia, Rúa Galicia n 4, Parque Tecnológico de Galicia, San Cibrao das Viñas, 32900 Ourense, Spain; (P.E.S.M.); (J.M.L.)
| | - Jose M. Lorenzo
- Centro Tecnológico de la Carne de Galicia, Rúa Galicia n 4, Parque Tecnológico de Galicia, San Cibrao das Viñas, 32900 Ourense, Spain; (P.E.S.M.); (J.M.L.)
- Area de Tecnoloxía dos Alimentos, Facultade de Ciencias, Universidade de Vigo, 32004 Ourense, Spain
| | - Ammar Hdaifeh
- Agri-Food Sustainability Assessment, University de Lorraine, 54600 Nancy, France;
| | - Abdo Hassoun
- Sustainable AgriFoodTech Innovation & Research (SAFIR), 62000 Arras, France;
- Syrian Academic Expertise (SAE), Gaziantep 27200, Turkey
| | - Konstantinos Salonitis
- Sustainable Manufacturing Systems Centre, School of Aerospace, Transport & Manufacturing, Cranfield University, Cranfield MK43 0AL, UK; (K.S.); (M.A.-S.)
| | - Mohamed Afy-Shararah
- Sustainable Manufacturing Systems Centre, School of Aerospace, Transport & Manufacturing, Cranfield University, Cranfield MK43 0AL, UK; (K.S.); (M.A.-S.)
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