Occurrence of aflatoxins in nuts and peanut butter imported to UAE

Osaili, Tareq M.; Odeh, Wael A.M. Bani; Ayoubi, Manar Al; Ali, Ahmed A.S.A. Al; Sallagi, Maryam S. Al; Obaid, Reyad S.; Garimella, Vaidehi; Bakhit, Fatema Saeed Bin; Holley, Richard A.; Darra, Nada El

doi:10.1016/j.heliyon.2023.e14530

Cited by 5 publications

(2 citation statements)

References 28 publications

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“…The increased fungal development in peanuts seen during a study in India was partially caused by the predominance of fabric packaging. Fabrics are not airtight, exposing nuts or other foods to moisture that can encourage the growth of mycotoxigenic fungi (Osaili et al 2023 ). In addition, when comparing samples from different parts of the world, samples from Asia had the highest prevalence of AFs.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of ELISA and immunoaffinity fluorometric analytical tools of four mycotoxins in various food categories

Boshra,

El-Housseiny,

Farag

et al. 2023

AMB Expr

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Mycotoxins (MTs) are secondary toxic metabolites that can contaminate food, impacting quality and safety, leading to various negative health effects and serious pathological consequences conferring urgent need to evaluate and validate the currently standard methods used in their analysis. Therefore, this study was aimed to validate ELISA and VICAM immunoaffinity fluorometric, the two common methods used to monitor the level of MTs according to the Egyptian Organization for Standardization and Quality Control. A total of 246 food samples were collected and tested for Aflatoxins (196 samples), Ochratoxin A (139), Zearalenone (70), and Deoxynivalenol (100) using both analytical methods. Results showed that aflatoxins exceeded limits in 42.9, 100, and 13.3% of oily seeds, dried fruits, and chili and spices, respectively. For ochratoxin A, 3.9% of Gramineae and 8% of spices and chili (locally sourced) exceeded the limits, while 17.6% of imported pasta and noodles exceeded the limits for deoxynivalenol. Significant differences for the aflatoxins and ochratoxin A detection among different categories of chocolate, dried fruits, and oily seeds (p-value < 0.05). No zearalenone contamination was detected in the exported, imported, and locally sourced categories. No deoxynivalenol contamination was detected in the tested Gramineae category. In contrast, for pasta and noodles, the imported samples exhibited the highest contamination rate (above the upper limit of 750 µg/kg) with 17.6% of the samples testing positive for deoxynivalenol with no significant difference among different sample categories of Gramineae, pasta, and noodles (p-value > 0.05). In conclusion, our study found no significant differences between the ELISA and immunoaffinity fluorometric analysis in the detection of the respective MTs in various food categories and therefore, they can substitute each other whenever necessary. However, significant differences were observed among different food categories, particularly the local and imported ones, highlighting the urgent need for strict and appropriate control measures to minimize the risk of MTs adverse effects.

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Section: Discussionmentioning

confidence: 99%

Evaluation of ELISA and immunoaffinity fluorometric analytical tools of four mycotoxins in various food categories

Boshra,

El-Housseiny,

Farag

et al. 2023

AMB Expr

View full text Add to dashboard Cite

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“…However, several challenges have been identified in relation to the export of cocoa such as the reduction in the quality due to the risk of mycotoxins [15]. The detection of aflatoxin was observed to currently rely on the application of chemical approaches involving high costs, destructive processes, sophisticated equipment, and labor expertise [16] such as ELISA [17], HPLC [18], and LCMS [19]. Another method is computer vision which involves utilizing different image acquisition technologies such as Color imaging [20], Near-infrared (NIR) Spectroscopy [21][22], Mid-infrared (MIR) Spectroscopy [23][24], Near-infrared (NIR) Hyperspectral Imaging [25][26], and even X-Ray Imaging [27] to detect mycotoxin.…”

Section: Introductionmentioning

confidence: 99%

The Classification of Aflatoxin Contamination Level in Cocoa Beans using Fluorescence Imaging and Deep learning

Sadimantara,

Argo,

Sucipto

et al. 2024

Journal of Robotics and Control

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Aflatoxin contamination in cacao is a significant problem in terms of trade losses and health effects. This calls for the need for a non-invasive, precise, and effective detection strategy. This research contribution is to determine the best deep-learning model to classify the aflatoxin contamination level in cocoa beans based on fluorescence images and deep learning to improve performance in the classification. The process involved inoculating and incubating Aspergillus flavus (6mL/100g) to obtain aflatoxin-contaminated cocoa beans for 7 days during the incubation period. Liquid Mass Chromatography (LCMS) was used to quantify the aflatoxin in order to categorize the images into different levels including “free of aflatoxin”, “contaminated below the limit”, and “contaminated above the limit”. 300 images were acquired through a mini studio equipped with UV lamps. The aflatoxin level was classified using several pre-trained CNN approaches which has high accuracy such as GoogLeNet, SqueezeNet, AlexNet, and ResNet50. The sensitivity analysis showed that the highest classification accuracy was found in the GoogLeNet model with optimizer: Adam and learning rate: 0.0001 by 96.42%. The model was tested using a testing dataset and obtain accuracy of 96% based on the confusion matrix. The findings indicate that combining CNN with fluorescence images improved the ability to classify the amount of aflatoxin contamination in cacao beans. This method has the potential to be more accurate and economical than the current approach, which could be adapted to reduce aflatoxin's negative effects on food safety and cacao trade losses.

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Revalorization of Macadamia nutshell residue as a filler in eco-friendly castor polyol-based polyurethane foam

Maia

Balieiro

Teixeira

et al. 2023

J Mater Cycles Waste Manag

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Occurrence of aflatoxins in nuts and peanut butter imported to UAE

Cited by 5 publications

References 28 publications

Evaluation of ELISA and immunoaffinity fluorometric analytical tools of four mycotoxins in various food categories

Evaluation of ELISA and immunoaffinity fluorometric analytical tools of four mycotoxins in various food categories

The Classification of Aflatoxin Contamination Level in Cocoa Beans using Fluorescence Imaging and Deep learning

Revalorization of Macadamia nutshell residue as a filler in eco-friendly castor polyol-based polyurethane foam

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