Rapid Testing of Aflatoxin by Using Image Processing and Artificial Neural Network

Soemantri, A S; Miskiyah,; Juniawati,; Diyono, Wahyu

doi:10.1088/1755-1315/309/1/012062

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…Moreover, it was proclaimed that AF shows bright greenish‐yellow fluorescence (BGYF) under ultraviolet (UV) light at a wavelength of 365 nm (Wicklow, 1999). Soemantri and Diyono (2019) applied this information for rapid detection of AF in corn using UV sensing digital camera with 5‐watt UV lamps. They built ANN architecture considering 10 input parameters, viz.…”

Section: Application Of Digital Color Imaging For Mold and Mycotoxins...mentioning

confidence: 99%

Research advancements in optical imaging and spectroscopic techniques for nondestructive detection of mold infection and mycotoxins in cereal grains and nuts

Mishra

Panda

Ramirez

et al. 2021

Comp Rev Food Sci Food Safe

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Cereal grains and nuts are represented as the economic backbone of many developed and developing countries. Kernels of cereal grains and nuts are prone to mold infection under high relative humidity and suitable temperature conditions in the field as well as storage conditions. Health risks caused by molds and their molecular metabolite mycotoxins are, therefore, important topics to investigate. Strict regulations have been developed by international trade regulatory bodies for the detection of mold growth and mycotoxin contamination across the food chain starting from the harvest to storage and consumption. Molds and aflatoxins are not evenly distributed over the bulk of grains, thus appropriate sampling for detection and quantification is crucial. Existing reference methods for mold and mycotoxin detection are destructive in nature as well as involve skilled labor and hazardous chemicals. Also, these methods cannot be used for inline sorting of the infected kernels. Thus, analytical methods have been extensively researched to develop the one that is more practical to be used in commercial detection and sorting processes. Among various analytical techniques, optical imaging and spectroscopic techniques are attracting growers' attention for their potential of nondestructive and rapid inline identification and quantification of molds and mycotoxins in various food products. This review summarizes the recent application of rapid and nondestructive optical imaging and spectroscopic techniques, including digital color imaging, X-ray imaging, near-infrared spectroscopy, fluorescent, multispectral, and hyperspectral imaging. Advance chemometric techniques to identify very low-level mold growth and mycotoxin contamination are also discussed. Benefits, limitations, and challenges of deploying these techniques in practice are also presented in this paper.

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Section: Application Of Digital Color Imaging For Mold and Mycotoxins...mentioning

confidence: 99%

Research advancements in optical imaging and spectroscopic techniques for nondestructive detection of mold infection and mycotoxins in cereal grains and nuts

Mishra

Panda

Ramirez

et al. 2021

Comp Rev Food Sci Food Safe

View full text Add to dashboard Cite

show abstract

“…Their results showed the highest accuracy of 96.35% for nuts over other samples tested (corn) [200,201]. Soemantri et al reported even higher accuracy for corn (an average accuracy of 99%) [202].…”

Section: Image Processingmentioning

confidence: 89%

Current Developments of Analytical Methodologies for Aflatoxins’ Determination in Food during the Last Decade (2013–2022), with a Particular Focus on Nuts and Nut Products

Schincaglia

Aspromonte

Franchina

et al. 2023

Foods

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This review aims to provide a clear overview of the most important analytical development in aflatoxins analysis during the last decade (2013–2022) with a particular focus on nuts and nuts-related products. Aflatoxins (AFs), a group of mycotoxins produced mainly by certain strains of the genus Aspergillus fungi, are known to impose a serious threat to human health. Indeed, AFs are considered carcinogenic to humans, group 1, by the International Agency for Research on Cancer (IARC). Since these toxins can be found in different food commodities, food control organizations worldwide impose maximum levels of AFs for commodities affected by this threat. Thus, they represent a cumbersome issue in terms of quality control, analytical result reliability, and economical losses. It is, therefore, mandatory for food industries to perform analysis on potentially contaminated commodities before the trade. A full perspective of the whole analytical workflow, considering each crucial step during AFs investigation, namely sampling, sample preparation, separation, and detection, will be presented to the reader, focusing on the main challenges related to the topic. A discussion will be primarily held regarding sample preparation methodologies such as partitioning, solid phase extraction (SPE), and immunoaffinity (IA) related methods. This will be followed by an overview of the leading analytical techniques for the detection of aflatoxins, in particular liquid chromatography (LC) coupled to a fluorescence detector (FLD) and/or mass spectrometry (MS). Moreover, the focus on the analytical procedure will not be specific only to traditional methodologies, such as LC, but also to new direct approaches based on imaging and the ability to detect AFs, reducing the need for sample preparation and separative techniques.

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Aflatoxin contamination level estimation in food using reflectance multispectral imaging based system

Madushan,

Malshan,

Abewickrama

et al. 2024

Journal of Agriculture and Food Research

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Rapid Testing of Aflatoxin by Using Image Processing and Artificial Neural Network

Cited by 3 publications

References 6 publications

Research advancements in optical imaging and spectroscopic techniques for nondestructive detection of mold infection and mycotoxins in cereal grains and nuts

Research advancements in optical imaging and spectroscopic techniques for nondestructive detection of mold infection and mycotoxins in cereal grains and nuts

Current Developments of Analytical Methodologies for Aflatoxins’ Determination in Food during the Last Decade (2013–2022), with a Particular Focus on Nuts and Nut Products

Aflatoxin contamination level estimation in food using reflectance multispectral imaging based system

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