Biosensors and the evaluation of food contaminant biosensors in terms of their performance criteria

Aydın, Elif Burcu; Aydın, Muhammet; Sezgintürk, Mustafa Kemal

doi:10.1080/03067319.2019.1672675

Cited by 12 publications

(4 citation statements)

References 95 publications

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“…Amidst the prevailing challenges in food safety assessment, the integration of artificial intelligence (AI) with biosensors has assumed paramount importance [ 41 ]. Key attributes, including sensitivity, selectivity, stability, detection limit, reproducibility, response time, and range or linearity [ 42 ], are not only pivotal for the standalone performance of biosensors but also hold pivotal roles in their amalgamation with AI. This integration allows for the precise identification and interpretation of signals from biosensors, enabling the swift detection and accurate analysis of harmful substances in food [ 43 ].…”

Section: The Role Of Biosensors In Food Safety Assessmentmentioning

confidence: 99%

The Application of Multi-Parameter Multi-Modal Technology Integrating Biological Sensors and Artificial Intelligence in the Rapid Detection of Food Contaminants

Zhang,

Yang,

Zhu

2024

Foods

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Against the backdrop of continuous socio-economic development, there is a growing concern among people about food quality and safety. Individuals are increasingly realizing the critical importance of healthy eating for bodily health; hence the continuous rise in demand for detecting food pollution. Simultaneously, the rapid expansion of global food trade has made people’s pursuit of high-quality food more urgent. However, traditional methods of food analysis have certain limitations, mainly manifested in the high degree of reliance on personal subjective judgment for assessing food quality. In this context, the emergence of artificial intelligence and biosensors has provided new possibilities for the evaluation of food quality. This paper proposes a comprehensive approach that involves aggregating data relevant to food quality indices and developing corresponding evaluation models to highlight the effectiveness and comprehensiveness of artificial intelligence and biosensors in food quality evaluation. The potential prospects and challenges of this method in the field of food safety are comprehensively discussed, aiming to provide valuable references for future research and practice.

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Section: The Role Of Biosensors In Food Safety Assessmentmentioning

confidence: 99%

The Application of Multi-Parameter Multi-Modal Technology Integrating Biological Sensors and Artificial Intelligence in the Rapid Detection of Food Contaminants

Zhang,

Yang,

Zhu

2024

Foods

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“…They can be useful for on-line patulin control in the food industry. The main challenges of biosensors are the limited stability of the bio-recognition component (which affects the biosensors’ long-term storage stability), poor selectivity, especially in enzyme inhibition-based biosensors, and the high cost of antibodies when compared to synthetic recognition elements ( Kaur et al., 2015 ; Burcu Aydın et al., 2020 ) ( Table 3 ).…”

Section: Detection Technology Of Patulin and Alternaria ...mentioning

confidence: 99%

Comprehensive review on patulin and Alternaria toxins in fruit and derived products

Bacha

Nie

et al. 2023

Front. Plant Sci.

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Mycotoxins are toxic secondary metabolites produced by certain fungi, which can contaminate various food commodities, including fruits and their derived products. Patulin and Alternaria toxins are among the most commonly encountered mycotoxins in fruit and their derived products. In this review, the sources, toxicity, and regulations related to these mycotoxins, as well as their detection and mitigation strategies are widely discussed. Patulin is a mycotoxin produced mainly by the fungal genera Penicillium, Aspergillus, and Byssochlamys. Alternaria toxins, produced by fungi in the Alternaria genus, are another common group of mycotoxins found in fruits and fruit products. The most prevalent Alternaria toxins are alternariol (AOH) and alternariol monomethyl ether (AME). These mycotoxins are of concern due to their potential negative effects on human health. Ingesting fruits contaminated with these mycotoxins can cause acute and chronic health problems. Detection of patulin and Alternaria toxins in fruit and their derived products can be challenging due to their low concentrations and the complexity of the food matrices. Common analytical methods, good agricultural practices, and contamination monitoring of these mycotoxins are important for safe consumption of fruits and derived products. And Future research will continue to explore new methods for detecting and managing these mycotoxins, with the ultimate goal of ensuring the safety and quality of fruits and derived product supply.

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“…Metals, metal oxides, conductive polymers, biopolymers, carbon-based structures, quantum dots and their composites [ 93 , 100 , 107 , 109 , 119 , 120 ] have been used as the immobilization matrices for label-free electrochemical cancer biosensors. In general, electrostatic interactions can have negative effects on the stability of the biorecognition element or the repeatability of the biosensor [ 121 , 122 ]. However, these methods, which have very simple processes, are still actively used in the surface immobilization of many electrodes.…”

Section: Immobilization Strategies Of Biorecognition Elementsmentioning

confidence: 99%

Label-Free Electrochemical Biosensor Platforms for Cancer Diagnosis: Recent Achievements and Challenges

Şanko

Kuralay

2023

Biosensors

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With its fatal effects, cancer is still one of the most important diseases of today’s world. The underlying fact behind this scenario is most probably due to its late diagnosis. That is why the necessity for the detection of different cancer types is obvious. Cancer studies including cancer diagnosis and therapy have been one of the most laborious tasks. Since its early detection significantly affects the following therapy steps, cancer diagnosis is very important. Despite researchers’ best efforts, the accurate and rapid diagnosis of cancer is still challenging and difficult to investigate. It is known that electrochemical techniques have been successfully adapted into the cancer diagnosis field. Electrochemical sensor platforms that are brought together with the excellent selectivity of biosensing elements, such as nucleic acids, aptamers or antibodies, have put forth very successful outputs. One of the remarkable achievements of these biomolecule-attached sensors is their lack of need for additional labeling steps, which bring extra burdens such as interference effects or demanding modification protocols. In this review, we aim to outline label-free cancer diagnosis platforms that use electrochemical methods to acquire signals. The classification of the sensing platforms is generally presented according to their recognition element, and the most recent achievements by using these attractive sensing substrates are described in detail. In addition, the current challenges are discussed.

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Biosensors and the evaluation of food contaminant biosensors in terms of their performance criteria

Cited by 12 publications

References 95 publications

The Application of Multi-Parameter Multi-Modal Technology Integrating Biological Sensors and Artificial Intelligence in the Rapid Detection of Food Contaminants

The Application of Multi-Parameter Multi-Modal Technology Integrating Biological Sensors and Artificial Intelligence in the Rapid Detection of Food Contaminants

Comprehensive review on patulin and Alternaria toxins in fruit and derived products

Label-Free Electrochemical Biosensor Platforms for Cancer Diagnosis: Recent Achievements and Challenges

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