Introduction
Food safety becomes integral when it comes to the food and agricultural sector and it plays a significant role in promoting the sound health of individuals in addition to ensuring consumption of products with reasonable quality standards. Bacteria, viruses, fungi and parasites are the common causes of the spoilage and contamination in the various types of food products. Besides microbial contamination, veterinary drugs, pesticide residues, insecticide residues, non-permitted additives, extraneous matters and other components have the potential to contaminate the food matrixes. These biological contaminants can impose severe threats to human beings, apart from often being able to interfere with the quality of food products. Hence, detecting these dangerous components in food products becomes crucial to ensure food safety. In order to rectify the issues associated with food safety, several strategic measures have been implemented to detect the chemical and biological hazards in foods. (Zhang et al., 2022)
For the quantitative & qualitative determination of the biological and chemical contaminates present inside the foods, there are different conventional method ologies, which include the Titrimetric methods, Microbial cultures, Polymerase chain reaction and Chromatographic techniques. The conventional methods are time-consuming and are also required to pass through complex procedures, in order to detect the presence of various contaminants. The detection threshold of some of the conventional methods is very low, while the chances of errors are higher. Experienced technical persons are required to evaluate conventional analysis methods effectively.
Principle of Biosensing
The various types of sensors are simple and compact detectors for identifying and monitoring biological and chemical compounds. Chemical, biochemical and electrochemical sensors are commonly used in the agro and food sectors. Enzyme-based, Immuno-based, Nucleic acid-based and chemical-based sensors are used in the Food Industry in various applications to detect chemical substances, pathogens and adulterants.
Modern sensing techniques are designed to make detection simple and compactable. Advanced methodologies, including smartphone-mediated detection strategies, 3D printing-mediated sensing strategies, Artificial Intelligence (AI) based sensing strategies and Infrared sensing strategies are implemented to ensure safety of various types of food products in the food sector, (Mao et al., 2022).
Further, the requirements to adopt sensing technology to ensure food safety has become essential today. The current studies on biosensors for food safety and quality are mainly focused on the farm-to-fork detection of contaminants, product quality from farms, the agricultural field, sorting and grading areas, real-time physicochemical sensing strategies and laboratory scale sensing technologies. The new strategies for molecular detection mainly include enzymatic, nucleic acid-based, immune-based and molecular-impregnated polymer-based approaches. (Peng et al., 2022)
Biosensing Strategies in Food Safety
Conventional microbial biosensors use the respiratory and metabolic functions of the microorganisms to detect a substance that is either a substrate or an inhibitor of the processes. Microbial biosensors are more advantageous than enzyme biosensors, since the construction of enzyme sensors is complex and costly. Some main types of microbial biosensors are amperometric, potentiometric and conductometric sensors. The amperometric microbial biosensor operates at a fixed potential concerning a reference electrode and involves the detection of the current generated by the oxidation or reduction of species at the surface of the electrode. Generally, potentiometric microbial biosensors consist of an ion-selective or gas-sensing electrode coated with an immobilized microbial layer. Due to microbial metabolism, the uptake or release of analyte generates a change in potential resulting from ion accumulation or depletion. Potentiometric transducers measure the potential difference between a working electrode and a reference electrode and the signal is correlated to the concentration of the analyte. The signals are expressed through a logarithmic relationship between the potential generated and analyte concentration, so that a wide detection range becomes possible. Potentiometric microbial sensors are used to detect organophosphates, penicillin, tryptophan, urea, trichloroethylene, ethanol and sucrose.
Application in Food Safety
Conventional methods for detecting and identifying foodborne pathogens are primarily based on microbiological and biochemical identification. However, they are greatly restricted by long assay time that sometimes may take up to several days to yield results, due to enrichment requirements. Biosensors for foodborne pathogens should comply with high sensitivity (ability to detect lower population densities) as a desirable feature, because some pathogens are harmful at low densities, (Adley & Ryan, 2015). In recent years, biosensors have become an alternative tool to conventional methods, owing to their ability to perform rapid response analyses, high-throughput capacity, good selectivity, low cost, speed of operation, portability and the ability to measure samples with minimal sample preparation, (Moran et al., 2016). The biosensors are commonly used to detect contaminants like pesticide residues, veterinary drugs, illegal additives, pathogens, mycotoxins and allergens, (Hua et al., 2021). These biosensors are good at detecting these contaminants in foods, agri-products and aquaculture products.
Most food products are highly perishable & each food is susceptible to rapid physicochemical changes and rapid microbial contamination. Therefore, it is highly essential to detect the contaminants and chemicals within a shorter time period. The conventional methods are accurate, but it requires more time to detect these contaminants. Meanwhile, the food product should undergo different physicochemical and chemical changes during the detection process. Therefore, rapid detection technologies are essential for the detection of contaminants instantaneously. Especially in the case of quality testing during the receiving of ingredients and during the plant form test of milk, these biosensors can be effectively implemented in the Food Industry to maintain safety and improve the quality of the food ingredients and thus, the final products.
Conclusion
Biosensors, to assist in monitoring of the of foods have been a research focus already for decades, as biosensors’ key characteristics such as simplicity, sensitivity and low cost match well with the challenging demands that need to be met when ensuring food safety. In food detection, biosensors stand out, owing to the various advantages that come with them, which include high sensitivity, high selectivity and low cost. With further developments taking place on the technology front after the arrival of computer systems, followed by the Internet, 3D Printing, Artificial Intelligence, as well as various other technologies, biosensors are being gradually integrated along with them for maximizing their performance.
References:
1. Adley, C . C ., & Ryan, M. P. (2015). Conductometric biosensors for high throughput screening of pathogens in food. High Throughput Screening for Food Safety Assessment: Biosensor Technologies, Hyperspectral Imaging and Practical Applications, 315–326. https://doi. org/10.1016/B978-0-85709-801-6.00014-9
2. Hua, Z., Yu, T., Liu, D., & Xianyu, Y. (2021). Recent advances in gold nanoparticles-based biosensors for food safety detection. Biosensors and Bioelectronics, 179, 113076.
3. Mao, Z., Chen, R., Wang, X., Zhou, Z., Peng, Y., Li, S., Han, D., Li, S., Wang, Y., & Han, T. (2022). CRISPR/Cas12a-based technology: A powerful tool for biosensing in food safety. Trends in Food Science & Technology.
4. Moran, K. L. M., Fitzgerald, J., McPartlin, D. A., Loftus, J. H., & O’Kennedy, R. (2016). Biosensor-Based Technologies for the Detection of Pathogens and Toxins. Comprehensive Analytical Chemistry, 74, 93–120. https://doi. org/10.1016/BS.COAC.2016.04.002
5. Peng, L., Li, P., Chen, J., Deng, A., & Li, J. (2022). Recent progress in assembly strategies of nanomaterials-based ultrasensitive electrochemiluminescence biosensors for food safety and disease diagnosis. Talanta, 123906.
6. Zhang, J., Huang, H., Song, G., Huang, K., Luo, Y., Liu, Q., He, X., & Cheng, N. (2022). Intelligent biosensing strategies for rapid detection in food safety: A review. Biosensors and Bioelectronics, 114003.
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