The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
Label-free optical biosensors for food and biological sensor applications
Abstract
Abstract Safety of food is a scientific domain requiring advanced handling, preparation, and storage. Food is a paramount need for growth of microorganisms it serves as a medium for proliferation and contamination. The primary historical techniques for food analysis are time-consuming and laborious whereas biosensors have an easier control over these limitations. Biosensor technology is a powerful tool for food analysis. Optical sensors reveal higher calibre for analysis of drugs, pesticide residues, pathogens, heavy metals, toxic substances as well as for overall hygiene monitoring in the food system. Label-free operations altogether acquired a well-established need for the characterization and identification of molecular components. We review the recent advances in label-free optical biosensors based on the target analytes. This study focuses on the concise classification, underlying principles on the optical transducer, optical (surface) analytical techniques as a part of biosensing and use of nanostructures in optical sensors. The main highlights include characterisation of localized surface plasmon and surface plasmon resonance based biosensors. Additionally, other optical biosensors such as bioluminescent optical fibre biosensors, evanescent wave fluorescence, ellipsometric, surface-enhanced Raman scattering and light-addressable potentiometric sensors are also well explained and characterized for food and environmental applications.
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Citations
Cites
Localized Surface Plasmon Resonance Sensors
Mayer, K. M., & Hafner, J. H. (2011) · Chemical Reviews · doi:10.1021/cr100313v · Cited by 4,350
Surface plasmon resonance for gas detection and biosensing
Liedberg, B., Nylander, C., & Lunström, I. (1983) · Sensors and Actuators · doi:10.1016/0250-6874(83)85036-7 · Cited by 2,539
Sensitive optical biosensors for unlabeled targets: A review
Fan, X., White, I. M., Shopova, S. I., Zhu, H., Suter, J. D., & Sun, Y. (2008) · Analytica Chimica Acta · doi:10.1016/j.aca.2008.05.022 · Cited by 2,187
Single Silver Nanoparticles as Real-Time Optical Sensors with Zeptomole Sensitivity
McFarland, A. D., & Van Duyne, R. P. (2003) · Nano Letters · doi:10.1021/nl034372s · Cited by 1,626
Surface Plasmon Resonance: A Versatile Technique for Biosensor Applications
Nguyen, H., Park, J., Kang, S., & Kim, M. (2015) · Sensors · doi:10.3390/s150510481 · Cited by 1,357
Plasmonics for future biosensors
Brolo, A. G. (2012) · Nature Photonics · doi:10.1038/nphoton.2012.266 · Cited by 1,074
Damborský, P., Švitel, J., & Katrlík, J. (2016) · Essays in Biochemistry · doi:10.1042/ebc20150010 · Cited by 907
Bornehag, C.-G., Sundell, J., Weschler, C. J., Sigsgaard, T., Lundgren, B., Hasselgren, M., & Hägerhed-Engman, L. (2004) · Environmental Health Perspectives · doi:10.1289/ehp.7187 · Cited by 851
Advances in biosensors for detection of pathogens in food and water
Leonard, P., Hearty, S., Brennan, J., Dunne, L., Quinn, J. G., Chakraborty, T., & O’Kennedy, R. J. (2002) · Enzyme and Microbial Technology · doi:10.1016/s0141-0229(02)00232-6 · Cited by 605
Localized Surface Plasmon Resonance Biosensing: Current Challenges and Approaches
Unser, S., Bruzas, I., He, J., & Sagle, L. (2015) · Sensors · doi:10.3390/s150715684 · Cited by 565
Cited by
Optical biosensors: A decade in review
Singh, A. K., Mittal, S., Das, M., Saharia, A., & Tiwari, M. (2023) · Alexandria Engineering Journal · doi:10.1016/j.aej.2022.12.040 · Cited by 292
Metadata
- Authors
- Khansili, N., Rattu, G., & Krishna, P. M.
- Venue
- Sensors and Actuators B: Chemical
- Publisher
- Elsevier BV
- Published
- 2018-07
- Volume
- 265
- Pages
- 35-49
- ISSN
- 0925-4005 (ISSN-L)
- OpenAlex
- W2792475275
- Cited by
- 328
- References
- 55
- FWCI
- 11.70
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.