Abstract
Over the past two decades, the meat industry has faced increasing pressure to prevent foodborne outbreaks and reduce economic losses associated with delayed detection of spoilage. This demand has accelerated the development of on-site, real-time sensing tools capable of identifying early signs of contamination. Electrospun nanofiber (NF) platforms have emerged as particularly promising due to their large surface area, tunable porosity, and versatile chemistry, which make them ideal scaffolds for immobilizing enzymes, antibodies, or aptamers while preserving bioactivity under field conditions. These NFs have been integrated into optical, electrochemical, and resistive devices, each enhancing response time and sensitivity for key targets ranging from volatile organic compounds indicating early decay to specific bacterial markers and antibiotic residues. In practical applications, NF matrices enhance signal generation (SERS hotspots), facilitate analyte diffusion through three-dimensional networks, and stabilize delicate biorecognition elements for repeated use. This review summarizes major NF fabrication strategies, representative sensor designs for meat quality monitoring, and performance considerations relevant to industrial deployment, including reproducibility, shelf life, and regulatory compliance. The integration of such platforms with data networks and Internet of Things (IoT) nodes offers a path toward continuous, automated surveillance throughout processing and cold-chain logistics. By addressing current technical and regulatory challenges, NF-based biosensors have the potential to significantly reduce waste and safeguard public health through early detection of contamination before it escalates into costly recalls.
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Ramachandraiah, K., Martin, E. M., & Limayem, A. (2025, November 1). Electrospun Nanofiber Platforms for Advanced Sensors in Livestock-Derived Food Quality and Safety Monitoring: A Review. Sensors. Multidisciplinary Digital Publishing Institute (MDPI). https://doi.org/10.3390/s25226947
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