Using Raman Spectroscopy to Identify Antibiotics in Meat (Research Proposal Sample)

Using Raman Spectroscopy to Identify Antibiotics in Meat
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Using Raman Spectroscopy to Identify Antibiotics in Meat
Introduction
Meat safety is often multidimensional, whereby there is information asymmetry between producers, public safety authorities, and consumers. Since their discovery in the mid-20th century, meat producers use antibiotics to treat diseases and enhance animal growth. Animals have been shown to gain up to 3% weight, thereby enhancing bottom lines for meat producers (PBS, n.d.). Also, meat producers often deny the pervasive use of antibiotics in the industry. This has made it hard to obtain accurate data concerning the amount of antibiotics given to animals. Ingestion of antibiotics can result in the resistance of many bacteria, including Salmonella and E.coli which has been linked to more than 23,000 deaths in the U.S every year and about $ 34 billion in losses (Cohan, 2018). Another 400,000 U.S residents fall ill due to infections emanating from foodborne antibiotic resistant bacteria. The World Health Organization has identified antimicrobial resistance as a significant threat to food security, development, and global health (Ritchie, 2017). The declining effectiveness of treatment manifests as bacterial populations evolve, causing the treatments to become less ineffective ort completely ineffective
Background
While the hazards due to the use of antibiotics have been documented, an effective technique for detection in the meat industry is yet to be developed. The highly resolved and narrow bands of the spatially offset Raman spectroscopy (SORS) methodology provide a suitable method for non-destructive extraction of physical and chemical information concerning samples. This sensor technology can be used to analyze meat products before they reach consumers. SORS has been employed in the industry to differentiate various by beef cuts as demonstrated by Ostovar Pour et al. (2020). In the analysis, different beef cuts were analyzed using SORS for depths of up to 5mm. The technique allowed a non- invasive analysis of protein, fat and glycogen levels in muscles. The spectroscopic results were obtained through a statistical clustering of the various meat cuts. Also, SORS has also been used to analyze meat product’s chemical composition by Ostovar Pour et al. (2019) and permitted an analysis of diffusely located samples at greater depth compared to traditional Raman spectroscopy. SORS helped in detecting the spectral bands of chemicals such as cortisal, lactate, and glucose below the meat surface by spiking. The results were validated using chemometric analysis which clearly showed the chemical compounds in meat tissue according to their distinct groups. In this study, SORS will allow for rapid analysis that does not require special preparation. The technique will analyze meat composition at the subsurface level to identify biochemical marker bands associated with antibiotics. Overall, this study seeks to evaluate the efficacy of SORS in analyzing meat products for the presence of antibiotics.