Market Drivers and Discovering Technologies in Meat Species Identification

Changing demographics and the need to know what we eat has fueled a drastic rise in consumer awareness and hence the demand for certification by government and regulatory bodies. The inceptions of regulations in emerging economies like India and China that have entered the global food trade are expected to increase the demand for testing services. Due to the sheer volume of the global meat market, there has been focus on technologies for meat speciation, like immunoassay-based techniques and electrophoretic techniques. However, by virtue of their intrinsic constraints, these technologies have been superseded by the recent molecular DNA-based methods. DNA-based technologies, mainly polymerase chain reaction (PCR) and real-time PCR (RTPCR), are in the spotlight because of their quantitative capabilities, better sensitivity, and rapidity. Next-generation sequencing (NGS), a high-throughput sequencing method, has revolutionized meat speciation studies in terms of speed, read length, and throughput, along with cost-reduction. Variants of chromatographic and spectroscopic techniques are an attractive option due to the speed of analysis and minimal sample preparation but they fail to quantify adulteration in cases such as cooked meat, which has more complex chromatographic patterns. Even with the advent of these methods, consumers need to be vigorously assured that players across the supply network are operating in the consumer’s interest and not in their own financial gain. Under the Blockchain system of technology, traceability of the end product is feasible at every point of its processing or packaging and all the data can be retrieved in less than 2 min. Considering the intersection of the largest target segment, meat, and the fastest growing technology, PCR-based technology, this review intends to provide an updated overview, of market and research studies for authenticity, and a short summary of traceability systems to enhance trade transparency.