Biomarkers and biosensors for the diagnosis of noncompliant pH, dark cutting beef predisposition, and welfare in cattle

COMPREHENSIVE REVIEWS IN FOOD SCIENCE AND FOOD SAFETY(2022)

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摘要
Meat quality can be affected by stress, exhaustion, feed composition, and other physical and environmental conditions. These stressors can alter the pH in postmortem muscle, leading to high pH and low-quality dark cutting (DC) beef, resulting in considerable economic loss. Moreover, the dark cutting prediction may equally provide a measure for animal welfare since it is directly related to animal stress. There are two needs to advance on-site detection of dark cutters: (1) a clear indication that biomarker (signature compounds) levels in cattle correlate with stress and DC outcome; and (2) measuring these biomarkers rapidly and accurately on-farm or the abattoir, depending on the objectives. This critical review assesses which small molecules and proteins have been identified as potential biomarkers of stress and dark cutting in cattle. We discuss the potential of promising small molecule biomarkers, including catecholamine/cortisol metabolites, lactate, succinate, inosine, glucose, and beta-hydroxybutyrate, and we identify a clear research gap for proteomic biomarker discovery in live cattle. We also explore the potential of chemical-sensing and biosensing technologies, including direct electrochemical detection improved through nanotechnology (e.g., carbon and gold nanostructures), surface-enhanced Raman spectroscopy in combination with chemometrics, and commercial hand-held devices for small molecule detection. No current strategy exists to rapidly detect predictive meat quality biomarkers due to the need to further validate biomarkers and the fact that different biosensor types are needed to optimally detect different molecules. Nonetheless, several biomarker/biosensor combinations reported herein show excellent potential to enable the measurement of DC potential in live cattle.
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biomarkers, biosensors, dark cutting, detect welfare in cattle, meat quality, on-farm meat quality prediction
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