The use of molecular spectroscopic techniques combined with chemometric machine learning for the analysis of meat freshness: a narrative review

The objective of this review was to highlight the application of molecular spectroscopy combined with chemometrics to evaluate the freshness and quality of meats intended for quality control of meats and meat-based food products.The development and validation of reliable analytical method for the evaluation of meat freshness and meat quality is very crucial for safeguarding food hygiene.Numerous analytical methods, either particularly conventional methods such as wet chemical and organoleptic analysis, have long been used for the assessment of meat freshness.these methods can be labour-intensive, time-consuming, and often require substantial amounts of chemical reagents.or advanced (modern) methods such as spectroscopy, chromatography and sensors have been reported for the assessment of meat freshness.Molecular spectroscopic methods such as UV-vis, fluorescence and vibrational spectroscopy (infrared, Raman, hyperspectral imaging), specifically, offered rapid and reliable approaches method for the evaluatingon of meat quality and meat freshness, with the potential to reduce sample preparation, reagent consumption, and analytical waste.Advances in chemometric and machine-learning approaches have further enhanced the application of molecular spectroscopy for meat freshness assessment by enabling the extraction of meaningful information from compl ex spect r oscopi c dat a and t he devel opment of pr edi ct i ve model sW i t h t he advanced of machi ne l ear ni ng or chemomet r i cs, mol ecul ar spect r oscopy has been wi del y r epor t ed f or det er mi nat i on of meat f reshness.Thi s r evi ew hi ghl i ght s recent advances in molecular spectroscopy coupled with chemometric and machine-learning techniques for the evaluation of meat freshness and quality.