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Rapid and Quantitative Detection of the Microbial Spoilage of Meat by Fourier Transform Infrared Spectroscopy and Machine Learning

机译:傅立叶变换红外光谱和机器学习快速定量检测肉类微生物变质

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摘要

Fourier transform infrared (FT-IR) spectroscopy is a rapid, noninvasive technique with considerable potential for application in the food and related industries. We show here that this technique can be used directly on the surface of food to produce biochemically interpretable “fingerprints.” Spoilage in meat is the result of decomposition and the formation of metabolites caused by the growth and enzymatic activity of microorganisms. FT-IR was exploited to measure biochemical changes within the meat substrate, enhancing and accelerating the detection of microbial spoilage. Chicken breasts were purchased from a national retailer, comminuted for 10 s, and left to spoil at room temperature for 24 h. Every hour, FT-IR measurements were taken directly from the meat surface using attenuated total reflectance, and the total viable counts were obtained by classical plating methods. Quantitative interpretation of FT-IR spectra was possible using partial least-squares regression and allowed accurate estimates of bacterial loads to be calculated directly from the meat surface in 60 s. Genetic programming was used to derive rules showing that at levels of 107 bacteria·g−1 the main biochemical indicator of spoilage was the onset of proteolysis. Thus, using FT-IR we were able to acquire a metabolic snapshot and quantify, noninvasively, the microbial loads of food samples accurately and rapidly in 60 s, directly from the sample surface. We believe this approach will aid in the Hazard Analysis Critical Control Point process for the assessment of the microbiological safety of food at the production, processing, manufacturing, packaging, and storage levels.
机译:傅里叶变换红外(FT-IR)光谱是一种快速,无创的​​技术,在食品和相关行业中具有巨大的潜力。我们在这里表明,该技术可以直接在食物表面使用,以产生可生物化学解释的“指纹”。肉类变质是微生物的生长和酶活性引起的分解和代谢产物形成的结果。 FT-IR被用于测量肉基质内的生化变化,从而增强并加速了微生物变质的检测。鸡胸肉购自一家国家零售商,粉碎10秒钟,然后在室温下变质24小时。每小时,使用衰减的总反射率直接从肉类表面进行FT-IR测量,并通过经典的电镀方法获得总的活菌计数。使用偏最小二乘回归可以对FT-IR光谱进行定量解释,并可以在60 s内直接从肉类表面计算出准确的细菌负荷估算值。用遗传程序推导规则,表明在10 7 细菌·g -1 的水平上,变质的主要生化指标是蛋白水解的开始。因此,使用FT-IR,我们能够直接从样品表面获取新陈代谢快照,并在60 s内准确无误地定量评估食品样品的微生物负荷。我们认为,这种方法将有助于危害分析关键控制点过程,以评估食品在生产,加工,制造,包装和存储水平上的微生物安全性。

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