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Rapid determination of pork sensory quality using Raman spectroscopy

机译：拉曼光谱法快速测定猪肉的感官质量

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摘要

Existing objective methods to predict sensory attributes of pork in general do not yield satisfactory correlation to panel evaluations, and their applications in meat industry are limited. In this study, a Raman spectroscopic method was developed to evaluate and predict tenderness, juiciness and chewiness of fresh, uncooked pork loins from 169 pigs. Partial Least Square Regression models were developed based on Raman spectroscopic characteristics of the pork loins to predict the values of the sensory attributes. Furthermore, binary barcodes were created based on spectroscopic characteristics of the pork loins, and subjected to multivariate statistical discriminant analysis (i.e., Support Vector Machine) to differentiate and classify pork loins into quality grades ("good" and "bad" in terms of tenderness and chewiness). Good agreement (>83% correct predictions) with sensory panel results was obtained. The method developed in this report has the potential to become a rapid objective assay for tenderness and chewiness of pork products that may find practical applications in pork industry.
机译：总体而言，现有的预测猪肉感官特性的客观方法与专家组评估不能令人满意地相关，因此它们在肉类工业中的应用受到限制。在这项研究中，开发了一种拉曼光谱方法来评估和预测169头生猪的未煮熟的猪里脊肉的嫩度，多汁性和咀嚼性。基于猪腰的拉曼光谱特征开发了偏最小二乘回归模型，以预测感官属性的值。此外，根据猪里脊肉的光谱特性创建了二进制条形码，并对其进行了多元统计判别分析（即支持向量机），以将猪里脊肉的嫩度区分和分类为质量等级（“好”和“差”）和耐嚼性）。获得了与感觉小组结果的良好一致性（正确预测> 83％）。本报告中开发的方法有可能成为猪肉产品嫩度和咀嚼性的快速客观测定方法，可能在猪肉行业中得到实际应用。

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