The utility of Raman spectroscopic signatures of fresh pork loin (1 d & 15 d postmortem) in predicting fresh pork tenderness and slice shear force (SSF) was determined. Partial least square models showed that sensory tenderness and SSF are weakly correlated (R² = 0.2). Raman spectral data were collected in 6 s using a portable Raman spectrometer (RS). A PLS regression model was developed to predict quantitatively the tenderness scores and SSF values from Raman spectral data, with very limited success. It was discovered that the prediction accuracies for day 15 post mortem samples are significantly greater than that for day 1 postmortem samples. Classification models were developed to predict tenderness at two ends of sensory quality as “poor” vs. “good”. The accuracies of classification into different quality categories (1st to 4th percentile) are also greater for the day 15 postmortem samples for sensory tenderness (93.5% vs 76.3%) and SSF (92.8% vs 76.1%). RS has the potential to become a rapid on-line screening tool for the pork producers to quickly select meats with superior quality and/or cull poor quality to meet market demand/expectations.

确定了鲜猪肉里脊（死后1天和15天）的拉曼光谱特征在预测鲜猪肉嫩度和切片剪切力（SSF）中的实用性。偏最小二乘模型显示，感觉压痛与SSF相关性较弱（R ² = 0.2）。使用便携式拉曼光谱仪（RS）在6 s内收集拉曼光谱数据。开发了PLS回归模型以从拉曼光谱数据定量预测嫩度评分和SSF值，但效果非常有限。发现尸检后第15天的预测准确度显着大于尸检后第1天的预测准确度。开发了分类模型以预测感官质量两端的压痛，即“差”与“好”。死后15天的感官压痛（93.5％vs 76.3％）和SSF（92.8％vs 76.1％）的不同质量分类（第1至第4个百分位数）的准确性也更高。