背景

   烹制猪肉香肠中水分含量（MC）和持水力（WHC）的传统检测方法是一种有损、耗时的方法，需要熟练人员进行操作，不适合应用于在线工业领域。

   本研究的目标是探索多光谱成像（MSI）与多变量分析法结合来鉴别水分含量（MC）和持水力（WHC）。

结果

   用6种不同盐浓度（0-2.5%）处理的156个CPS样品采用了不同的校准模型来进行分析，以便寻找预测CPS中的MC和WHC的较佳方法。

   通过使用光谱和质构的融合数据，利用偏较小二乘法回归模型测定的MC和WHC的相关系数（r）分别为0.949和0.832。另外，其在CPS中的空间分布可通过应用预测方程将每个像素转换为图像，从而可视。

结论

   对MC和WHC测量取得了令人满意的检测和可视结果，多光谱分析法是一种可用于香肠工业领域的快速、无损检测方法。

BACKGROUND

The traditional detection methods for moisture content (MC) and water-holding capacity (WHC) in cooked pork sausages (CPS) are destructive, time-consuming, and require skilled personnel and not suitable for on-line industry applications. 

The goal of this work was to explore the potential of multispectral imaging (MSI) in combination with multivariate analysis for the identification of MC and WHC in CPS.

RESULTS

Spectra and textures of 156 CPS treated by six salt concentrations (0–2.5%) were analyzed using different calibration models to find the most optimal results of predicting MC and WHC in CPS. 

By using the fused data of spectra and textures, partial least squares regression models performed well for determining the MC and WHC with correlation coefficient (r) of 0.949 and 0.832, respectively. Additionally, the spatial distribution of them in CPS could be visualized via applying the prediction equations to transfer each pixel in the image.

CONCLUSION

Results of satisfactory detection and visualization of the MC and WHC showed that MSI has the potential to serve as a rapid and nondestructive method for use in sausage industry.