传统检测烹制猪肉香肠 (CPS)的湿度 (MC) 和持水力（WHC）的方法为无损方法，耗时且需要熟练人员，并不适合在工业在线监测领域应用。本工作的目标是探讨多光谱成像(MSI)技术结合多变量分析法来鉴别CPS中的MC和WHC。结果：利用不同校准模型来分析6种盐浓度(0-2.5%)处理的156根 CPS的光谱和纹理，寻找预测CPS中MC和WHC的较佳结果。利用光谱和纹理融合数据，偏较小二乘回归模型测定MC和WHC结果良好，相关系数(r) 分别为 0.949和0.832。另外，CPS中MC和WHC空间分布可通过预测方程图像传递的每个像素视觉呈现出来。结论：结果令人满意，MC和WHC成像显示MSI多光谱成像法在香肠工业中可作为有潜力的快速、无损检测方法。该研究使用VideometerLab多光谱成像系统。 

    Potential use of multispectral imaging technology to identify moisture content and water-holding capacity in cooked pork sausages: Nondestructive identification of moisture content and water-holding capacity in sausage

Abstract

    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.