IRTA. XaRTA. Food Technology. Finca Camps i Armet, E-17121 Monells (Girona), Spain.
Meat Sci. 2013 Apr;93(4):873-9. doi: 10.1016/j.meatsci.2012.12.002. Epub 2012 Dec 7.
Development of real-time, non-destructive methods to characterize dry-cured ham is of interest to the food industry. Since dielectric properties change depending on the composition of the food product studied, time domain reflectometry (TDR) could be a useful method to characterize dry-cured ham. In this study, samples with different compositions were measured with a TDR device equipped with an open-ended coaxial line sensor. Partial least square regression (PLSR) analysis was used to develop predictive models to determine salt, water and fat contents and a(w) in dry-cured ham. Results show that salt content (RMSEV=0.22%), water content (RMSEV=1.67%) and a(w) (RMSEV=0.0087) can be accurately determined, though fat content is determined with less precision (RMSEV=2.81%). Saltiness, dryness and fatness of the samples, in the studied range, did not affect the accuracy of the predictions. Developed predictive models were accurate enough to consider the TDR device as a useful tool for characterizing and classifying dry-cured ham in industry.
开发实时、非破坏性的方法来描述干腌火腿的特性是食品工业感兴趣的。由于介电特性取决于所研究的食品产品的组成，时域反射（TDR）可能是一种有用的方法来描述干腌火腿。在这项研究中，使用配备开放式同轴线路传感器的 TDR 设备测量了具有不同成分的样品。偏最小二乘回归（PLSR）分析用于开发预测模型，以确定干腌火腿中的盐、水和脂肪含量以及 aw。结果表明，可以准确确定盐含量（RMSEV=0.22%）、水含量（RMSEV=1.67%）和 aw（RMSEV=0.0087），尽管脂肪含量的确定精度较低（RMSEV=2.81%）。在所研究的范围内，样品的咸味、干燥度和脂肪度不会影响预测的准确性。开发的预测模型足够准确，可以考虑 TDR 设备作为在工业中描述和分类干腌火腿的有用工具。
