Near infrared (NIR) measurements have been used for several years to examine the processes taking place in the dishwasher during dishwashing. It is possible to differentiate between the soil components butterfat, oatmeal and egg-yolk and to determine their concentration in the dishwashing liquor quantitatively. Consequently, time-consuming dishwashing tests can be avoided by weighing the dishes. However, this method is also based on a small number of NIR measurements which are carried out intrusively during the dishwashing process, i.e. outside the dishwasher. These few NIR measurements make it difficult to investigate the dynamics of a dishwashing process. In this study, the development, testing and usage of a new online tracking measuring system is presented. The latter was used to perform 38 dishwashing processes, each containing 51 NIR spectra, to develop a calibration model using the partial least squares regression method with cross-validation. This new online tracking measuring system, based on the calibration, can determine the concentrations of three different soil components in the dishwashing liquor during automatic dishwashing. By recording the 51 spectra, it is possible to display a tracking curve for each soil component, i.e. the concentration courses of the dishwashing process over time. This results in a significantly better time resolution and it was possible to investigate the first dynamic part of the tracking curve, i.e. the beginning of the dishwashing process. This could lead to the opportunity to change the state of the dishwasher depending on the concentrations detected in the first step and, secondly, to a more environmentally friendly and cost-reducing dishwashing process.

近红外（NIR）测量已用于检查洗碗机中在洗碗机中发生的过程数年。可以区分黄油，燕麦片和蛋黄的土壤成分，并定量确定它们在洗碗液中的浓度。因此，可以通过称量碗碟来避免费时的洗碗测试。但是，该方法也基于少量的NIR测量，这些测量是在洗碗过程中（即在洗碗器外）侵入式进行的。这几项NIR测量值使调查洗碗过程的动力学变得困难。在这项研究中，提出了一种新的在线跟踪测量系统的开发，测试和使用。后者用于执行38个洗碗过程，每个过程包含51个NIR光谱，使用带有交叉验证的偏最小二乘回归方法开发校准模型。这种基于校准的新型在线跟踪测量系统可以在自动洗碗过程中确定洗碗液中三种不同土壤成分的浓度。通过记录51个光谱，可以显示每个土壤成分的跟踪曲线，即洗碗过程中浓度随时间变化的过程。这样可以显着提高时间分辨率，并且有可能研究跟踪曲线的第一个动态部分，即洗碗过程的开始。这可能导致有机会根据第一步中检测到的浓度来更改洗碗机的状态，其次，