It was
demonstrated that by the use of time-resolved measurements quaternary mixtures
can be quantified, which were measured by sensor setups employing less sensors
than analytes to be quantified. Thereby the 1-sensor SPR setup practically achieves
the same results than the RIfS array using 3 sensors, whereas the evaluation
of single RIfS sensors showed worse results than the SPR setup. The evaluation
of single time points of the 3-sensor RIfS setup, which corresponds to the common
static sensor evaluation, showed unacceptably bad results, as the data analysis
was mathematically underdetermined (3 sensor responses for 4 analytes). This
demonstrates how the principle of time-resolved measurements can help to reduce
the number of sensors and thus the hardware costs. The principle allows the
quantitative determination of systems, which would never have been quantified
using static measurements. Similar to section 9.3, it
was demonstrated that the influence of smoothing the time-resolved sensor responses
is two-sided. Smoothing of very noisy sensor responses of thin sensitive layers
improves the calibration whereas smoothing of sensor responses with a high signal
to noise ratio adversely influences the calibration. Additionally, it was demonstrated
once more that the frameworks introduced in this work help to improve the multivariate
calibration of the sensor signals of all data sets investigated.