## 5 Results
### Reduced Light Quality Index  
The data set used to determine the PPFD is applied here. The channels (as can be seen in Figure 4) can be combined to the desired interval determining the ratios of counts in the red, green, and blue light region, thus providing a measure for determining the RLQI. To examine the approach of adding all color interval channels, a cold-white and a warm-white LED with known emission spectrum were investigated. The experimental data is plotted in Figure 6. The output of each channel is represented as a bar centered at the expected center wavelength of the channel and a width according to the channel's FWHM. The values are taken from the data sheet [23]. The counts are normalized to the highest count number in the data set. The expected spectral emission of the light source is shown by the gray dashed line. It has been reconstructed by a cubic interpolation of data points extracted from the graph in the LED data sheet. The given PPFDs are measured with the  
Figure 5: (**a**) Distribution of the obtained PAR via the LI-190 reference and predicted values of the MLR using data from the AS7341. The recorded data sets are over-represented at low light conditions. (**b**) Residuals of the MLR for each data set. reference sensor and our regression model. The channel counts provide a relatively good representation of the expected spectra. For the cold-white LED (LUXEON C 5700K/90, LUMILEDS), the characteristic peak in the blue wavelength region is visible, as well as the broadband maximum in the red-green area. Similar observations can be made for the warm-white LED (LUXEON C 2700K/80, LUMILEDS). The counts in the blue region are reduced and the broadband peak is red-shifted. The warm-white LED's RLQI was determined to be 43%-47%-10% (red-green-blue), with a maximum absolute deviation of 6% from the expected distribution. For the cold-white LED, an RLQI of 35%-45%-20% (r-g-b) was measured. Here, the deviation is in the range of 13% points. This is caused by the sensor channels sensitive in the blue interval, which seem to under-represent the narrow peak in the blue of the 5700 K LED spectrum. In addition, no spectral analysis of the used light sources was performed; therefore, we rely only on the accuracy of the data sheet. Nonetheless, in our opinion this is enough evidence that the principle for determining the RLQI can be applied in the field. To provide a first demonstration, the PPFD was measured in the case of an open blue sky (15 September 2020, in Rheinfelden, Germany, see Figure 7a) and under some leaves (Figure 7b) with comparable ambient conditions (30 July 2020, in Freiburg, Germany). The RLQI changes visibly from 29.8%-40.6%-30.6% (r-g-b) under blue sky to a spectrum where the blue part is reduced with respect to the green and red region, resulting in 34.4%-45.4%-20.2% (r-g-b). This shows that there is a definite loss in information of the spectral distribution if only the PAR is considered for plant growth and photosynthesis estimation in different illumination scenarios. The light quality may also vary during the day, with changing weather conditions and may even be different at various canopy levels in the vegetation or plantation. For the clear sky scenario, our measured light quality can also be compared to a the results of [PERSON] et al. [6], who performed a light quality measurement with a spectrometer in Basel (less than 75 km from our measurement site). The blue fraction ranges from 27 % to 40 %, green from 31 % to 35 %, and red from 27 % to 39 %. These values were measured for different solar angles that were heavily influencing the relation of red and blue fractions of the spectrum. Comparing the values in Figure 7a) to this, it is obvious that the green fraction is higher than expected. The measurement of blue and red parts are within the ranges measured by [PERSON] et al. Therefore, the proposed RLQI can provide some deeper insight in the spectral distribution of the incident light, while measuring the PPFD.