*3.2. Hyperspectral Setup Optimisation*

Figure 3 shows the normalised SNR values for a potato and a leek canopy for each of the measurement setups.

Each dataset was normalised (after SNR calculation) using the formula (x-min)/range, which leads to values between 0 and 1. It can be observed that different setups lead to different SNR values. The highest SNR value in the potato crop was obtained with an off-zenith angle of 8◦, a height above crop canopy of 70 cm and an ET of 50 ms. A close second was the setup of an 8◦ angle, a height of 110 cm and an ET of 50 ms. For leek, the best SNR was achieved with an angle of 17◦, a height of 70 cm and an exposure time of 50 ms. Examining the SNR values of the potato, a clear trend of stepwise increasing SNR values with increasing ET could be observed. This differed from the leek SNR values, which showed no clear trend. Figure 4 shows the PCA variables factor map plots on the plane formed by PC1 and PC2, and PC1 and PC3, respectively, for hyperspectral measurements of a potato crop. The plot on the plane formed by PC2 and PC3 showed no representation of the SNR vector, so it has been omitted. It can be seen on the axes that PC1 represented 48.67% of the total variance in the data, while the second and third PCs represented 25% of the variance each. The height vector was perpendicular to the SNR vector in the PC1–PC2 plane, indicating that height did not significantly affect SNR for the potato crop. This was confirmed by the plot of PC1 and PC3, where SNR was

fully represented by a long vector, as opposed to height, which was not represented in this plane (indicating it is perpendicular to this plane). The angle and SNR showed no relation in the plot of PC1 and PC2, because angle was not represented in this plane. Looking at the projection on the plane of PC1 and PC3, it can be seen that the angle vector had a projection that was almost perpendicular to the SNR vector. This indicates that SNR was not closely related to camera angle for potatoes. The last variable, ET, was almost entirely congruen<sup>t</sup> with the SNR vector in both the plot on the PC1 and PC2 plane and the PC1 and PC3 plane. This indicated that for potato crops, SNR was mostly influenced by ET. Figure 5 shows the PCA variables factor map plots for hyperspectral measurements of leek for the PC1 and PC2 plane, and the PC1 and PC3 plane. The plot on the plane formed by PC2 and PC3 again showed no representation of the SNR vector, so it has been omitted. It can be seen that the first PC represented 36.75% of the total variance in the data, while the second and third PCs represented 25% of the variance each. In these plots, we saw that the relationship between SNR and the other variables was not as clear-cut compared to those of the potato canopy. Comparable to the potato canopy data, the projections of the angle vector were not concurrent with the leek SNR vector on either the PC1 and PC2 plot or the PC1 and PC3 plot. The projection of the height vector in this case seemed to indicate a more significant, negative relation to SNR compared to the potato dataset. ET again seemed to have a significant positive correlation with SNR. This positive correlation with ET was also observed in the SNR values in Figure 3, especially for potato scans. For leek scans, the SNR values are more variable, but still high ETs seemed to correspond to higher SNR values.

**Figure 4.** Principal component analysis (PCA) variables factor map plots of a potato canopy, showing the projection on principal components (PC1 and PC2) (top) and PC1 and PC3 (bottom). The projection of each variable vector on the axis formed by the signal-to-noise ratio (SNR) vector gives an indication of the relation of this variable to SNR.

**Figure 5.** Principal component analysis (PCA) variables factor map plots of a leek canopy, showing the projection on PC1 and PC2 (top) and PC1 and PC3 (bottom). The projection of each variable vector on the axis formed by the signal-to-noise ratio (SNR) vector gives an indication of the relation of this variable to SNR.

### *3.3. E*ff*ect of Artificial Lighting on Hyperspectral Measurements of a Crop Canopy in the Field*

Figure 6 shows the average reflectance curves for the scans of a leek row, with artificial light on/off under sunny and cloudy conditions. The curve related to sunny conditions (Figure 6A) showed that although measurements were taken on an exceptionally sunny day (for winter conditions), the lamps still contributed to reflectance. This is in contrast with the results under cloudy conditions (Figure 6B), in which it can be observed that the added illumination apparently decreased reflectance values, especially in the NIR range. The normalized reflectance curves of the on/off treatments were less similar to each other during cloudy conditions compared to sunny conditions (Figure 6C,D). The normalized reflectance curves of the sunny condition experiment appeared very similar in the visible region of the spectrum, while the cloudy conditions curve showed differences, especially in the red colour region of the spectrum (600–680 nm). In the NIR region, the on/off curves of under sunny conditions are inconsistent. During cloudy conditions, the light-on-treatment's reflectance curve is consistently below that of the off-treatment in the NIR region, up to +/-930 nm, after which differences are inconsistent. A depression in the reflectance curve appeared around 950 nm, for cloudy conditions, which did not appear for sunny conditions for both the raw and normalised spectra.

Looking at the increased reflectance of the white reference as a result of switching on the light under sunny conditions (Figure 7A), a mild increase can be seen more or less uniformly over the entire spectrum, with a bigger increase in the middle part of the spectrum compared to the edges at 400 and 1000 nm. It is clear that the halogen lights cause a reflectance pattern that is very similar to the natural light conditions. However, looking at the cloudy white reference reflectance data (Figure 7B), the additional lighting appeared to mainly increase the reflectance values at higher wavelengths, with the largest increase again occurring in the middle part of the spectrum. However, in cloudy conditions, the difference between the light on and light off for white reference curves is much more significant, both in terms of shape of the curve and magnitude of reflectance (Figure 7B). The white

reference reflectance curve without artificial light was less bell-shaped and more skewed under cloudy conditions (Figure 7B) compared to that without artificial lights under sunny conditions (Figure 7A), indicating the effect of cloud cover on the reflectance spectrum.

**Figure 6.** Average reflectance curve of a leek canopy with artificial light (two 500 W halogen lamps) on (dashed blue line) and light off (full green line) scenarios under sunny (**A**) and cloudy (**B**) weather conditions. Normalised spectra plots also shown for sunny (**C**) and cloudy (**D**) conditions.

**Figure 7.** White reference signal curve with artificial light (two 500 W halogen lamps) on (green line) and lights off (blue line) scenarios under sunny (A) and cloudy (B) scanning conditions. Raw sensor signal is shown.

### *3.4. E*ff*ect of Artificial Lighting on Thermal Measurements of a Crop Canopy in the Field*

Figure 8 compares thermal images measured in conditions with and without artificial light, under sunny (8.1) and cloudy (8.2) conditions.

**Figure 8.** Figure 8.1 shows thermal images of a leek ridge in the middle of the row (Figure 8.1A,C) and at row edge (Figure 8.1B,D). Scans were taken during cloudless, sunny conditions, with additional lighting (Figure 8.1A,B) and in natural light (Figure 8.1C,D). Figure 8.2 shows thermal images taken on a cloudy day, comparing lights on (Figure 8.2A) with lights off (Figure 8.2B). Red circles indicate the areas studied for comparison of hot spot formation. Rightmost red circles of Figure 8.2 (A and B) show the bend of a leaf, which shows up as a hot spot due to physical damage caused by the bending/cracking of the leaf.

Comparing Figure 8.1B,D with Figure 8A,C, it can be seen that the ridge at the edge of the row was slightly slanted, causing it to receive less radiation, which resulted in a decreased average temperature measured in these frames (Figure 8B,D). It can further be observed that the prolonged exposure to the halogen lights at the row edge caused a temperature increase in the top parts of the crop canopy, which is closest to the lamps (Figure 8.1B). This leads to 'hot spots' that were not necessarily related to disease or other types of plant stress, since no disease appeared during the weeks following measurement and the hot spots appeared only after the halogen lamps were turned on. There was no clear formation of hot spots in the middle of the crop row during the light-on treatment (Figure 8A,C). The temperature difference seemed to mainly stem from absorption of radiation by the soil. Figure 8.2 shows the effect of additional lighting during cloudy conditions. This measurement was later in the growing season, when dense weed cover started appearing on the ridges. It is clear from the thermal images that weeds significantly affect measured temperature patterns, as weed temperature was cooler than that of the soil but generally hotter than the leek. No apparent average temperature increase was observed when switching on lights, considering the entire thermal image, with even some minor temperature decrease. The red circled areas on Figure 8.2A show that during this measurement, the artificial light caused hot spots even during movement of the sensor box. This was repeatedly observed in different locations throughout the measured leek rows. These hotspots seemed to be located around sharp bends in the leaves or on lower leaves, which were older and decaying. Looking at healthy leaf tissue (areas outside the red circles), there was no effect of additional light, even on parts of the leek crop that were higher compared to the hotspots. Figure 9 shows the average temperature measured over two rows of leek plants, in conditions with and without artificial lights. There was approximately a 1 ◦C increase in average temperature due to the addition of artificial light, during sunny conditions. The images taken in the middle of the crop row (image series number 4–8) showed a higher average temperature compared to those at the row edge.

**Figure 9.** Average T calculated over a series of thermal images captured over two leek crop rows under sunny conditions. Images captured with (on) and without (off) artificial light. Background soil temperature was lower compared to leek temperatures, meaning that lower temperatures correspond to areas with relatively few leek plants, while higher temperature corresponds to the centre of the leek row.
