## 4 Discussion  
The impact of SCN on soybean yield and physiology was evaluated using ground-based information and aerial spectral imagery. Further, ML models were formulated and tested for SY estimation under varied dataset sizes. The blue band (r = \(-\)0.58) and VIs such as GNDVI, GRVI, and GCI (r = \(-\)0.58) were identified to be the best discriminants of  
Figure 6: The Pearson correlation (r) and relative root mean square error (rRMSE) for measured and estimated soybean yields with REFs+VIs as an input group for models validated over (**a**) the train dataset at 95.5, (**b**) test dataset at 50:50, and (**c**) entire dataset at 95.5 splits. Figure 7: Plots showing performances of six soybean yield estimation models through the (**a**) Pearson correlation (r) and (**b**) relative root mean square error (rRMSE) at ten train–test data split ratios and two input groups (REFs, REFs+VIs) when validated over entire, test and train datasets. SCN populations for resistant and susceptible varieties. GNDVI has also been identified as suitable for disease identification in other studies that pertained to SCN and sudden death syndrome in soybean [10] and yellow leaf disease of arecanut [47]. The SCN and vigor correlation on 21 July (r = 0.04) was lower than that on 7 July (r = 0.41) (Table 2) which could be attributed to the development of visible mild symptoms on crop canopy not only due to SCN but also the varied impacts of fungicide treatments, and possibly due to responses to other unmeasured biotic and abiotic stressors. This observation could also be due to the variety response to SCN populations with resistant variety showing a higher vigor and vigor progression. This is consistent with findings by [PERSON] et al. [48] where the beet cyst nematode population multiplication was higher in the susceptible cultivar compared to the tolerant one. Furthermore, the ability of nematode tolerant cultivar to endure nematode damage in the second half of the growing season was shown by no difference in the final shoot biomass [48]. This makes visual scouting of canopies for SCN infestation very challenging [10]. Nonetheless, the positive vigor progression between the two measurement dates as well as relatively lesser SCN populations indicated sufficient availability of water and minimal level of other stressors on the canopy. This aspect is well supported by a study that observed more SCN on the root cortex instead of vascular tissues under adequate soil moisture conditions [10]. SCN population showed a moderate correlation with NDE (r = \(-\)0.5) and yield (r = \(-\)0.4) which likely reflects SCN damage. This could be due to two primary reasons, firstly, the variation in crop vigor not only due to SCN but also the varied impacts of fungicide treatments, and possible responses to other unmeasured biotic and abiotic stressors. Secondly, the SCN assessment using aerial imaging of crop canopy forms an indirect mode of assessment where SCN, in reality, are observed from soil samples. Nonetheless, yield, vigor, and NDE did quantify significant differences for resistant and susceptible varieties. This observation is well supported by [PERSON] et al. [48] who evaluated beet cyst nematode infestation in sugar beets (susceptible and tolerant cultivars) using visible light imaging, thermography and spectrometry. Spectral vegetation indices (NDVI, MCARI2) and CHLG) showed a correlation with yield (R = 0.69) and nematode population in the soil (R = 0.78) for the susceptible cultivar. Several studies have reported that SCN infection reduces photosynthesis rate, chlorophyll content, and plant growth with chlorosis forming the aboveground symptom on the canopy [6]. NDE related to leaf chlorophyll showed strong correlation with the SY for the resistant and susceptible varieties and was consistent with observation that increased SCN damage to the roots results in more visible symptoms on the shoots, and lower yields [8]. This is strongly supported by a negative and significant correlation between the SCN population and yield [49].