## 3 Results
### Correlations between Diurnal Sets of Observations across Corn Growth Stages  
The linear relationships between canopy photosynthetic activity (i.e., GPP) and the optical metrics are shown in Figures 6 and 7, where the strength of relationships is indicated by the coefficients of determination (R\({}^{2}\), percentage of explained variation in the dependent variable) in colors corresponding to the growth stage. The overall coefficient of determination is listed in black only when the relationship was statistically significant (\(p<0.01\)). The correlation between GPP and YII was negative (Figure 6A), while positive linear relationships with GPP were established for ETR (Figure 6B), APAR (Figure 6C), and the SIF metrics (Figure 6D-F). Stronger correlations emerged between GPP and the observations collected during the young and mature stages. The relationships between observations from the S1 and S2 stages maintained linearity, however, the relationships were not statistically significant (\(p>0.01\)). The correlation between GPP and YII (Figure 6A) grouped the observations from the young and mature stages, separating them from those from both S1 and S2 stages. Strong overall correlations with GPP were established for \(\mathrm{SIF_{A}}\), \(\mathrm{SIF_{B}}\), and \(\mathrm{SIF_{A+B}}\) (Figure 6D-F), grouping the observations from all growth stages together, thus providing the potential for estimating GPP using a generalized (i.e., common) relationship across all growth stages. Overall, the highest correlation emerged between GPP and \(\mathrm{SIF_{A+B}}\) (R\({}^{2}\) = 0.78, Figure 6F), with the strongest association identified between observations from the mature growth stage (R\({}^{2}\) = 0.80, Figure 6F), followed by the correlation between the observations from the young stage (R\({}^{2}\) = 0.78). Using observations from the young stages, the strongest correlations were established between GPP and \(\mathrm{SIF_{A}}\) (R\({}^{2}\) = 0.79, Figure 6E). Comparing the correlations between observations from the mature stage, GPP was strongly correlated with \(\mathrm{SIF_{B}}\), followed by \(\mathrm{SIF_{A+B}}\), \(\mathrm{SIF_{A}}\), YII, and ETR (i.e., R\({}^{2}\) = 0.82, Figure 6D; R\({}^{2}\) = 0.80, Figure 6F; R\({}^{2}\) = 0.78, Figure 6E; R\({}^{2}\) = 0.77, Figure 6A; R\({}^{2}\) = 0.71, Figure 6B; respectively). During the young stage, the correlation between GPP and \(\mathrm{SIF_{B}}\) explained a slightly larger proportion of the variation in GPP as compared to APAR (R\({}^{2}\) = 0.79 vs. R\({}^{2}\) = 0.77, respectively). During the young and mature stages, \(\mathrm{SIF_{A}}\) and \(\mathrm{SIF_{A+B}}\) explained a larger percent of the variation as compared to APAR, with \(\mathrm{SIF_{A+B}}\) providing the stronger correlations (Figure 6F). Negative linear relationships were established between YII and the SIF metrics (Figure 7A-C), explaining an equally large amount of the variation in SIF\({}_{\rm A}\) and SIF\({}_{\rm A+B}\) during the young and mature stages (Figure 7C, R\({}^{2}\) = 0.63 and R\({}^{2}\) = 0.84, respectively). The strength of these correlations was most pronounced for the observations from the mature stage (green points in Figure 7A-C). The linear regressions between YII and SIF\({}_{\rm A}\) and SIF\({}_{\rm A+B}\) clearly separated the observations collected during the senescent stages from those collected during the young and mature stages. The strength of the correlations between YII and SIF\({}_{\rm B}\) and the slopes of the relationships differed with growth stage (Figure 7B). Positive linear relationships were established between ETR and SIF (Figure 7D-E), with the highest amount of the variation in the data explained for the SIF\({}_{\rm B}\) observations from the mature stage (Figure 7E, green, R\({}^{2}\) = 0.77).