## 2 Materials and Methods
### Data Processing and Analysis

Table 2: Reflectance indices indicative of corn growth, chlorophyll content, and level of photosynthesis. MoniPAM, Flux, and FLoX closely matched. As result of the processing, the three data sets (Figure 2) were merged into one, containing measurements covering the period from 8:15-17:45 (\(\leq\)20 per day), at consistent 30 min time intervals and with matching PAR levels. To avoid artifacts in the data due to lower solar illumination angels at the site, the measurements collected at 8:15, 17:15, and 17:45 were excluded from the analysis, living the time period of 8:45-16:45 (i.e., 17 observations per day). The time period for which we have data from all three instruments in 2017 covers from day of year (DOY) 192 to DOY 273 (i.e., July 11 to September 29, 2017, Figure 2). During DOYs 210-220, the FLoX system was deployed for tower measurements of diurnal SIF, in support of the 2017 NASA airborne SIF acquisitions at the Smithsonian Research Center (SERC) in Edgewater, MD. Nevertheless, the 2017 dataset includes measurements representative of the major corn growth stages (58 days total). We identified the distinct growth stages based on Phenocam records [53], the variation in canopy GPP, leaf quantum yield of photosystem two (i.e., YII), and the reflectance VIs (FLoX), as indicated in Figures 1-3. The young (Yn) growth stage was identified by the pattern of increase in the reflectance indices NDVI and Clred, as seen in early July (Figures 2 and 3), and covers the corn vegetative period. Upon reaching maximal YII, NDVI, and Clred values (DOY 192-209, July 11-28), we defined the mature corn stage (M, DOY 220-235, August 8-22), which includes the corn initial reproductive phases. Finally, the early and late senescence stages (S1 and S2) displayed a sharp decrease in GPP, YII, and Clred from August 23 through September 30 (DOY 236-273). To compare the diurnal and seasonal variation in the observations and statistically evaluate the strength of the relationships of the optical metrics to photosynthetic activity, and their dependence upon the time of collection and growth stage, we selected three representative days free of clouds within each growth stage (12 days, 17 observations/day), as follows: young (Yn, DOY 192-194), mature (M, DOY 222-224), early senescence (S1, DOY 245-247), and advanced senescence (S2, DOY 255-257). Frequently, remote sensing parameters saturate and underperform, and are not transferable across a phenology. To allow for scaling using remote sensing metrics (i.e., SIF), a linear relationship with the parameter of interest (i.e., GPP and LUE) is desired. The relationships between GPP, LUE, and the fluorescence and reflectance metrics were investigated using linear regression analysis, and the established correlations are shown in Figures 6 and 7. The strength of the relationships is indicated by listing the coefficients of determination (i.e., R\({}^{2}\), percentage of explained variation in the dependent variable) in corresponding colors according to growth stage. The overall coefficient of determination is listed in black when the relationship was statistically significant (\(p<0.01\)). The diurnal measurements were sub-selected further to form categorical variables representative of the three distinct periods during the day: morning (am, 8:45-10:15), noon (11:45-1:15), and afternoon (pm, 15:15-16:45) local time (EDT or UTC-4, 12 observations per day, 144 observations). The seasonal changes in the diurnal profiles of the observations are shown in Figures 4 and 5, where each value represents a mean of the measurements collected at this time on three consecutive clear days, representative of each growth stage, as indicated by different colors (blue--young, green--mature, red--early senescence, yellow--late senescence). The trends in the data are depicted using best fit lines (i.e., linear or polynomial).