The inverse relationship between solar-induced fluorescence yield and photosynthetic capacity: benefits for field phenotyping

Improving photosynthesis is considered a promising way to increase crop yield to feed a growing population. Realizing this goal requires non-destructive techniques to quantify photosynthetic variation among crop cultivars. Despite existing remote sensing-based approaches, it remains a question whether solar-induced fluorescence (SIF) can facilitate screening crop cultivars of improved photosynthetic capacity in plant breeding trials. Here we tested a hypothesis that SIF yield rather than SIF had a better relationship with the maximum electron transport rate (J(max)). Time-synchronized hyperspectral images and irradiance spectra of sunlight under clear-sky conditions were combined to estimate SIF and SIF yield, which were then correlated with ground-truth V-cmax and J(max). With observations binned over time (i.e. group 1: 6, 7, and 12 July 2017; group 2: 31 July and 18 August 2017; and group 3: 24 and 25 July 2018), SIF yield showed a stronger negative relationship, compared with SIF, with photosynthetic variables. Using SIF yield for J(max) (V-cmax) predictions, the regression analysis exhibited an R-2 of 0.62 (0.71) and root mean square error (RMSE) of 11.88 (46.86) mu mol m(-2) s(-1) for group 1, an R-2 of 0.85 (0.72) and RMSE of 13.51 (49.32) mu mol m(-2) s(-1) for group 2, and an R-2 of 0.92 (0.87) and RMSE of 15.23 (30.29) mu mol m(-2) s(-1) for group 3. The combined use of hyperspectral images and irradiance measurements provides an alternative yet promising approach to characterization of photosynthetic parameters at plot level.

Automated summary

The combination of time-synchronized hyperspectral images and irradiance spectra can provide a better estimation of SIF and SIF yield, which exhibit a negative correlation with photosynthetic variables. Using SIF yield for J(max) (V-cmax) predictions, the regression analysis demonstrates varying levels of accuracy and RMSE for different groups.