Improved photosynthetic rates have been shown to increase crop biomass, making improved photosynthesis a focus for driving future grain yield increases. Improving the photosynthetic pathway offers opportunity to meet food demand, but requires high throughput measurement techniques to detect photosynthetic variation in natural accessions and transgenically improved plants. Gas exchange measurements are the most widely used method of measuring photosynthesis in field trials but this process is laborious and slow, and requires further modeling to estimate meaningful parameters and to upscale to the plot or canopy level.
Results/Conclusions
In field trials of wild type, and genetically engineered tobacco with both decreased Rubisco and overexpressed photosynthetic carbon reduction cycle enzymes, we measured photosynthesis under a wide range of meteorological conditions. We were able to predict the carboxylation rate of Rubisco (Vcmax) with R2= 0.66 and electron transport rate (J) at R2 = 0.57, and detect photosynthetic variation from high throughput hyperspectral analysis using a partial least squares regression technique. Ground-truth measurements from photosynthetic gas exchange, a full spectrum (400-2500nm) hyperspectral leaf clip, hyperspectral indices, and extractions of leaf pigments support the model.
The results from a range of wild-type cultivars and from genetically modified germplasm suggest that the opportunity for rapid selection of top performing genotypes from among thousands of plots. This research creates the opportunity to extend agroecosystem models from simplified “one-cultivar” generic parameterization to better represent a full suite of current and future crop cultivars for a wider range of environmental conditions.