Hosted by: Angie Burnett

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. In field trials of tobacco with modifications made to the photosynthetic pathway, we infer key photosynthetic parameters from imaging spectroscopy using a partial least squares regression technique. We used two hyperspectral cameras with resolution 2.1nm in the visible range and 4.9nm in the NIR. Ground-truth measurements from leaf-level photosynthetic gas exchange, full-range (400-2500nm) hyperspectral reflectance and extracted pigments support the model. The results from a range of wild-type cultivars and from genetically modified germplasm offer a high-throughput screening tool for crop trials aimed at identifying increased photosynthetic capacity.