Postdoc Oak Ridge National Laboratory Oak Ridge, Tennessee
Body of Abstract: We rapidly need solutions to scale the impacts of environmental stress across levels of biological organization. Technological advances have enabled the growing use of hyperspectral imaging to predict plant growth traits and function. This technology has benefits over traditional measurements as it can assess plant traits without destructive harvesting or labor-intensive measurements. Spectral wavelengths have been correlated with estimates of important physiological characteristics such as leaf pigments, leaf mass per area, plant nitrogen, and the rates of the biochemical reactions of photosynthesis. However, accuracy of such predictions across variable nutrient conditions is not well characterized. Therefore, we took hyperspectral images and measured a suite of plant anatomical, biochemical, and physiological traits of Populus trichocarpa grown across multiple nitrogen treatments. We found expected nutrient related results such as Rubisco carboxylation, photosynthetic electron transport, chlorophyll a/b, and protein content all increased with nitrogen. Total plant protein [coefficient of determination (R2) = -0.11; where a negative value indicates that the partial least squares regression residual sum of squares exceeds the total sum of squares] Rubisco content (R2 = 0.07), and chlorophyll content (R2 = -0.09) were not predicted well via hyperspectral imaging. Many plant gas exchange traits such as the photosynthetic light compensation point (R2 = -0.31) and the maximum rate of Rubisco carboxylation (R2 = 0.16) were not well predicted by imaging; while other gas exchange traits, such as light saturated photosynthesis (R2 = 0.26) and the rate of photosynthetic electron transport (R2 = 0.44) were slightly better predicted by hyperspectral imaging. Ultimately, these data will be used to discover resilience genes and establish a gene-to-trait-to-spectra relationship methodology that can be expanded to other species and across levels of biological organization for resilience assessment.