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Organized Oral Session

Session: : Integrating Light Spectra to Understand the Causes and Consequences of Variation in Plant Function Across Biological Scales

OOS 51-6 - Spectral Phenotyping of Plant Physiology with T-SWIFT: a Tower-Spectrometer on Wheels Investigating Frequent Timeseries

Thursday, August 10, 2023
9:15 AM – 9:30 AM PDT
Location: 254
Proximal remote sensing offers a powerful tool for high-throughput phenotyping of plant physiology across both time and space. While some optical remote sensing approaches (solar-induced fluorescence (SIF) and hyperspectral reflectance) are rapidly growing in popularity, their adoption has introduced a unique set of challenges and uncertainties, . This is particularly true when looking at finer spatial (e.g., photosystem, chloroplast, leaf, branch, tree) and temporal (seconds->days) scales. We synthesize findings on the drivers of optical remote sensing and plant physiological dynamics using a custom built scanning tower-based hyperspectral instrument called T-SWIFT: a Tower-Spectrometer on Wheels Investigating Frequent Timeseries. Using machine learning approaches to interrogate hyperspectral reflectance data, we highlight how these data can be used to track drought resilience across different genotypes and water treatments in bean, poplar, almond and corn. By assessing diurnal and seasonal variability in plant function, we can optically predict real-time changes in stomatal conductance, water potential, and photochemical quenching to inform vegetation monitoring, crop water needs, and breeding population screening.