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Scientists monitor crop photosynthesis, performance using hyperspectral sensors

28 February 2018 | News
by Ian Michael

A research team led by Guofang Miao, a postdoctoral researcher at the Department of Natural Resources and Environmental Sciences (NRES) at the University of Illinois, USA, have reported on the first continuous field season using sun-induced fluorescence (SIF) data to determine how soybeans respond to fluctuating light levels and environmental stresses. SIF can reveal the plants’ photosynthetic performance throughout the growing season. Their work is reported in Journal of Geophysical ResearchBiogeosciences.

“Photosynthetic performance is a key trait to monitor as it directly translates to yield potential”, said Kaiyu Guan, an assistant professor at NRES and the principal investigator of this research. “This method enables us to rapidly and non-destructively monitor how well plants perform in various conditions like never before.”

“Since the recent discovery of using satellite SIF signals to measure photosynthesis, scientists have been exploring the potential to apply SIF technology to better agricultural ecosystems”, said study collaborator Carl Bernacchi, an associate professor of plant science at the Carl R. Woese Institute for Genomic Biology (IGB). “This research advances our understanding of crop physiology and SIF at a local scale, which will pave the way for satellite observations to monitor plant health and yields over vast areas of cropland.”

During photosynthesis, one to two percent of a plant’s absorbed light energy is emitted as fluorescent light. And that emitted fluorescent light is proportional to the rate of photosynthesis. Researchers capture this process using hyperspectral sensors to detect fluctuations in photosynthesis over the growing season. They designed this continuous study to better understand the relationship between absorbed light, emitted fluorescent light and the rate of photosynthesis. “We want to find out whether this proportional relationship is consistent across various ecosystems, especially between crops and wild ecosystems such as forests and savannas”, said Miao.

“We are also testing the applicability of this technology for crop phenotyping to link key traits with their underlying genes”, said co-author Katherine Meacham, a postdoctoral researcher at the IGB.

“SIF technology can help us transform phenotyping from a manual endeavour requiring large teams of researchers and expensive equipment to an efficient, automated process,” said co-author Caitlin Moore, also a postdoctoral researcher at the IGB. 

A network of SIF sensors has been deployed across the US to evaluate croplands and other natural ecosystems. Guan’s lab has launched two other long-term SIF systems in Nebraska to compare rain-fed and irrigated fields in corn‒soybean rotations. “By applying this technology to different regions, we can ensure the efficacy of this tool in countless growing conditions for a myriad of plants”, said Xi Yang, an assistant professor at the University of Virginia, who designed this study’s SIF monitoring system.

“Our ability to link SIF data at the leaf, canopy and regional scales will facilitate the improvement of models that forecast crop yields”, Guan said. “Our ultimate goal is to monitor the photosynthetic efficiency of any field across the world to evaluate crop conditions and forecast crop yields on a global scale in real time.”

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