CHAMPAIGN, Ill. (August 24, 2021) — A team from the University of Illinois has developed a model that treats photosynthesis as a dynamic process rather than an activity that either is or is not happening. This allowed the group to examine the impacts of the many fluctuations in light that crop leaves experience due to intermittent clouds, overlying leaves and the sun’s daily passage across the sky. In today’s densely planted crops, these fluctuations are the norm. Lower efficiency of photosynthesis due to slow adjustment to light changes and are estimated to cost up to 40 percent of potential productivity. If crop leaves could be genetically manipulated to adjust more rapidly, then the gain in productivity and efficiency of water-use would be substantial.
Plants use sunlight to generate their food through photosynthesis. When the sun rises each morning, plants must prepare themselves to receive nutrients from the sunlight, which takes time. Decreasing the prep time of plants could hold the key to improving yields in many varieties.
“When light changes, the plants need time to get used to it. It takes time and decreases efficiency,” said Yu Wang, a postdoctoral researcher at Illinois, who led this work for a research project called Realizing Increased Photosynthetic Efficiency (RIPE). “Our goal is in trying to limit the loss during the transition period. We are working to make the plants respond faster to the dynamic light environment.”
RIPE, led by Illinois, is an international research project that aims to increase global food production by developing food crops that turn the sun’s energy into food more efficiently with support from the Bill & Melinda Gates Foundation, Foundation for Food & Agriculture Research and U.K. Foreign, Commonwealth & Development Office.
In this recent study, published in The Plant Journal, RIPE researchers showed that by treating photosynthesis as a dynamic process, they could improve the response time of C4 plants, (plants that use C4 carbon fixation for photosynthesis) such as corn, to adjust more rapidly to fluctuations in light.
First, they validated their model against actual photosynthesis measurements in fluctuating light, which they made in corn, sorghum and sugarcane. They then used their model to predict which steps in photosynthesis limited the response of the process to fluctuations in light in the three crops.