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Bringing soybeans into a more favourable light

Illinois researchers investigate transitory shadows to brighten soybean yields

Yu Wang, a post-doctoral researcher (left), and Dr. Stephen Long, professor at University of Illinois, make up part of a team studying the effects of light quality on yield in soybeans.

One phrase often heard when the talk turns to getting more bushels out of a crop is the advice to “control the controllable.” Speakers making presentations use the term as a call for growers to streamline their focus on a select number of management practices. Factors such as planting depth, row width, weed, disease and pest management, varietal selection, fertilizer use and soil analysis can all be monitored and adjusted, according to specific demands in a growing season. But not everything is controllable, and not only weather variables like temperatures and precipitation levels. Now, a team of researchers at the University of Illinois has developed a computer model that can measure changes in the quality of the light that strikes a plant during the course of a day, down to the smallest fraction.

The project is called Realizing Increased Photosynthetic Efficiency (RIPE), sponsored by the Bill & Melinda Gates Foundation, the U.S. Foundation for Food and Agriculture Research (FFAR) and the United Kingdom’s Department for International Development (DFID).

The initial goal of the work in soybeans and other pulses has been to understand — and measure — how much yield may be lost due to the way crops adjust their photosynthetic rates to minute-to-minute fluctuations during cloudy and sunny days.

Dr. Stephen Long and Yu Wang, a post-doctoral researcher, are two of the scientists involved in the RIPE initiative. According to Long, the work dates back to 2003 when research began determining the effect of shadows on light quality. At that time, super-computing facilities at the University of Illinois made the initial work possible, and in 2019, the RIPE team was able to work with an actual soybean crop.

“Lessons from the earlier models led us to genetic changes that should speed adjustment and give crops higher productivity,” says Long, a professor in the University of Illinois’s department of crop sciences. “This was demonstrated with genetically modified tobacco in field tests in 2016. We’re now working on making the same changes in soybean and cowpea. If successful, I expect it will be another six to eight years before this technology is available to farmers.”

The researchers are trying to improve photosynthesis by speeding the rate of photoprotection in soybeans, thereby increasing yield. photo: Supplied

Less is more?

The computer model takes two critical light-based factors into consideration: photoprotection and an enzyme, Rubisco activase. Photoprotection is just what the term suggests — a system for protecting the plant from sun damage. The trouble is, it protects the plant by dissipating excess light energy that otherwise could be used to drive photosynthesis.

Worse, when light levels drop, it can take several minutes or even hours for photoprotection to ease or stop altogether, which increases the yield penalty. If the gap could be cut, however, more photosynthesis would mean more yield.

In research involving tobacco plants, accelerating relaxation increased productivity by 14 to 20 per cent. Even a slightly lower level in soybeans would be substantial — and welcome.

“We found that soybean plants may lose as much as 13 per cent of their productivity because they cannot adjust quickly enough to the changes in light intensity that are standard in any crop field,” says Wang. She adds that soybean is the fourth most important crop in terms of overall production, and it’s the top source of vegetable protein in the world. “Thirteen per cent may not sound like much, but in terms of global yield, this is massive.”

In the past, only hour-by-hour changes in light intensity have been examined. For this study, the researchers developed a dynamic computational ray-tracing model capable of predicting light levels to the millimetre across every leaf, for every minute of the day in a flowering soybean crop. They’re also comparing the predictions with actual measurements that have been made by putting mini-light sensors at random points within soybean field crop canopies.

With the model, Long, Wang and the rest of the team simulated a sunny and cloudy day at the university’s campus in Champaign, Illinois. The most significant limitation of photosynthesis came on the sunny day, and it was because of photo- protection. On the cloudy day, photosynthesis was most limited by short-term photoprotection and the Rubisco activase, which is triggered by light and activated to fix carbon into sugar.

“In the RIPE project, we’re looking at ways both to speed relaxation of photo- inhibition on sun-shade transitions and induction of photosynthesis on shade-sun transitions,” says Long. “We’ve identified genes to up-regulate through bioengineering to accelerate both processes. We’re also looking at variation within existing germplasm to determine if improvement through breeding would be possible.”

And in the long-term…

Long and the team also determined that canopy size and leaf angles have an effect. The model can indicate the benefit that can be obtained from different manipulations — and whether they’d be worthwhile — and can then explore mil- lions more genetic permutations than could be be tested experimentally.

As for the impact of fluctuating light intensities at varying heights of the plant or the effects of higher latitudes (longer day-length at the height of summer), Long states both are potential directions to explore with further research.

“The gene expression modifications we’ve made so far affect all leaves, but there are technologies that could boost expression as leaves become increasingly shaded,” he says, referring to the effect on lower leaves in the canopy.

As for the impact of longer day-lengths at the height of summer in places like Ontario or Manitoba, Long notes sun angles, particularly those that are lower, generally lead to more transitions within the crop canopy. Although they have yet to explore that effect, it is something the computer model can measure.

The potential for this research is far- reaching, adds Long. Together with the National Center for Supercomputing Applications, there is a project at the University of Illinois, funded by FFAR, which aims to represent crop growth processes from gene expression through metabolism to physiology, growth and yield.

“When realized,” says Long, “this will allow an unprecedented exploration of the underlying mechanisms affecting yield and help explore millions of permutations to redesign crops for improved environmental tolerance, sustainability and increased yield.”

This article was originally published in the October 2020 issue of Soybean Guide.

About the author

CG Production Editor

Ralph Pearce



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