From the lab to the world: solving big problems in agriculture and energy
- The Kramer lab has unveiled a sophisticated, user-friendly, and cheap scientific instrument to measure plant health and photosynthesis parameters.
- It solves the problem that scientists still lack the ability to measure plant performance in the real world. Current technology with that ability is expensive and difficult to use.
- Collected data is uploaded to an online platform and is available for anyone who joins: plant scientists, citizen scientists, farmers, and breeders.
- The Kramer lab is using the collected data (over 425,000 data sets from over 28 countries, to date) to understand how to improve plant yields.
“We are in trouble,” says David Kramer, Hannah Distinguished Professor in Photosynthesis and Bioenergetics at the PRL. “Our crops are not keeping up with our population. In fact, in some cases we are falling behind. And we need plants for all our food and much of our fuels. The problem is that arable land is not increasing, but our population and our lifestyles are demanding more from our farms. Even more urgently, the climate is changing.”
Although there have been recent leaps in understanding plants’ chemical and genetic make ups, what really holds us back to improving plants is the ability to accurately measure how they perform in the real world, where they face stress, disease and other factors that cannot be replicated in laboratories.
“We need to peer inside the living plant and see how things work, which components are working better, and why they fail. Once we can do this, we can figure out what genes are controlling performance so we combine them to make crop varieties that perform better.”
Although some technologies currently can do all that, they are prohibitively expensive and difficult to use, placing them out of reach to all but the richest companies, institutions, and governments.
MultispeQ: a game changer
A team of researchers led by Kramer – including scientist and first co-author Sebastian Kuhlgert, engineer Robert Zegarac, software expert Prabade Weebadde, and open-source science leader Greg Austic – held a series of brainstorming sessions to imagine a new technology to reach a wider user base, like plant scientists wanting to breed superior plants or farmers needing to better manage their land.
“We mapped out the reasons why current technology wasn’t widely available, from high instrument cost, to the complexities of gathering and understanding complex data generated by such instruments, to the ability to compare the data to crop genetics and field conditions.”
“We also wanted the data to be publicly available, meaning we had to teach users around the globe how to use the technology.”
The result, published in the journal Royal Society Open Science, is the newly unveiled MultispeQ, a sophisticated, portable, and user-friendly scientific instrument that overcomes many of the major limitations of currently available instruments. It comes at less than 10% of the cost of available technologies.
The MultispeQ makes non-invasive measurements of parameters related to plant productivity and health, including a range of environmental factors (light intensity and quality, temperature, relative humidity), leaf pigmentation (chlorophyll, anthocyanin) and various photosynthetic parameters based on static or light-driven fluorescence yield and absorbance changes.
The tech shines with its user interface. The device automatically guides users to make the right measurements and then wirelessly transmits the results to a cloud-based data sharing platform, called PhotosynQ.
To date, beta users have captured over 425,000 data sets, in over 1,500 projects, and in around 28 countries. And similarly to social media platforms, data is accessible to anyone who joins the open-source platform, opening up synergistic opportunities for collaboration.
Take the project between Marty Chilvers, a field crops pathologist, and the Kramer lab, interested in photosynthesis: Marty researches soilborne root rot diseases that rob yield but that often have no obvious symptoms above the ground, making early disease detection crucial.
In one project, Marty’s team set the trial up, and the Kramer lab came in to take the measurements.
“The platform allowed multiple people from different fields to look at the numbers in ways that we may not have had thought of, adding value to the data,” Marty says. “And while we were interested in how the parameters predicted plant health and soybean sudden death syndrome caused by root rot, the Kramer team used the same data set to analyze photosynthetic performance.”
A gateway to improving plant yields
The Kramer lab’s particular interest in these massive data sets is to understand plant performance in their natural environements in order to improve plant yield.
And insights are flowing in.
“There are strong indicators that these data can predict crop yield at early stages of plant growth,” David says. “We can also catch disease at very early stages, when it is still not apparent to the eye. We can measure plant stress levels.”
But, ultimately, David thinks the secret lies in improving photosynthesis, an area plant breeders have yet to address. And his team believes that, to their knowledge, the technology is giving them an unprecedented look at how photosynthesis works in the wild, at such a large scale.
“Research is showing that photosynthesis is rather inefficient – plants lose energy during the process. If we understand where those losses happen, we could potentially breed more efficient plants or create artificial photosynthetic systems that do the job better. Already, we have worked with Zambian research collaborators to identify stretches of DNA that improve bean photosynthesis performance under their local conditions.”
The team is looking to expand its user base to include researchers, growers, and citizen scientists for community-driven plant research, removing barriers that have prevented these stakeholders from collectively understanding the basic biology needed to improve plants on the ground.
The MultispeQ is now out of beta. For more information, visit www.photosynq.org. This work is made possible by funding from the Department of Energy Office of Science, Basic Energy Sciences, the McKnight Foundation, and USAID.
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