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Big data: IPK Investigators double accuracy in predicting wheat Returns

By increasing population sizes, an international team of scientists led by IPK Leibniz-Institute was able to double the prediction accuracy for wheat yield. Credit: IPK/ Christoph Martin The enormous potential of Big Data has already been demonstrated in areas such as financial services and telecommunications. An international team of researchers led by the IPK Leibniz…

Big data: IPK researchers double accuracy in predicting wheat yields
By increasing population dimensions, an international team of scientists headed by IPK Leibniz-Institute managed to double the forecast precision for wheat return. Charge: IPK/ Christoph Martin

The enormous potential of Big Data has already been demonstrated in areas like financial services and telecommunications. An global group of investigators headed by the IPK Leibniz Institute has tapped the potential of large data for the very first time on a large scale for plant study. To this end, data from three jobs were used to increase the predictive accuracy for yield in hybrid varieties of wheat.

“We were able to draw on the largest dataset published to date, which contains information from almost a decade of wheat research and development,” says Prof. Dr. Jochen Reif, Head of the Breeding Research Department in IPK. The results, which could herald a new era for , have been released in the magazine Science Advances.

Finally, data on over 13,000 genotypes tested in 125,000 yield inhabitants were analyzed. For comparison: In a breeding program, are tested in 20,000 yield plots every year. “It was clear to us that we would have to increase the population sizes in order to ultimately develop robust predictive models for yield,” states Prof. Dr. Jochen Reif,”so in this case it was really once:’a lot goes a long way.'” The effort was worth it, he explained. “We were able to double the predictive accuracy for yield in our study.”

The study team used data from both previous projects HYWHEAT (financed by the Federal Ministry of Research and Education) and also Zuchtwert (financed by the Federal Ministry of Food and Agriculture) as well as from an application of this seed manufacturer KWS. Basically, the challenge in such studies is to prepare the data to a uniform quality level and so enable a common analysis. “Since we were responsible for the designs of the experiments from the start, we were able to plan them in such a way that a small proportion of the same genotypes were always tested across the projects, thus enabling an integrated analysis in the first place,” says Prof. Dr. Jochen Reif.

The scientist is strongly convinced that it pays to use Big Data for plant reproduction and research. “We have ultimately worked on the future of all of us,” states the IPK scientist. “We have succeeded in showing the potential of Big Data for breeding yield-stable varieties in times of climate change.”

According to Prof. Dr. Jochen Reif, the present model study has a significance which goes far beyond one crop type and hopefully heralds a cultural shift in breeding. “We were able to show the great benefits of Big Data for plant breeding. However, the possibilities for this are only possible through a trusting cooperation of all stakeholders to share data and master the challenges of the future together.”

Ultimately, this is also the entry point for its use of artificial intelligence (AI). “The effective use of AI als

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