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 Institute has now tapped the potential of big data for the first time on a large scale for plant research. To this end, data from three projects 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 at IPK. The results, which could herald a new era for plant breeding, have now been published in the magazine Science Advances.
Finally, data on more than 13,000 genotypes tested in 125,000 yield plots were analysed. For comparison: In a breeding programme, plants 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," says Prof. Dr. Jochen Reif, "so in this case it was really once: 'a lot goes a long way'". The effort was worth it, he said. "We were able to double the predictive accuracy for yield in our study."
The research team used data from the two previous projects HYWHEAT (funded by the Federal Ministry of Research and Education) and Zuchtwert (funded by the Federal Ministry of Food and Agriculture) as well as from a programme of the seed producer KWS. Basically, the challenge in such studies is to prepare the information to a uniform quality level and thus enable a common analysis.
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