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In order to improve world food conditions, a team around computer science professor Kristian Kersting was inspired by the technology behind Google News.
Almost 800 million people worldwide suffer from malnutrition. In the future there could be around 9.7 billion people—around 2.2 billion more than today. Global demand for food will increase as climate change leaves more and more soil infertile. How should future generations feed themselves?
Kersting - Professor - Machine - Learning - Technische
Kristian Kersting, Professor of Machine Learning at the Technische Universität Darmstadt, and his team see a potential solution in the application of artificial intelligence (AI). Machine learning, a special method of AI, could be the basis for so-called precision farming, which could be used to achieve higher yields on areas of equal or smaller size. The project is funded by the Federal Ministry of Food and Agriculture. Partners are the Institute of Crop Science and Resource Conservation (INRES) at the University of Bonn and the Aachen-based company Lemnatec.
"First of all, we want to understand what physiological processes in plants look like when they suffer from stress," said Kersting. "Stress occurs, for example, when plants do not absorb enough water or are infected with pathogens. Machine learning can help us to analyse these processes more precisely." This knowledge could be used to cultivate more resistant plants and to combat diseases more efficiently.
Researchers - Camera - Broadwave - Spectrum - Insights
The researchers installed a hyperspectral camera that records a broadwave spectrum and provides deep insights into the plants. The more data available on the physiological processes of a plant during its growth cycle, the better a software is able to identify recurring patterns that are responsible for stress. However, too much data can be a problem, as the calculations become too complex. The researchers therefore need algorithms that use only...
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