The third eye sees more - more efficient plants and more environmentally friendly food productionCategory: Research
The 21st century faces great challenges for the food security: The world population continues to grow steadily, while dwindling resources and the effects of climate change make it increasingly difficult to meet the food demand of people worldwide. One strategy to meet these challenges is to increase crop yields. But new innovative technologies are needed for both plant breeding and sustainable cultivation.
A team at the Chair of Plant Nutrition at the TUM School of Life Sciences Weihenstephan is therefore researching how optical sensor technology, known as "high-throughput phenotyping", can sustainably increase yields in agriculture. "We use ground-based sensor systems, drone and satellite data for this," says Prof. Urs Schmidhalter, head of the Chair of Plant Nutrition. "The latest research results show that important plant performance characteristics and physiological processes in field trials and in the cultivation of crops can be measured quickly and non-invasively in this way" adds Prof. Schmidhalter.
These innovative techniques help to assess the yield performance of plants quickly and cost-effectively in very early selection cycles of plant breeding. Important physiological characteristics, such as the nitrogen use efficiency and drought tolerance of the plants, can also be assessed in field trials. Furthermore, with artificial intelligence, it is possible to process the huge amounts of data.
"This type of data acquisition will not only become important in the future in breeding, but also already offers great potential in the sustainable cultivation of plants, which makes it possible to use less seeds, pesticides and fertilizers," predicts Schmidhalter.
Jin, X.; Zarco-Tejada, P.; Schmidhalter, U.; Reynolds, M.; Hawkesford, M.; Varshney, R.; Yang, T.; Nie, C.; Li, Z.; Ming, B.; Xiao, Y.; Xie, Y.; Li, S. (2020) High-throughput estimation of crop traits: A review of ground and aerial phenotyping platforms. 2020. IEEE Geoscience and Remote Sensing Magazine. 0-0. 10.1109/mgrs.2020.2998816.
Hu, Y., Knapp, S., Schmidhalter, U. (2020) Advancing High-Throughput Phenotyping of Wheat in Early Selection Cycles. Remote Sensing. 12. 3. 574. 10.3390/rs12030574.
Prey, L.; Hu, Y.; Schmidhalter, U. (2020). High-Throughput Field Phenotyping Traits of Grain Yield Formation and Nitrogen Use Efficiency: Optimizing the Selection of Vegetation Indices and Growth Stages. Frontiers in Plant Science. 10. 10.3389/fpls.2019.01672.
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