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KibEZ - AI-based yield determination of sugar beets (KibEZ)
Project
Project code: EIP-Agri-2022-Ni-PPGDB
Contract period: 01.01.2022
- 31.12.2024
Budget: 457,988 Euro
Purpose of research: Applied research
Keywords: plant production and horticulture, fertilisation, soil
Savings in fertilizing applications due to yield mapping and in transport activities due to precise information on beet mass are the leading motivation of KibEZ. Currently, precise yield mapping has not yet been possible in sugar beet cultivation. Ultrasonic sensors record the fill level of the beet tank, but these can only estimate the volume of the sugar beets. The KibEZ project tests artificial intelligence (AI) based solutions that are intended for long-term use on different types of machines by various manufacturers. Machine parameters and further measurements, such as power consumption of cleaning elements and soil type, are used as inputs for the AI. To draw the right conclusions and derive accurate yield maps, the AI must be trained in the correct processing of the input data through multiple calibration and training sessions. The TU Braunschweig integrates the expert knowledge of a beet lifting community, a machinery manufacturer, a farmer, and the Chamber of Agriculture as well as the test results into the artificial intelligence.
Section overview
Subjects
- Crop Production
- Process engineering
- Computer science
