The blunt leaf dock/ broad leaved dock (Rumex obtusifolius) is a fast growing, highly competitive and as well as resistant weed. It is endemic to Austria and generally a very common weed in Europe. Rumex obtusifolius prefers nutrient-rich, moist soils. As a light germinator, it spreads easily in patchy plant stands. Its taproot can penetrate compacted, waterlogged and oxygen-poor soil layers to a depth of 2.60 meters. It is considered a pest in agriculture, both in field and pasture, because of its rapid growth, ability to vegetatively propagate from leftover roots and its extensive taproot system. The most important regulation strategy is to prevent dock plants from establishing. If plants are already present in the field, the dock population must be assessed. If there are up to two dock plants per square meter, single-stock measures with pricking out or tilling and reseeding are still helpful. If there are more than two plants per square meter, only uprooting and a dock cure will help. As a further step, it is necessary to adjust the crop rotation. The application of pesticides is possible, however, mechanical removal is preferred. The goal this study is to develop a CNN (Convolutional Neural Network) that is specially trained to identify dock plants and to capture location and position in the field/pasture. RGB photographs (approx. 3000) were collected using an unmanned arial vehicle and handheld cameras from March to August 2021 The obtained dataset contained photographs of different plants in all sizes and forms to include all phenotypes and age difference. The network was also trained to differentiate between whole plants and plant parts such as leaves.
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Weed detection by example “RUMEX OBTUSIFOLIUS“ plants in grassland and field areas from RGB imagery with an DEEP LEARNING algorithm.
Published: 03 January 2023 by MDPI in 9th International Electronic Conference on Sensors and Applications session Sensor Data Analytics
Keywords: CNN;Plant;UAV's;Dock;Weed detection;Annotation;Rumex obtusifolius