Browsing by Person "Peteinatos, Gerassimos G."

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Agronomic and technical evaluation of herbicide spot spraying in maize based on high-resolution aerial weed maps - an on-farm trial
(2024) Allmendinger, Alicia; Spaeth, Michael; Saile, Marcus; Peteinatos, Gerassimos G.; Gerhards, Roland; Allmendinger, Alicia; Department of Weed Science, Institute for Phytomedicine, University of Hohenheim, 70599 Stuttgart, Germany; (A.A.);; Spaeth, Michael; Department of Weed Science, Institute for Phytomedicine, University of Hohenheim, 70599 Stuttgart, Germany; (A.A.);; Saile, Marcus; Department of Weed Science, Institute for Phytomedicine, University of Hohenheim, 70599 Stuttgart, Germany; (A.A.);; Peteinatos, Gerassimos G.; ELGO-DIMITRA, Leof Dimokratias 61, Agii Anargiri, 135 61 Athens, Greece;; Gerhards, Roland; Department of Weed Science, Institute for Phytomedicine, University of Hohenheim, 70599 Stuttgart, Germany; (A.A.);; Rossi, Vittorio
Spot spraying can significantly reduce herbicide use while maintaining equal weed control efficacy as a broadcast application of herbicides. Several online spot-spraying systems have been developed, with sensors mounted on the sprayer or by recording the RTK-GNSS position of each crop seed. In this study, spot spraying was realized offline based on georeferenced unmanned aerial vehicle (UAV) images with high spatial resolution. Studies were conducted in four maize fields in Southwestern Germany in 2023. A randomized complete block design was used with seven treatments containing broadcast and spot applications of pre-emergence and post-emergence herbicides. Post-emergence herbicides were applied at 2–4-leaf and at 6–8-leaf stages of maize. Weed and crop density, weed control efficacy (WCE), crop losses, accuracy of weed classification in UAV images, herbicide savings and maize yield were measured and analyzed. On average, 94% of all weed plants were correctly identified in the UAV images with the automatic classifier. Spot-spraying achieved up to 86% WCE, which was equal to the broadcast herbicide treatment. Early spot spraying saved 47% of herbicides compared to the broadcast herbicide application. Maize yields in the spot-spraying plots were equal to the broadcast herbicide application plots. This study demonstrates that spot-spraying based on UAV weed maps is feasible and provides a significant reduction in herbicide use.
Precision chemical weed management strategies: A review and a design of a new CNN-based modular spot sprayer
(2022) Allmendinger, Alicia; Spaeth, Michael; Saile, Marcus; Peteinatos, Gerassimos G.; Gerhards, Roland
Site-specific weed control offers a great potential for herbicide savings in agricultural crops without causing yield losses and additional weed management costs in the following years. Therefore, precision weed management is an efficient tool to meet the EU targets for pesticide reduction. This review summarizes different commercial technologies and prototypes for precision patch spraying and spot spraying. All the presented technologies have in common that they consist of three essential parts. (1) Sensors and classifiers for weed/crop detection, (2) Decision algorithms to decide whether weed control is needed and to determine a suitable type and rate of herbicide. Usually, decision algorithms are installed on a controller and (3) a precise sprayer with boom section control or single nozzle control. One point that differs between some of the techniques is the way the decision algorithms classify. They are based on different approaches. Green vegetation can be differentiated from soil and crop residues based on spectral information in the visible and near-infrared wavebands (“Green on Brown”). Those sensors can be applied for real-time on/off control of single nozzles to control weeds before sowing after conservation tillage and in the inter-row area of crops. More sophisticated imaging algorithms are used to classify weeds in crops (“Green on Green”). This paper will focus on Convolutional Neural Networks (CNN) for plant species identification. Alternatively, the position of each crop can be recorded during sowing/planting and afterward herbicides can be targeted to single weeds or larger patches of weeds if the economic weed threshold is exceeded. With a standardized protocol of data communication between sensor, controller and sprayer, the user can combine different sensors with different sprayers. In this review, an ISOBUS communication protocol is presented for a spot sprayer. Precision chemical weed control can be realized with tractor-mounted sprayers and autonomous robots. Commercial systems for both classes will be introduced and their economic and environmental benefits and limitations will be highlighted. Farmers ask for robust systems with less need for maintenance and flexible application in different crops.