Browsing by Person "Spaeth, Michael"

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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.
A comparison of seven innovative robotic weeding systems and reference herbicide strategies in sugar beet (Beta vulgaris subsp. vulgaris L.) and rapeseed (Brassica napus L.)
(2023) Gerhards, Roland; Risser, Peter; Spaeth, Michael; Saile, Marcus; Peteinatos, Gerassimos
More than 40 weeding robots have become commercially available, with most restricted to use in crops or fallow applications. The machines differ in their sensor systems for navigation and weed/crop detection, weeding tools and degree of automation. We tested seven robotic weeding systems in sugar beet and winter oil‐seed rape in 2021 and 2022 at two locations in Southwestern Germany. Weed and crop density and working rate were measured. Robots were evaluated based on weed control efficacy (WCE), crop stand loss (CL), herbicide savings and treatment costs. All robots reduced weed density at least equal to the standard herbicide treatment. Band‐spraying and inter‐row hoeing with RTK‐GPS guidance achieved 75%–83% herbicide savings. When hoeing and band spraying were applied simultaneously in one pass, WCE was much lower (66%) compared to the same treatments in two separate passes with 95% WCE. Hoeing robots Farmdroid‐FD20®, Farming Revolution‐W4® and KULTi‐Select® (+finger weeder) controlled 92%–94% of the weeds. The integration of Amazone spot spraying® into the FD20 inter‐row and intra‐row hoeing system did not further increase WCE. All treatments caused less than 5% CL except for the W4‐robot with 40% CL and the combination of conventional inter‐row hoeing and harrowing (21% CL). KULT‐Vision Control® inter‐row hoeing with the automatic hydraulic side‐shift control resulted in 80% WCE with only 2% CL. Due to the low driving speed of maximum 1 km h−1 of hoeing robots with in‐row elements, treatment costs were high at 555–804 € ha−1 compared to camera‐guided inter‐row hoeing at 221 € ha−1 and broadcast herbicide application at 307–383 € ha−1. Even though the costs of robotic weed management are still high, this study shows that robotic weeding has become a robust, and effective weed control method with great potential to save herbicides in arable and vegetable crops.
Development and testing of a precision hoeing system for re-compacted ridge tillage in maize
(2024) Alagbo, Oyebanji O.; Saile, Marcus; Spaeth, Michael; Schumacher, Matthias; Gerhards, Roland
Ridge tillage (RT) is a conservation practice that provides several benefits such as enhanced root growth and reduced soil erosion. The objectives of this study were to develop an autosteered living mulch seeder and hoeing prototype for RT systems using RTK-GNSS (real-time kinematic global navigation satellite systems) created ridges as a guide. It was also aimed to compare weed control efficacy and crop response of ridge-hoeing compared to conventional hoeing in flat tillage (FT). It was further aimed to investigate the impact of a new RT technology (with ridge re-compaction) on maize root development, yield, soil temperature, and moisture compared to FT. Field experiments were conducted with maize in 2021 and 2022 in a two-factorial split-plot design with tillage (RT and FT) as main treatment and weed control (untreated, herbicide, twice hoeing, hoeing + living mulch) as sub-treatment factors. Weed density, coverage, biomass, crop density, weed control efficacy (WCE) and maize silage yield were assessed. Temperature loggers were installed within RT and FT to take temperature readings at 20 min. Soil moisture and root penetrability were measured every two weeks in each plot using soil samples and a penetrometer. The WCE and yield did not differ significantly between the tillage systems. Twice hoeing resulted in 71–80 % WCE, which was equal to herbicide treatment. Hoeing + living mulch achieved 70–72 % WCE. Different from previous studies with ridge tillage, temperatures in the compacted ridges did not consistently differ from the ridge valleys and flat seedbeds. Root penetration (against 1.4 MPa penetrometer cone index) was 40 % higher in RT than in FT. On average, RT maize produced more (53.6 g m−2) root biomass compared to FT. In summary, re-compacted ridges built along RTK-GNSS lines can allow post-emergent hoeing and living mulch seeding along ridges and also provide good growing conditions for maize.
Development of a sensor-based harrowing system using digital image analysis to achieve a uniform weed control selectivity in cereals
(2021) Spaeth, Michael; Gerhards, Roland
Using intelligent sensor technology for site-specific weed control can increase the efficacy of traditional weed control implements. Several scientific studies successfully used intelligent sensors for automatic harrow control by taking many different parameters into account such as weed density, soil resistance factor, and plant growth. However, none of the systems was practically feasible because these factors made the control system too complex and unattractive for farmers. Defining only one parameter (crop soil cover) instead of many provides a new and simple approach which was investigated in this work. The first scientific publication focuses on the development, practical implementation and testing of the automatic harrow control system. Two RGB-cameras were mounted before and after the harrow and constantly monitored crop cover. The CSC was then computed out of these resulting images. The image analysis, decision support system and automatic control of harrowing intensity by hydraulic adjustment of the tine angle were installed on a controller which was mounted on the harrow. Eight field experiments were carried out in spring cereals. Mode of harrowing intensity was changed in four experiments by speed, number of passes and tine angle. Each mode was varied in five intensities. In four experiments, only the intensity of harrowing was changed. Modes of intensity were not significantly different among each other. However, intensity had significant effects on WCE and CSC. Cereal plants recovered well from 10% CSC, and selectivity was in the constant range at 10% CSC. Therefore, 10% CSC was the threshold for the decision algorithm. If the actual CSC was below 10% CSC, intensity was increased. If the actual CSC was higher than 10%, intensity was decreased. The new system was tested in an additional field study. Threshold values for CSC were set at 10%, 30% and 60%. Automatic tine angle adjustment precisely realised the three different CSC values with variations of 1.5% to 3%. The next publication discussed and assessed the site-specific field adaptation of the development in cereals. In 2020, three field experiments were conducted in winter wheat and spring oats to investigate the response of the weed control efficacy and the crop to different harrowing intensities, in southwest Germany. In all experiments, six levels of CSC were tested. Each experiment contained an untreated control and an herbicide treatment as a comparison to the harrowing treatments. The results showed an increase in the WCE with an increasing CSC threshold. Difficult-to-control weed species such as Cirsium arvense (L.) and Galium aparine (L.) were best controlled with a CSC threshold of 70%. With a CSC threshold of 20% it was possible to control up to 98% of Thlaspi arvense (L.) The highest crop biomass, grain yield, and selectivity were achieved with an CSC threshold of 20–25% at all trial locations. With this harrowing intensity, grain yields were higher than in the herbicide control plots and a WCE of 68–98% was achieved. The last scientific article compares pairwise a conventional harrow intensity with automatic sensor-based harrowing intensity. Five field experiments in cereals were conducted at three locations in southwestern Germany in 2019 and 2020 to investigate if camera-based harrowing resulted in a more homogenous CSC and higher WCE, biomass, and crop grain yield than a conventional harrow with a constant intensity across the whole plot. For this purpose, pairwise comparisons of three fixed harrowing intensities (10 °, 40 °, and 70 ° tine angle) and three predefined CSC thresholds (CSC of 10%, 20%, and 60%) were realized in randomized complete block designs. Camera-based adjustment of the intensity resulted in 6-16% less standard deviation variation of CSC compared to fixed settings of tine angle. Crop density, WCE, crop biomass and grain yield were significantly higher for camera-based harrowing than for conventional harrowing. WCE and yields of all automatic adjusted harrowing treatments were equal to the herbicide control plots. In this PhD-thesis, a sensor-based harrow was developed and successfully investigated as an alternative to conventional herbicide application in cereals. A permanent, equal replacement of chemical weed control in arable farming systems can only be achieved using modern, sensor-based mechanical weed control approaches. Therefore, the efficacy of the mechanical weed control method can be improved and increased continuously. It has been shown that the precise adjustment of mechanical weed control methods to site-specific weed conditions allows similar WCE results as an herbicide application without causing yield losses. These findings contribute towards modern plant protection strategies to reduce the herbicide use and to establish the acceptance of technical progress in society.
Mechanical weed control: Sensor-based inter-row hoeing in sugar beet (Beta vulgaris L.) in the Transylvanian depression
(2024) Parasca, Sergiu Cioca; Spaeth, Michael; Rusu, Teodor; Bogdan, Ileana
Precision agriculture is about applying solutions that serve to obtain a high yield from the optimization of resources and the development of technologies based on the collection and use of precise data. Precision agriculture, including camera-guided row detection and hydraulic steering, is often used as an alternative because crop damage can be decreased and driving speed can be increased, comparable to herbicide applications. The effects of different approaches, such as uncontrolled (UC), mechanical weed control (MWC), herbicide weed control (HWC), and mechanical + herbicide control (MWC + HWC), on weed density and yield of sugar beet were tested and evaluated in two trials (2021 and 2022) in South Transylvania Depression at the tested intervals BBCH 19 and 31. Weed control efficacy (WCE) depends on the emergence of the weeds and a good timing of weed controls in all the trials and methods, though the highest yield of sugar beet roots was recorded in the treatment MWC + HWC, with an increase up to 12–15% (56.48 t ha−1) yield from HWC (50.22 t ha−1) and a yield increase of more than 35–40% than MWC (42.34 t ha−1). Our trials show that it is possible to increase yield and have fewer chemical applications with the introduction of new precision technologies in agriculture, including sensor-guided mechanical controls.
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.
Weed control in a pesticide‐free farming system with mineral fertilisers
(2023) Saile, Marcus; Spaeth, Michael; Schwarz, Jürgen; Bahrs, Enno; Claß‐Mahler, Ingrid; Gerhards, Roland
Negative impacts of pesticides on the environment and human health, the risk of pesticide residues in the food chain, and the problems with herbicide‐resistant weed biotypes support the need for alternative cropping systems. The objective of this study was to investigate weed populations, weed management and crop yield in a pesticide‐free cropping system with the use of mineral fertilisers. Conventional‐, organic‐ and mineral‐ecological cropping systems (MECS) with 6‐year crop rotations including winter wheat, maize, winter triticale or winter rye, soyabean or spring pea, and spring barley were established in a randomised complete strip plot design with four repetitions. Experiments were conducted at four locations in Germany. Preventive and sensor‐guided mechanical weed management strategies were applied in all crops in the organic system and in MECS. Herbicide were applied in the conventional farming system. Weed densities, weed species composition, weed control efficacy (WCE) and crop yield were analysed over 2 years in 2020 and 2021. Conventional farming had the highest WCE and 1–7 weeds m−2 (2.7% weed coverage) after herbicide application. In the organic cropping system and MECS, up to 27 weeds m−2 were counted after camera‐guided weed hoeing. Weed coverage in MECS (9.7%) was higher than in the organic cropping system with 7.7%. Crop yield in MECS was equal to the conventional farming system and 20% higher yield than in the organic farming system. MECS represents a promising new and productive cropping practice if an effective integrated weed management strategy is applied.