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Joint field experiments were established in Southwestern Germany to investigate the potential of herbicide savings on-farm sites with high densities of problematic weed species. From 2020 until 2024, 21 field studies were conducted in maize, soybean and winter wheat, all realised as randomised complete block designs with four replications. Mechanical weeding and two combined chemical with mechanical weeding methods were compared to conventional broadcast pre- and post-emergence herbicide spraying and an untreated control. Weed density, herbicide savings, greenhouse gas emissions and crop yield were determined for all treatments. On average, 142 weeds/m2 were counted in the untreated plots. The most frequent weed species were Chenopodium album, Echinochloa crus-galli, Solanum nigrum, Stellaria media, and Veronica persica. Combined chemical with mechanical weed control in soybean and winter wheat was more effective than chemical and mechanical weed control alone. In maize, the combination of hoeing and herbicide application achieved equal weed control efficacy (WCE) as chemical weeding alone. Hoeing removed less intra-row weeds than inter-row weeds. Hoeing and harrowing had low WCE against Chenopodium album and perennial weed species. Combined treatments reduced herbicide use by 24-60% in relation to conventional herbicide treatments. Mechanical and combined weed control achieved equal yield as the conventional herbicide treatment. This study underlines the potential for herbicide savings by integrating mechanical weed control methods.

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.

New cropping practices such as single-grain seeding, lower seed densities with stronger cultivars, wide inter-row spacings and camera-guided side-shift control for weed hoeing facilitate mechanical weed control in oilseed rape. In a two-year field study in Southwestern Germany, camera-guided inter-row hoeing was compared to standard herbicide treatments and untreated control. Seeding with 12.5, 25 and 50 cm inter-row spacing was included as a second factor in the experiment. Weed and crop density were measured directly after treatment. Weed and crop biomass, oilseed rape root diameter and nitrogen uptake were assessed before winter. Seed yield was measured at harvest with a plot combine harvester. In 2021, hoeing in 50 cm inter-row spacing achieved equal weed control efficacy as the herbicide treatment (65-75%). In 2022, hoeing did not reduce weed density, probably due to heavy rainfalls during the first and second pass of hoeing. However, herbicide treatments controlled 92% of the weeds. In 2021, hoeing significantly increased oilseed rape shoot biomass and root diameter compared to the herbicide treatment and the untreated control. Hoeing in 50 cm inter-row spacing resulted in equal yield as the herbicide treatment. In 2022, weed control treatments and inter-row spacing had no effect on oilseed rape biomass, root diameter and yield. This study shows the potential and limitations of weed hoeing in oilseed rape. It also underlines the strong ability of modern oilseed rape cultivars to suppress annual broadleaved weeds.

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.

Delayed sowing of winter cereals in Western Europe is a preventive method to reduce Alopecurus myosuroides infestations. Two series of on-farm studies including 36 experiments were conducted in South-Western Germany to analyse the combined effects of delayed sowing and pre-emergence herbicide application on A. myosuroides density, weed control efficacy and cereal grain yield. From 2006 until 2009, pendimethalin + flufenacet was applied one week after sowing winter barley and winter wheat. From 2018 until 2020, cinmethylin was used in winter wheat and winter triticale. Densities of A. myosuroides in the untreated early sown control plots amounted up to 1 233 plants/m2. Delayed sowing on average reduced densities by 43%. The mixture of pendimethalin + flufenacet in combination with delayed sowing controlled 87% of the A. myosuroides plants and increased cereal grain yields from 6.4 t/ha in the early sown untreated control to 7.9 t/ha. Cinmethylin in combination with delayed sowing resulted in 91% weed control efficacy and increased grain yields from 5.3 t/ha to 8.8 t/ha. Average grain yields of all delayed sowing treatments were 0.7 t/ha higher than in the early sown treatments. Therefore, delayed sowing combined with pre-emergence herbicide application is a cost-effective strategy of integrated weed management (IWM) in winter cereals reducing dependency on post-emergence herbicide use and mitigating the risk of herbicide resistance development.

Cinmethylin is a potential new pre-emergence herbicide in Europe inhibiting the fatty acid thioesterases in the plastid against Alopecurus myosuroides and other grass-weeds in winter cereals and oil-seed rape. Five field experiments were conducted in Southwestern Germany from 2018 until 2020 to assess the control efficacy of cinmethylin and other common pre-emergence herbicides alone and combined with post-emergence herbicides against A. myosuroides and yield response of winter wheat and winter triticale. In four experiments, the effect of early and late sowing of winter cereals was included as the second factor in the experiment to investigate if late sowing can reduce A. myosuroides density weed control efficacy. All fields were heavily infested with A. myosuroides with average densities of 110-730 plants/m2. Late sowing reduced densities in three out of four experiments. Herbicides controlled 42-100% of the A. myosuroides plants. However, none of the treatments was consistently better than the other treatments over all experiments. In three out of 5 experiments, grain yields were significantly increased by the herbicide treatments. The results demonstrate that cinmethylin increases the options for controlling A. myosuroides in winter cereals. However, it needs to be combined with other control tactics.

Aim of study: An approach to integrate knowledge into the IT-infrastructure of precision agriculture (PA) is presented. The creation of operation relevant information is analyzed and explored to be processed by standardized web services and thereby to integrate external knowledge into PA. The target is to make knowledge integrable into any software solution. Area of study: The data sampling took place at the Heidfeld Hof Research Station in Stuttgart, Germany. Material and methods: This study follows the information science’s idea to separate the process from data sampling into the final actuation through four steps: data, information, knowledge, and wisdom. The process from the data acquisition, over a professional data treatment to the actual application is analyzed by methods modelled in the Unified Modelling Language (UML) for two use-cases. It was further applied for a low altitude sensor in a PA operation; a data sampling by UAV represents the starting point. Main results: For the implemented solution, the Web Processing Service (WPS) of the Open Geospatial Consortium (OGC) is proposed. This approach reflects the idea of a function as a service (FaaS), in order to develop a demand-driven and extensible solution for irregularly used functionalities. PA benefits, as on-farm processes are season oriented and a FaaS reflects the farm’s variable demands over time by origin and extends the concept to offer external know-how for the integration into specific processes. Research highlights: The standardized implementation of knowledge into PA software products helps to generate additional benefits for PA.

The water demand for cover crops (CC) should be considered to achieve competitive crop stands for weed control also under unfavorable conditions. This study aims to estimate the weed suppressive ability of winter CC, as Sinapis alba L., Phacelia tanacetifolia Benth., Vicia sativa L. and Avena strigosa Schreb., under a water-limited regime. The water deficit tolerance of different CC was determined in a greenhouse experiment by measuring the maximum quantum efficiency of photosystem II. Moreover, soil moisture, CC, and weed establishment were measured in field experiments in Southwest-Germany during two contrasting growing seasons in 2016 and 2017. A. strigosa showed a higher water deficit tolerance than S. alba in the greenhouse. In the field, A. strigosa showed the highest weed cover reduction (98%) in the field, along with an increasing effect on the soil moisture compared to the untreated control. S. alba performed most sensitive to water deficit in the greenhouse but reached the significantly highest weed control efficacy (94%) during the dry field season in 2016. Even though the selected CC showed differing sensitivities to water deficit in the greenhouse, their weed suppression ability was independent of the water supply under field conditions.

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.

Due to the increasing number of herbicide-resistant weed populations and the resulting yield losses, weed control must be given high priority to ensure food security. Integrated weed management (IWM) strategies, including reduced herbicide application, sensor-guided mechanical weed control and combinations thereof are indispensable to achieve this goal. Therefore, this study examined combinations of pre- and post-emergence herbicide applications with sensor-based harrowing and hoeing in cereals by conducting five field experiments at two locations in Southwestern Germany from 2019 to 2021. Each experiment contained an untreated control and a single post-emergence herbicide treatment as a comparison to these IWM treatments. The effects of the different IWM approaches on weed control efficacy (WCE), crop density, and grain yield were recorded. All experiments were set up in a randomized complete block design with four repetitions. Pre-emergence herbicide application combined with one-time harrowing and subsequent hoeing (Pre-Herb + Harr + Hoe) achieved the highest WCE (100%), followed by an approach of WCE (95%) for two-times hoeing. In contrast, a single pre-emergence herbicide application achieved the worst result with an average WCE of 25%. Grain yield was equal between all treatments in between 6 t ha−1 and 10 t ha−1, except for a single pre-emergence herbicide application, which achieved a 2.5 t ha−1 higher grain yield in winter wheat in 2021 that averaged 11 t ha−1, compared to the combination of Pre-Herb + Harr + Hoe that averaged 8.5 t ha−1. The results showed that it is possible to reduce and replace herbicides while achieving equivalent yield and WCE.

Weed biodiversity plays a key role in supporting food webs and ecosystem services in agroecosystems. One important service, that reduces weed abundance, is the predation of weed seeds by invertebrates and vertebrates. In this context weed biodiversity may be supportive in maintaining seed predator prevalence. This however, can be highly influenced by farming systems. In the present study we examined the connections between weed diversity, carabid beetle diversity and weed seed predation (WSP) rate. Additionally, the influence of a farming intensity gradient on WSP rate and predator groups was evaluated. An on-farm experiment on the Eastern Swabian Alps was set up from 2015 to 2017, where we determined the weed diversity, carabid beetle diversity using pitfall traps and WSP rates and predator groups by utilizing seed cards and exclosure cages. There was a linear correlation between weed diversity and carabid beetle diversity as well as a pattern showing that intermediate diversity of carabid beetles (3–8 species) exhibited the highest WSP rates by invertebrates. However, a direct connection between weed diversity and WSP was not detected. Farming intensity had no consistent influence on WSP, rather year and specific agronomic measures like cover cropping most presumably affected WSP. Carabid beetle communities were similar in 2016 and 2017 with omnivorous species dominating in the conventional fields and granivorous species in extensively managed fields. The most efficient seed predators were vertebrates. The promotion of beneficial predators and ecosystem services like WSP is possible by designing appropriate management strategies. Key components of these strategies should be the conservation of plant diversity and the utilization of weed control strategies such as cover cropping that provide suitable habitats for beneficial predators.

Mais, Sojabohne und Zuckerrübe reagieren mit hohen Ertragsverlusten auf Unkrautkonkurrenz in frühen Entwicklungsstadium. Daher sind effektive Methoden der Unkrautbekämpfung zwischen und in den Reihen der Kulturpflanzen wichtig. Das Ziel dieser Studie war es, den Effekt von der Fingerhacke, der Torsionshacke, des Rollstriegels und eines Häufelschars auf die Unkrautkontrolle innerhalb der Kulturpflanzenreihen zu untersuchen. Dabei wurden diese Werkzeuge in Kombination mit einer Kamera-gesteuerten Hacke zwischen den Reihen kombiniert. Eine Variante wurde nur zwischen den Reihen gehackt. Darüber hinaus gab es eine unbehandelte Kontrolle und eine unkrautfreie Variante mit ganzflächigem Herbizid-Einsatz. In Zuckerrüben wurde auch die Hacke zwischen den Reihen mit einer Band-Herbizid-Applikation kombiniert. In Mais und Soja wurde jeweils ein Feldversuch im Jahr 2015 durchgeführt, in Zuckerrüben wurden zwei Feldversuche in den Jahren 2015 und 2016 auf der Versuchsstation der Universität Hohenheim angelegt. Mais und Soja wurden zweimal gehackt, Zuckerrüben dreimal. Die Unkrautdichte (getrennt für die Bereiche in und zwischen den Kulturpflanzenreihen) und die Kulturpflanzenverluste wurden nach jeder Maßnahme gezählt. Die Erträge wurden zu Versuchsende bestimmt. Der Erfolg der Unkrautbekämpfung zwischen den Kulturpflanzenreihen war mit 90–95 % in den Hack- und Herbizid-Varianten gleich. Der Bekämpfungserfolg gegen die Unkräuter in der Kulturpflanzenreihe war bei allen Hackvarianten mit durchschnittlich 67 % deutlich niedriger als in der Kontrolle mit Herbizid-Applikation. In Mais überlebten durchschnittlich 30 Unkräuter pro m², in Sojabohne 4 Unkräuter pro m² und in Zuckerrübe 13 Unkräuter pro m². Die Werkzeuge in der Reihe konnten nur in einem von vier Versuchen den Bekämpfungserfolg im Vergleich zur kameragesteuerten Hacke zwischen den Reihen allein erhöhen. Diese Studie zeigt die Notwendigkeit von verbesserten Hackverfahren in den Kulturpflanzenreihen, um Ertragsverluste zu vermeiden und Kosten für die manuelle Unkrautbekämpfung zu reduzieren.

Although different modifications of ridge tillage (RT) systems exist in different regions around the world, the positive impacts of RT on crop yields and weed management are quite similar. This review gives a comprehensive summary of different forms of RT and highlights the benefits of RT for crop growth, mainly due to better access to soil moisture, nutrients and light. In temperate areas, RT can accelerate crop emergence because soil temperature is usually higher on the ridge. These stimulating effects increase crop competitiveness against weeds especially in the early period of crop development until canopy closure. RT with crops placed on the top of ridges can also be used for automatically guiding inter-row hoes and intra-row band sprayers. The ridges can replace automatic vision control systems for hoeing and band spraying, which are needed for precise weeding in conventional flat seedbeds. Therefore, RT can be considered a possible platform for smart/robotic weeding. This paper introduces a new RT system using real-time kinematic (RTK) global satellite navigation systems (GNSS) for the ridging and seeding of maize and soybean on top of recompacted ridges. Straight ridges with precise positioning data were used to guide mechanical weeding elements precisely along the crop rows. Simultaneously, weeds in the valleys were suppressed by living mulches. Field experiments with this new technology in maize showed 85.5% weed dry biomass suppression compared to an untreated control and a slightly higher weed control efficacy than mechanical weeding in flat seedbeds.

Reliable tests on herbicide resistance are important for resistance management. Despite well-established greenhouse bioassays, faster and in-season screening methods would aid in more efficient resistance detection. The feasibility of a chlorophyll fluorescence agar-based test on herbicide resistance in Apera spica-venti L. was investigated. Herbicide resistant and sensitive A. spica-venti seedlings were transplanted into agar containing pinoxaden and pyroxsulam herbicides. Chlorophyll fluorescence was measured and the maximum quantum efficiency of photosystem II (Fv/Fm) was determined 48 h and 72 h after the transplantation to agar, respectively. The Fv/Fm values decreased with increasing herbicide concentration. Dose-response curves and respective ED50 values (herbicide concentration leading to 50% decrease of the Fv/Fm value) were calculated. However, each experiment repetition exhibited different sensitivities of the populations for both herbicides. In certain cases, resistant populations demonstrated similar Fv/Fm values as sensitive populations. Contrary to the findings in Alopecurus myosuroides Huds., discrimination of sensitive and resistant A. spica-venti populations was not feasible. An increased importance of the assessment time due to the herbicide concentrations calibrated for fast responses was assumed in this study.

Effective control of Alopecurus myosuroides Huds. (blackgrass) solely with a chemical treatment is not guaranteed anymore because populations exhibit resistance to almost all herbicide modes of action. Integrated weed management (IWM) against blackgrass is necessary to maintain high weed control efficacies in winter cereals. Four field experiments were conducted in Southwest Germany from 2018 to 2020 to control A. myosuroides with a combination of cultural and chemical methods. Stubble treatments, including flat, deep and inversion soil tillage; false seedbed preparation and glyphosate use, were combined with the application of the new pre-emergence herbicide cinmethylin in two rates in winter wheat. Average densities of A. myosuroides in the untreated control plots were up to 505 plants m−2. The combination of different stubble management strategies and the pre-emergence herbicide cinmethylin controlled 86–97% of A. myosuroides plants at the low rate and 95–100% at the high rate until 120 days after sowing. The different stubble tillage practices varied in their efficacy between trials and years. Most effective and consistent were pre-sowing glyphosate application on the stubble and stale seedbed preparation with a disc harrow. Stubble treatments increased winter wheat density in the first year but had no effect on crop density in the second year. Pre-emergence application of cinmethylin did not reduce winter wheat densities. Multiple tactics of weed control, including stubble treatments and pre-emergence application of cinmethylin, provided higher and more consistent control of A. myosuroides. Integration of cultural weed management could prevent the herbicide resistance development.

In the given study an adjustable harrowing system is presented and tested. The automatic harrow can increase or decrease the harrowing intensity during operation. A gentle (20%), medium (40%) and aggressive (60%) harrow intensity was chosen. Prior to the application, measurements were performed in each plot concerning the weed density and composition. With this information, a Decision Support System based on fuzzy logic was used in order to trigger an appropriate tine angle movement. Thus, areas with high crop and weed densities were applied with more aggressive harrowing treatments and areas with lower weed densities with a gentler treatment. A spring barley field was adopted to evaluate the suitability and effectiveness of the system at the University of Hohenheim, Germany. A harrow application was conducted at the maximum permitted harrow intensity (60%), as the farmer would have applied it on the field and an automatic adaptation, based on the results of the decision support system. A further herbicide treatment and an untreated control were also included. Weed counting was performed prior to and after the application, along with biomass cuts and yield in order to estimate the treatment efficacy. The automatic system performed well, providing similar results as the nonautomatic harrowing, but with lower intensity levels. Dicotyledonous weeds were, in both mechanical applications, reduced as well as by the herbicide application, without any significant differences.

Highly developed weed control strategies manage to suppress weeds and therefore contribute to a shift in weed community composition as well as a decline in rare weed occurrence. To counteract this decline fields containing rare weed species are taken under contract for preservation purposes, however only time limited. We mapped the weed flora in cereals of conventional (K) and organic (O) fields as well as current (V) and former (E) rare species conservation fields in the Gäu region of Southwestern Germany in 2016. We found similar weed species numbers in O (24 – 38 species) and V (36 – 43 species) and in C (7 – 17 species) and E (13 – 15 species). Weed community composition varied considerably between fields. By performing a CCA (Canonical Correspondence Analysis) we were able to explain 23% of the weed community composition by the parameters seeding rate and nitrogen fertilization. Nevertheless species such as Alopecurus myosuroides, Geranium dissectum, Papaver rhoeas, Poa trivialis and Veronica persica showed a high consistency in all observations. Rare and endangered weed species like Papaver argemone, Consolida regalis, Ranunculus arvensis and Galium tricornutum were only present in V and occasionally E and O. This indicates a rapid decline of weed species diversity after contracts expire, which slowly leads to a similar floral composition as in conventional fields. Therefore new concepts for constant protection of rare weed species should be put into action to ensure conservation success.

Public awareness and environmental policies have increased interest in applying non-herbicide weed control methods in conventional farming systems. Even though mechanical weed control has been used for centuries in agricultural practice, continuous developments—both in terms of implements and automation technologies—are continuously improving the potential outcomes. Current mechanical weed control methods were evaluated for their weed control efficacy and effects on yield potential against their equivalent herbicide methods. Furthermore, not much is known about the correlation between weed control efficacy (WCE) of different mechanical methods at varying weed density levels. A total of six experiments in winter wheat (2), peas (2), and soybean (2) were carried out in the years 2018, 2019, and 2020 in southwestern Germany. Harrowing and hoeing treatments at different speeds were carried out and compared to the herbicide treatments and untreated control plots. Regarding the average WCE, the combination of harrowing and hoeing was both the strongest (82%) and the most stable (74–100%) mechanical treatment in the different weed density levels. Whereas, in average, hoeing (72%) and harrowing (71%) were on the same WCE level, but harrowing (49–82%) was more stable than hoeing (40–99%). The grain yields in winter wheat varied between 4.1 Mg∙ha−1 (control) and 6.3 Mg∙ha−1 (harrow), in pea between 2.8 Mg∙ha−1 (hoe slow) and 5.7 Mg∙ha−1 (hoe fast) and in soybean between 1.7 Mg∙ha−1 (control) and 4 Mg∙ha−1 (herbicide). However, there were no significant differences in most cases. The results have shown that it is not possible to pinpoint a specific type of treatment as the most appropriate method for this cultivation, across all of the different circumstances. Different field and weather conditions can heavily affect and impact the expected outcome, giving, each time, an advantage for a specific type of treatment.

Setting the right intensity is crucial for the success of post-emergence weed harrowing in cereals. The percentage of crop soil cover (CSC) correlates with the selectivity of weed harrowing. Therefore, real-time camera-based measurements of CSC offer a novel approach to automatically adjust the intensity of harrowing. The intensity of harrowing is varied by hydraulic steering of the tine angle. Five field experiments in cereals were conducted at three locations in southwestern Germany in 2019 and 2020 to measure the effect of camera-based harrowing (2020) and conventional harrowing on weed control efficacy (WCE), crop density, and grain yield. For this purpose, pair-wise 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 intensity adjustment resulted in more homogeneous CSC across the whole plot (6–16% less standard deviation variation) compared to conventional fixed settings of the 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. Camera-based harrowing provides a robust technology for effective weed management with a lower risk of crop damage than conventional harrowing.

The search for approaches to a holistic sustainable agriculture requires the development of new cropping systems that provide additional ecosystem services beyond biomass supply for food, feed, material, and energy use. The reduction of chemical synthetic plant protection products is a key instrument to protect vulnerable natural resources such as groundwater and biodiversity. Together with an optimal use of mineral fertilizer, agroecological practices, and precision agriculture technologies, a complete elimination of chemical synthetic plant protection in mineral-ecological cropping systems (MECSs) may not only improve the environmental performance of agroecosystems, but also ensure their yield performance. Therefore, the development of MECSs aims to improve the overall ecosystem services of agricultural landscapes by (i) improving the provision of regulating ecosystem services compared to conventional cropping systems and (ii) improving the supply of provisioning ecosystem services compared to organic cropping systems. In the present review, all relevant research levels and aspects of this new farming concept are outlined and discussed based on a comprehensive literature review and the ongoing research project “Agriculture 4.0 without Chemical-Synthetic Plant Protection”.

Field experiments were conducted at two locations in 2014-2015 and 2015-2016 to investigate the weed suppressive ability of cover crop mulches in sugar beets. Three cover crops and two cover crop mixtures were tested in all four experiments. Weed densities ranged from 2 up to 210 plants/m2 in Chenopodium album L. and Stellaria media (L.) Vill. as predominant species. Sinapis alba grew significantly faster than Vicia sativa, Raphanus sativus var. niger, and both cover crop mixtures. Sinapis alba, Vicia sativa, Raphanus sativus var. niger reduced weed density by 57, 22, and 15% across all locations, respectively. A mixture of seven different cover crops reduced weed emergence by 64% compared to the control plot without cover crop mulch. Early sugar beet growth was enhanced by all mulch treatments in 2015 and decelerated in 2016.

Sugar beet yield loss was predicted from early observations of weed density, relative weed cover, and weed biomass using non-linear regression models. Six field experiments were conducted in Germany and in the Russian Federation in 2012, 2013 and 2014. Average weed densities varied from 20 to 131 with typical weed species compositions for sugar beet fields at both locations. Sugar beet yielded higher in Germany and relative yield losses were lower than in Russia. Data of weed density, relative weed cover, weed biomass and relative yield loss fitted well to the non-linear regression models. Competitive weed species such as Chenopodium album and Amaranthus retroflexus caused more than 80% yield loss. Relative weed cover regression models provided more accurate predictions of sugar beet yield losses than weed biomass and weed density.

The weed suppressive ability of oilseed radish (Raphanus sativus var. oleiformis Pers.) cover crop is attributed to high competitiveness for resources and biochemical effects on weeds. The oilseed radish cover crop was sown in five treatments plus an untreated control over a period of five weeks before and three weeks after winter wheat harvest. Additionally, fertilization effects on oilseed radish biomass and weed suppression were measured. The highest biomass of the cover crop was observed 12 weeks after harvest (WAH) when the oilseed radish was sown one week after harvest (1 WAH) (2015) and five weeks before harvest (5 WBH) (2016). No differences of fertilization were observed concerning oilseed radish and weed biomass in 2015, whereby increased biomass was found after fertilization in 2016. The highest weed control efficacy of up to 83% and 90% was achieved in treatments 1 WAH (2015) and 5 WBH (2016) at 12 WAH. The early sowing of oilseed radish in winter wheat resulted in low germination and biomass yield within the field, due to low precipitation in 2015. Nevertheless, there is a high potential of early sown oilseed radish for higher weed control efficacy, which was demonstrated in 2016.

Common vetch (Vicia sativa L.) can be an alternative grain legume to faba beans, peas, lupins and soy beans due to its high grain protein content. As it is uncommon for grain use, cropping systems need to be developed. Weed infestation is a major problem in grain legume cultivation. Therefore, intercropping systems for common vetch which ensure a low level of weed infestation need to be designed. Thus, weed suppression of common vetch in a replacement series with spring wheat was examined in Northern Germany in the year 2018. It was the aim to define which seed density ratios will achieve the highest weed suppression, total and common vetch yield. Three harvests of crop and weed biomass and a grain harvest at full maturity were carried out in a field experiment with four replications. Weed nitrogen content was examined. Transmission of photosynthetically active radiation to weed canopy level was measured during the season. Yield and weed suppression of intercrops were analysed by different indices, and factors contributing to weed suppression were discussed. With increasing wheat ratio, weed biomass in intercrops decreased and less nitrogen was taken up by weeds. Less photosynthetically active radiation was available to weed canopy level during juvenile development in intercrops with higher wheat ratios, whereas more radiation was available to weeds in these intercrops in later stages. Higher total biomass and grain yield was achieved in intercrops compared to sole crops. The mean land equivalent ratio (LER) of all intercrops calculated from grain yield was 1.32. The index actual yield loss or gain (AYL) specified a mean actual yield gain of intercrops of 73% compared to sole crops. The competitive ratio (CR) revealed that wheat was more competitive compared to vetch. Wheat was responsible for the extra yield of intercrops. It can be concluded that common vetch can be successfully grown in intercrops with spring wheat. Effective weed suppression due to intercropping was possible when the vetch ratio was moderate. With high vetch ratios sufficient weed suppression cannot be achieved. Crop-weed competition for nitrogen and for light in the early growth stages determined weed growth in vetch-wheat intercrops.

Rapid and reliable tests for pre-emergence herbicide susceptibility in weeds are important to test a wider range of accessions on their baseline sensitivity, as well as to provide information on putative resistance. This study focused on the development of an agar quick test to determine sensitivity differences in Alopecurus myosuroides Huds. to pre-emergence herbicides containing flufenacet and cinmethylin. The new agar quick test and a standardized whole plant pot bioassay were conducted twice in 2019. For both test systems, seeds of 18 populations of A. myosuroides originated from Southwest Germany and Great Britain were used and treated with discriminating rates of herbicides in dose-response studies. After 28 days, the above-ground dry matter of the plants was determined and the resistance factors were calculated. The agar test was able to provide information on the resistance status of the tested biotype within 12 days. All populations did not show reduced sensitivity to cinmethylin. Within three populations, differences in sensitivity levels were observed between the two test systems. As cinmethylin is not yet marketed in Europe, these resistance factors can also be considered as a baseline sensitivity for A. myosuroides. For flufenacet, the resistance factors differed significantly from the whole plant pot bioassay and the agar test for the biotypes A (0.35, 13.1), C (0.56, 13.2), D (1.87, 12.4), E (15.5, 3.5) and H (2.95, 14). It was possible for the most part for the cinmethylin tested populations to confirm the results of the standardized whole plant pot bioassay in the agar bioassay sensitivity tests, and hence create a promising, faster test system.

The need for herbicide usage reduction and the increased interest in mechanical weed control has prompted greater attention to the development of agricultural robots for autonomous weeding in the past years. This also requires the development of suitable mechanical weeding tools. Therefore, we devised a new weeding tool for agricultural robots to perform intrarow mechanical weed control in sugar beets. A conventional finger weeder was modified and equipped with an electric motor. This allowed the rotational movement of the finger weeders independent of the forward travel speed of the tool carrier. The new tool was tested in combination with a bi-spectral camera in a two-year field trial. The camera was used to identify crop plants in the intrarow area. A controller regulated the speed of the motorized finger weeders, realizing two different setups. At the location of a sugar beet plant, the rotational speed was equal to the driving speed of the tractor. Between two sugar beet plants, the rotational speed was either increased by 40% or decreased by 40%. The intrarow weed control efficacy of this new system ranged from 87 to 91% in 2017 and from 91 to 94% in 2018. The sugar beet yields were not adversely affected by the mechanical treatments compared to the conventional herbicide application. The motorized finger weeders present an effective system for selective intrarow mechanical weeding. Certainly, mechanical weeding involves the risk of high weed infestations if the treatments are not applied properly and in a timely manner regardless of whether sensor technology is used or not. However, due to the increasing herbicide resistances and the continuing bans on herbicides, mechanical weeding strategies must be investigated further. The mechanical weeding system of the present study can contribute to the reduction of herbicide use in sugar beets and other wide row crops.

Although clear evidence for benefits in crop production is partly missing, several natural compounds and microorganisms have been introduced to the market as biostimulants. They are supposed to enhance nutrient efficiency and availability in the rhizosphere, reduce abiotic stress, and improve crop quality parameters. Biostimulants often derive from natural compounds, such as microorganisms, algae, and plant extracts. In this study, the commercial plant extract-based biostimulant ComCat® was tested in two field experiments with maize in the communities of Banikoara and Matéri in Northern Benin and six pot experiments (four with maize and two with winter barley) at the University of Hohenheim in Germany. Maize was grown under nutrient deficiency, drought, and weed competition, and winter barley was stressed by the herbicide Luximo (cinmethylin). ComCat® was applied at half, full, and double the recommended field rate (50, 100, and 200 g ha−1) on the stressed and unstressed control plants as leaf or seed treatment. The experiments were conducted in randomized complete block designs with four replications. The above-ground biomass and yield data of one experiment in Benin were collected. The biostimulant did not promote maize and winter barley biomass production of the unstressed plants. When exposed to stress, ComCat® resulted only in one out of eight experiments in higher barley biomass compared to the stressed treatment without ComCat® application. There was a reduced phytotoxic effect of cinmethylin after seed treatment with ComCat®. Crop response to ComCat® was independent of the application rate. Basic and applied studies are needed to investigate the response of crops to biostimulants and their mechanisms of action in the plants before they should be used in practical farming.

Harrowing is mostly applied with a constant intensity across the whole field. Heterogeneous field conditions such as variable soil texture, different crop growth stages, variations of the weed infestation level, and weed species composition are usually not considered during the treatment. This study offers a new approach to sensor-based harrowing which addresses these field variations. Smart harrowing requires the continuous adaptation of the treatment intensity to maintain the same level of crop selectivity while ensuring a high weed control efficacy. Therefore, a harrow was equipped with a sensor-system to automatically adjust the angle of the harrow tines based on a newly developed decision algorithm. 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 crop soil cover (CSC) were tested. The CSC determines the balance between crop damage and weed removal. Each experiment contained an untreated control and an herbicide treatment as a comparison to the harrowing treatments. The results showed an increase in the weed control efficacy (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%. However, 70% CSC caused up to 50% crop biomass loss and up to 2 t·ha−1 of grain yield reduction. 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 locations. With this harrowing intensity, grain yields were higher than in the herbicide plots and a WCE of 68–98% was achieved. Due to the rapid adjustment of tine angle, the new sensor-based harrow allows users to apply the most selective harrowing intensity in every location of the field. Therefore, it can achieve equal weed control efficacies as using herbicide applications.

The increasing public concern about food security and the stricter rules applied worldwide concerning herbicide use in the agri-food chain, reduce consumer acceptance of chemical plant protection. Site-Specific Weed Management can be achieved by applying a treatment only on the weed patches. Crop plants and weeds identification is a necessary component for various aspects of precision farming in order to perform on the spot herbicide spraying or robotic weeding and precision mechanical weed control. During the last years, a lot of different methods have been proposed, yet more improvements need to be made on this problem, concerning speed, robustness, and accuracy of the algorithms and the recognition systems. Digital cameras and Artificial Neural Networks (ANNs) have been rapidly developed in the past few years, providing new methods and tools also in agriculture and weed management. In the current work, images gathered by an RGB camera of Zea mays, Helianthus annuus, Solanum tuberosum, Alopecurus myosuroides, Amaranthus retroflexus, Avena fatua, Chenopodium album, Lamium purpureum, Matricaria chamomila, Setaria spp., Solanum nigrum and Stellaria media were provided to train Convolutional Neural Networks (CNNs). Three different CNNs, namely VGG16, ResNet–50, and Xception, were adapted and trained on a pool of 93,000 images. The training images consisted of images with plant material with only one species per image. A Top-1 accuracy between 77% and 98% was obtained in plant detection and weed species discrimination, on the testing of the images.

Weed infestations and associated yield losses require effective weed control measures in soybean and sugar beet. Besides chemical weed control, mechanical weeding plays an important role in integrated weed management systems. Field experiments were conducted at three locations for soybean in 2013 and 2014 and at four locations for sugar beet in 2014 to investigate if automatic steering technologies for inter-row weed hoeing using a camera or RTK-GNSS increase weed control efficacy, efficiency and crop yield. Treatments using precision farming technologies were compared with conventional weed control strategies. Weed densities in the experiments ranged from 15 to 154 plants m−2 with Chenopodium album, Polygonum convolvulus, Polygonum aviculare, Matricaria chamomilla and Lamium purpureum being the most abundant species. Weed hoeing using automatic steering technologies reduced weed densities in soybean by 89% and in sugar beet by 87% compared to 85% weed control efficacy in soybean and sugar beet with conventional weeding systems. Speed of weed hoeing could be increased from 4 km h−1 with conventional hoes to 7 and 10 km·h−1, when automatic steering systems were used. Precision hoeing technologies increased soybean yield by 23% and sugar beet yield by 37%. After conventional hoeing and harrowing, soybean yields were increased by 28% and sugar beet yield by 26%.

Non-chemical weed control methods need to be directed towards a site-specific weeding approach, in order to be able to compete the conventional herbicide equivalents. A system for online weed control was developed. It automatically adjusts the tine angle of a harrow and creates different levels of intensity: from gentle to aggressive. Two experimental plots in a maize field were harrowed with two consecutive passes. The plots presented from low to high weed infestation levels. Discriminant capabilities of an ultrasonic sensor were used to determine the crop and weed variability of the field. A controlling unit used ultrasonic readings to adjust the tine angle, producing an appropriate harrowing intensity. Thus, areas with high crop and weed densities were more aggressively harrowed, while areas with lower densities were cultivated with a gentler treatment; areas with very low densities or without weeds were not treated. Although the weed development was relatively advanced and the soil surface was hard, the weed control achieved by the system reached an average of 51% (20%–91%), without causing significant crop damage as a result of harrowing. This system is proposed as a relatively low cost, online, and real-time automatic harrow that improves the weed control efficacy, reduces energy consumption, and avoids the usage of herbicide.

To achieve efficient weed control through cover cropping, the plant species chosen needs particular consideration. Combing different cover crop (CC) species in mixtures may increase the number of provided ecosystem services, including reliable suppression of weeds. We tested the weed suppression ability of single CC species and CC mixtures in a field trial during the autumn-to-winter growing season of 2016 and 2017. Anethum graveolens L. (dill), Raphanus sativus var. oleiformis Pers. (oilseed radish), Avena strigosa Schreb. (black oat), Carthamus tinctorius L. (safflower), Vicia sativa L. (vetch) and Phacelia tanacetifolia Benth. (phacelia) were sown in monocultures, as well as in mixtures with three or six species. Treatments with favorable establishment and above-average biomass yields tended to suppress weeds by showing lower weed dry matter and weed numbers. The highest weed control efficacy within the monocultures was reached in 2017 by black oat and oilseed radish with 72% and 83%, respectively. The mixture treatments reached a generally lower soil cover, aboveground dry matter and weed control efficacy (with an average of 57% in 2017). Even though mixtures were not as effective as the best performing single sown CCs, species combinations increased resilience against adverse weather conditions, an advantage to achieving efficient weed control over a long-term period. Therefore, species composition within mixtures is more relevant than the number of species included.

Plant modeling can provide a more detailed overview regarding the basis of plant development throughout the life cycle. Three-dimensional processing algorithms are rapidly expanding in plant phenotyping programmes and in decision-making for agronomic management. Several methods have already been tested, but for practical implementations the trade-off between equipment cost, computational resources needed and the fidelity and accuracy in the reconstruction of the end-details needs to be assessed and quantified. This study examined the suitability of two low-cost systems for plant reconstruction. A low-cost Structure from Motion (SfM) technique was used to create 3D models for plant crop reconstruction. In the second method, an acquisition and reconstruction algorithm using an RGB-Depth Kinect v2 sensor was tested following a similar image acquisition procedure. The information was processed to create a dense point cloud, which allowed the creation of a 3D-polygon mesh representing every scanned plant. The selected crop plants corresponded to three different crops (maize, sugar beet and sunflower) that have structural and biological differences. The parameters measured from the model were validated with ground truth data of plant height, leaf area index and plant dry biomass using regression methods. The results showed strong consistency with good correlations between the calculated values in the models and the ground truth information. Although, the values obtained were always accurately estimated, differences between the methods and among the crops were found. The SfM method showed a slightly better result with regard to the reconstruction the end-details and the accuracy of the height estimation. Although the use of the processing algorithm is relatively fast, the use of RGB-D information is faster during the creation of the 3D models. Thus, both methods demonstrated robust results and provided great potential for use in both for indoor and outdoor scenarios. Consequently, these low-cost systems for 3D modeling are suitable for several situations where there is a need for model generation and also provide a favourable time-cost relationship.

In this study, the evaluation of the accuracy and performance of a light detection and ranging (LIDAR) sensor for vegetation using distance and reflection measurements aiming to detect and discriminate maize plants and weeds from soil surface was done. The study continues a previous work carried out in a maize field in Spain with a LIDAR sensor using exclusively one index, the height profile. The current system uses a combination of the two mentioned indexes. The experiment was carried out in a maize field at growth stage 12–14, at 16 different locations selected to represent the widest possible density of three weeds: Echinochloa crus-galli (L.) P.Beauv., Lamium purpureum L., Galium aparine L.and Veronica persica Poir.. A terrestrial LIDAR sensor was mounted on a tripod pointing to the inter-row area, with its horizontal axis and the field of view pointing vertically downwards to the ground, scanning a vertical plane with the potential presence of vegetation. Immediately after the LIDAR data acquisition (distances and reflection measurements), actual heights of plants were estimated using an appropriate methodology. For that purpose, digital images were taken of each sampled area. Data showed a high correlation between LIDAR measured height and actual plant heights (R2 = 0.75). Binary logistic regression between weed presence/absence and the sensor readings (LIDAR height and reflection values) was used to validate the accuracy of the sensor. This permitted the discrimination of vegetation from the ground with an accuracy of up to 95%. In addition, a Canonical Discrimination Analysis (CDA) was able to discriminate mostly between soil and vegetation and, to a far lesser extent, between crop and weeds. The studied methodology arises as a good system for weed detection, which in combination with other principles, such as vision-based technologies, could improve the efficiency and accuracy of herbicide spraying.

Harrowing is often used to reduce weed competition, generally using a constant intensity across a whole field. The efficacy of weed harrowing in wheat and barley can be optimized, if site-specific conditions of soil, weed infestation and crop growth stage are taken into account. This study aimed to develop and test an algorithm to automatically adjust the harrowing intensity by varying the tine angle and number of passes. The field variability of crop leaf cover, weed density and soil density was acquired with geo-referenced sensors to investigate the harrowing selectivity and crop recovery. Crop leaf cover and weed density were assessed using bispectral cameras through differential images analysis. The draught force of the soil opposite to the direction of travel was measured with electronic load cell sensor connected to a rigid tine mounted in front of the harrow. Optimal harrowing intensity levels were derived in previously implemented experiments, based on the weed control efficacy and yield gain. The assessments of crop leaf cover, weed density and soil density were combined via rules with the aforementioned optimal intensities, in a linguistic fuzzy inference system (LFIS). The system was evaluated in two field experiments that compared constant intensities with variable intensities inferred by the system. A higher weed density reduction could be achieved when the harrowing intensity was not kept constant along the cultivated plot. Varying the intensity tended to reduce the crop leaf cover, though slightly improving crop yield. A real-time intensity adjustment with this system is achievable, if the cameras are attached in the front and at the rear or sides of the harrow.

In this work, we evaluate the role of agronomic factors in the selection for herbicide resistance in Apera spica-venti L. Beauv. (silky windgrass). During a period of three years, populations were collected in more than 250 conventional fields across Europe and tested for resistance in the greenhouse. After recording the field history of locations, a geo-referenced database has been developed to map the distribution of herbicide-resistant A. spica-venti populations in Europe. A Logistic Regression Model was used to assess whether and to what extent agricultural and biological factors (crop rotation, soil tillage, sowing date, soil texture and weed density) affect the probability of resistance selection apart from the selection pressure due to herbicide application. Our results revealed that rotation management and soil tillage are the factors that have the greatest influence on the model. In addition, first order interactions between these two variables were highly significant. Under conventional tillage, a percentage of winter crops in the rotation exceeding 75% resulted in a 1280-times higher risk of resistance selection compared to rotations with less than 50% of winter crops. Under conservation tillage, the adoption of >75% of winter crops increased the risk of resistance 13-times compared to rotations with less than 50% of winter crops. Finally, early sowing and high weed density significantly increased the risk of resistance compared to the reference categories (later sowing and low weed density, respectively). Soil texture had no significant influence. The developed model can find application in management programs aimed at preventing the evolution and spread of herbicide resistance in weed populations.

Site-specific weed management requires sensing of the actual weed infestation levels in agricultural fields to adapt the management accordingly. However, sophisticated sensor systems are not yet in wider practical use, since they are not easily available for the farmers and their handling as well as the management practice requires additional efforts. A new sensor-based weed detection method is presented in this paper and its applicability to cereal crops is evaluated. An ultrasonic distance sensor for the determination of plant heights was used for weed detection. It was hypothesised that the weed infested zones have a higher amount of biomass than non-infested areas and that this can be determined by plant height measurements. Ultrasonic distance measurements were taken in a winter wheat field infested by grass weeds and broad-leaved weeds. A total of 80 and 40 circular-shaped samples of different weed densities and compositions were assessed at two different dates. The sensor was pointed directly to the ground for height determination. In the following, weeds were counted and then removed from the sample locations. Grass weeds and broad-leaved weeds were separately removed. Differences between weed infested and weed-free measurements were determined. Dry-matter of weeds and crop was assessed and evaluated together with the sensor measurements. RGB images were taken prior and after weed removal to determine the coverage percentages of weeds and crop per sampling point. Image processing steps included EGI (excess green index) computation and thresholding to separate plants and background. The relationship between ultrasonic readings and the corresponding coverage of the crop and weeds were assessed using multiple regression analysis. Results revealed a height difference between infested and non-infested sample locations. Density and biomass of weeds present in the sample influenced the ultrasonic readings. The possibilities of weed group discrimination were assessed by discriminant analysis. The ultrasonic readings permitted the separation between weed infested zones and non-infested areas with up to 92.8% of success. This system will potentially reduce the cost of weed detection and offers an opportunity to its use in non-selective methods for weed control.

The loss of weed biodiversity in agricultural fields is a global issue that needs to be counteracted to preserve their supported ecosystem services and food webs. Many short-term efforts are undertaken to conserve weed species, especially already endangered ones, but several years after expiration, eventually result in species-poor communities. Understanding drivers of community composition is key to prevent biodiversity loss. To understand the factors that shape weed communities and influence weed diversity and endangered weed species, we monitored conventional and organic cereal fields in two regions of southwestern Germany. A redundancy analysis was performed on vegetation recordings and data from a farmer survey. Crop species, herbicide use, farming system, nitrogen, and light availability had the strongest impact on weed diversity. The weed communities were dominated by Alopecurus myosuroides, Galium aparine, Viola arvensis, Polygonum convolvulus, and Veronica persica, and were mainly shaped by crop species, tillage, location in the field, and timing of herbicide application. Bromus grossus and Bromus secalinus, two endangered weed species, survived in conventional field margins as a result of the use of herbicides with gaps for Bromus species. Conservation efforts are not restricted to organic farming and should consider the major drivers of weed communities. Precision farming techniques are available to create networks of habitats for endangered and common weed species and subsequently increase agro-biodiversity per se.

Herbicide resistant weeds need to be identified early so that yield loss can be avoided by applying proper field management strategies. A novel chlorophyll-fluorescence-imaging sensor has been developed to conduct real-time herbicide effect evaluation. In this research, greenhouse and field experiments were conducted to calibrate the capability of the sensor in monitoring herbicide effects on different biotypes of two grass weeds (Alopecurus myosuroides, Apera spica-venti) in southwestern Germany. Herbicides with different modes of action were applied for the effect monitoring. Chlorophyll fluorescence yield of the plants was measured 3⁻15 days after treatment (DAT) using the new fluorescence sensor. Visual assessment of the weeds was carried out on 21 DAT. The results showed that the maximal PS II quantum yield (Fv/Fm) of herbicide sensitive weeds was significantly lower than the values of resistant populations in 5 DAT. The new technology was capable of quickly identifying the herbicide’s effect on plants. It can be used to optimize management strategies to control herbicide resistant weeds.

The utilization of an effective stubble management practice can reduce weed infestation before and in the following main crop. Different strategies can be used, incorporating mechanical, biological, and chemical measures. This study aims at estimating the effects of cover crop (CC) mixtures, various stubble tillage methods, and glyphosate treatments on black-grass, volunteer wheat and total weed infestation. Two experimental trials were conducted in Southwestern Germany including seven weed management treatments: flat soil tillage, deep soil tillage, ploughing, single glyphosate application, dual glyphosate application, and a CC mixture sown in a mulch-till and no-till system. An untreated control treatment without any processing was also included. Weed species were identified and counted once per month from October until December. The CC mixtures achieved a black-grass control efficacy of up to 100%, whereas stubble tillage and the single glyphosate treatment did not reduce the black-grass population, on the contrary it induced an increase of black-grass plants. The dual glyphosate application showed, similar to the CC treatments, best results for total weed and volunteer wheat reduction. The results demonstrated, that well developed CCs have a great ability for weed control and highlight that soil conservation systems do not have to rely on chemical weed control practices.

Alopecurus myosuroides Huds. has become one of the most abundant grass weeds in Europe. High percentages of winter-annual crops in the rotation, earlier sowing of winter wheat and non-inversion tillage favor A.myosuroides. Additionally, many populations in Europe have developed resistance to acetyl-CoA carboxylase (ACCase), acetolactate synthase (ALS) and photosynthetic (PSII) inhibitors. Hence, yield losses due to A.myosuroides have increased. On-farm studies have been carried out in Southern Germany over five years to investigate abundance, control efficacies and crop yield losses due to A.myosuroides. Three crop rotations were established with varying proportions of winter- and summer-annual crops. The crop rotations had a share of 0, 25 and 50% of summer-annual crops. Within each crop rotation, three herbicide strategies were tested. In contrast to classical herbicidal mixtures and sequences, the aim of one of the herbicide strategies was to keep selection pressure as low as possible by using each mode of action (MOA) only once during the five years. A.myosuroides population was susceptible to all herbicide at the beginning of the experiment. Initial average density was 14 plants m−2. In the rotation with only winter-annual crops, density increased to 5347 ears m−2 in the untreated control plots. Densities were lower in the rotations with 25% and even lower with 50% summer-annual crops. Control efficacies against A. myosuroides in the herbicide strategy using only MOAs of the HRAC-groups B and A, according to the Herbicide Resistance Action Committee (HRAC) classification on MOA, dropped after five years compared to the strategy of changing MOA in every year. Nevertheless, the results demonstrate the need for combining preventive and direct weed-management strategies to suppress A.myosuroides and maintain high weed-control efficacies of the herbicides.

Weed hoeing can be successfully performed in wide row crops, such as sugar beet, maize, soybean and wide spaced cereals. However, little experience is available for hoeing in narrow cereal row spaces below 200 mm. Yet, mechanical weed control can pose an alternative to herbicide applications by reducing the herbicide resistant populations present in the field. In this experiment, it was investigated whether hoeing is feasible in cereals with 150 and 125 mm row spacings. The trial was set up at two locations (Ihinger Hof and Kleinhohenheim) in southwest Germany. Three different conventional hoeing sweeps, a goosefoot sweep, a no-till sweep and a down-cut side knife were adjusted to the small row widths, and hoeing was performed once with a tractor and a standard hoeing frame which was guided by a second human operator. The average grain yield, crop and weed biomass, and weed control efficacy of each treatment were recorded. The goosefoot and no-till sweep were tested at driving speeds of 4 and 6 km·h−1. The down-cut side knife was applied at 4 km·h−1. The results indicate that hoeing caused no yield decrease in comparison to a conventional herbicide application or manual weeding. The highest yield with a mechanical treatment was recorded for the no-till sweeps at both trial locations. Hoeing was performed successfully in narrowly spaced cereals of 150 and 125 mm, and the weed control efficacy of the mechanical treatments ranged from 50.9% at Kleinhohenheim to 89.1% at Ihinger Hof. Future experiments are going to focus on more distinct driving speeds ranging from 2 to 10 km·h−1 and performing more than one pass with the hoe. Additionally, combining the mechanical weeding tools with a camera-steered hoeing frame could increase accuracy, allow for higher working speeds and substitute the second human operator guiding the hoe.

Intercropping provides several benefits to the agro-ecosystem and plays an important role in Integrated Weed Management (IWM). In this study, we investigated the impact of living mulch in cereal crops on weed density and grain yield. Seven field experiments were conducted in Southwestern Germany. Perennial ryegrass and white clover were sown on the same day as the cereal crop (early) and when cereals had produced 3–5 leaves or the first tillers (late). Average weed density in the control plots without living mulch was 45 weeds m−2. Perennial ryegrass and white clover significantly reduced weed density to 22 plants m−2 and 25 plants m−2. Sowing date of living mulch had no effect on weed density. Grain yield was equal in all treatments. The results show that living mulch can suppress weeds without competing with the cereal crop.

Für die Unkrautbekämpfung in Zuckerrüben werden im frühen Wachstumsstadium der Pflanzen mehrmals großflächig Herbizide appliziert. In der vorliegenden Studie wurde untersucht, ob der Herbizideinsatz reduziert werden kann, indem Maßnahmen zur vorbeugenden, mechanischen und chemischen Unkrautkontrolle kombiniert werden. Die mechanische Unkrautbekämpfung zwischen den Reihen (inter-row) wurde in Feldversuchen an 6 Standorten mit einer Bandapplikation zwischen den Pflanzen (intra-row) kombiniert. An einem Standort wurde eine kamera- und eine GNSS-gesteuerte Reihenhacke eingesetzt. In den unbehandelten Parzellen (Kontrollversuch) wurde eine Unkrautdichte bis zu 91 Pflanzen m-2 nachgewiesen. Bandapplikationen in Kombination mit dem Hacken zwischen den Reihen reduzierten den Herbizideinsatz um 50 bis 75 % im Vergleich zur ganzflächigen Herbizidapplikation. Die Effektivität der Unkrautbekämpfung betrug 72 % bei der konventionellen Herbizidanwendung, 87 % bei der Kombination von Reihenhacke und Bandapplikation, 78 % für die Reihenhacke mit Kamerasteuerung und 84 % für die Reihenhacke mit GNSS-RTK-Steuerung. Durch die Unkrautbekämpfung stieg der bereinigte Zuckerertrag (BZE) – verglichen mit der unbehandelten Kontrollvariante – um 30 %. Die Kombination von mechanischer Unkrautkontrolle, Bandapplikation und präziser Reihenhacke als integrierte Unkrautbekämpfung führte zu guten Ergebnissen, d. h. der Herbizideinsatz konnte deutlich reduziert werden und die Unkrautbekämpfung wies eine hohe Wirksamkeit auf.

Herbicides may damage soybean in conventional production systems. Chlorophyll fluorescence imaging technology has been applied to identify herbicide stress in weed species a few days after application. In this study, greenhouse experiments followed by field experiments at five sites were conducted to investigate if the chlorophyll fluorescence imaging is capable of identifying herbicide stress in soybean shortly after application. Measurements were carried out from emergence until the three-to-four-leaf stage of the soybean plants. Results showed that maximal photosystem II (PS II) quantum yield and shoot dry biomass was significantly reduced in soybean by herbicides compared to the untreated control plants. The stress of PS II inhibiting herbicides occurred on the cotyledons of soybean and plants recovered after one week. The stress induced by DOXP synthase-, microtubule assembly-, or cell division-inhibitors was measured from the two-leaf stage until four-leaf stage of soybean. We could demonstrate that the chlorophyll fluorescence imaging technology is capable for detecting herbicide stress in soybean. The system can be applied under both greenhouse and field conditions. This helps farmers to select weed control strategies with less phytotoxicity in soybean and avoid yield losses due to herbicide stress.

Methylated seed oil (MSO) is a recommended adjuvant for the newly registered herbicide topramezone in China and also in other countries of the world, but the mechanism of MSO enhancing topramezone efficacy is still not clear. Greenhouse and laboratory experiments were conducted to determine the effects of MSO on efficacy, solution property, droplet spread and evaporation, active ingredient deposition, foliar absorption and translocation of topramezone applied to giant foxtail (Setaria faberi Herrm.) and velvetleaf (Abutilon theophrasti Medic.). Experimental results showed that 0.3% MSO enhanced the efficacy of topramezone by 1.5-fold on giant foxtail and by 1.0-fold on velvetleaf. When this herbicide was mixed with MSO, its solution surface tension and leaf contact angle decreased significantly, its spread areas on weed leaf surfaces increased significantly, its wetting time was shortened on giant foxtail but not changed on velvetleaf, and less of its active ingredient crystal was observed on the treated weed leaf surfaces. MSO increased the absorption of topramezone by 68.9% for giant foxtail and by 45.9% for velvetleaf 24 hours after treatment. It also apparently promoted the translocation of this herbicide in these two weeds.

The success of precision agriculture relies largely on our ability to identify how the plants’ growth limiting factors vary in time and space. In the field, several stress factors may occur simultaneously, and it is thus crucial to be able to identify the key limitation, in order to decide upon the correct contra-action, e.g., herbicide application. We performed a pot experiment, in which spring wheat was exposed to water shortage, nitrogen deficiency, weed competition (Sinapis alba L.) and fungal infection (Blumeria graminis f. sp. tritici) in a complete, factorial design. A range of sensor measurements were taken every third day from the two-leaf stage until booting of the wheat (BBCH 12 to 40). Already during the first 10 days after stress induction (DAS), both fluorescence measurements and spectral vegetation indices were able to differentiate between non-stressed and stressed wheat plants exposed to water shortage, weed competition or fungal infection. This meant that water shortage and fungal infection could be detected prior to visible symptoms. Nitrogen shortage was detected on the 11–20 DAS. Differentiation of more than one stress factors with the same index was difficult.