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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.

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.

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.

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”.

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.

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%.

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.

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.