Effects of weed harrowing and undersown clover on weed growth and spring cereal yield

Weed competition and nutrient scarcity often restrict organic cereal production, especially where the availability of livestock manure is limited. While harrowing of annual weeds and legume cover crops can be used, these methods are both executed in early spring and may hinder each other. Two cycles of a 2‐year crop rotation were carried out in south‐east Norway (60°42′N, 10°51′E, altitude 250 m) with weed harrowing and undersown cover crops (WHCC) at two fertiliser rates (40 and 100 kg nitrogen ha^?1). The effect of the WHCC treatments was measured by weed density and species, weed biomass, changes in weed seedbank and grain yield. The weed density depended on the interaction between WHCC, fertiliser and year. On average, pre‐emergence weed harrowing reduced weed density by 32% and weed biomass by 49%, while pre‐ and post‐emergence weed harrowing reduced weed density by 59% and weed biomass by 67% compared with the untreated control. Spergula arvensis became more abundant at low rather than at high fertiliser rates. On average, white clover cover crop sown after pre‐emergence weed harrowing resulted in the highest yields for both oat (+12.1%) and wheat (+16.4%) compared with the untreated control. Despite differences in weed population density and biomass among WHCC treatments within years, the weed biomass, weed density and seedbank increased for all WHCC treatments over the 4‐year period. More research is required into improving the efficacy of mechanical and cultural weed suppression methods that organic systems rely on.     

Potential uses of small unmanned aircraft systems (UAS) in weed research

Small unmanned aerial systems (UAS) with cameras have not been adopted in weed research, but offer low‐cost sensing with high flexibility in terms of spatial resolution. A small rotary‐wing UAS was tested as part of a search for an inexpensive, user‐friendly and reliable aircraft for practical applications in UAS imagery weed research. In two experiments with post‐emergence weed harrowing in barley, the crop resistance parameter, which reflects the crop response to harrowing, was unaffected by image capture altitude in the range from 1 to 50 m. This corresponded to image spatial resolution in the range from 0.3 to 17.1 mm per pixel. This finding is important because spatial resolution is inversely related to sensing capacity. We captured 20 plots comprising a total of about 0.2 ha in one image at 50 m altitude without losing information about the cultivation impacts on vegetation compared with ground truth data. UAS imagery also gave excellent results in logarithmic sprayer experiments in oilseed rape, where we captured 37 m long plots in each image from an altitude of 35 m. Furthermore, perennial weeds could be mapped from UAS images. These first experiences with a small rotary‐wing UAS show that it is relatively easy to integrate as a tool in weed research and offers great potential for site‐specific weed management.     

Modelling herbicide dose and weed density effects on crop:weed competition

The effects of a range of herbicide doses on crop:weed competition were investigated by measuring crop yield and weed seed production. Weed competitivity of wheat was greater in cv. Spark than in cv. Avalon, and decreased with increasing herbicide dose, being well described by the standard dose–response curve. A combined model was then developed by incorporating the standard dose–response curve into the rectangular hyperbola competition model to describe the effects of plant density of a model weed, Brassica napus L., and a herbicide, metsulfuron‐methyl, on crop yield and weed seed production. The model developed in this study was used to describe crop yield and weed seed production, and to estimate the herbicide dose required to restrict crop yield loss caused by weeds and weed seed production to an acceptable level. At the acceptable yield loss of 5% and the weed density of 200 B. napus plants m^–2, the model recommends 0.9 g a.i. metsulfuron‐methyl ha^–1 in Avalon and 2.0 g a.i. in Spark.     

Assessment of leaf cover and crop soil cover in weed harrowing research using digital images

Objective assessment of crop soil cover, defined as the percentage of leaf cover that has been buried in soil because of weed harrowing, is crucial to further progress in post‐emergence weed harrowing research. Up to now, crop soil cover has been assessed by visual scores, which are biased and context‐dependent. The aim of this study was to investigate whether digital image analysis is a feasible method to estimate crop soil cover in the early growth stages of cereals. Two main questions were examined: (i) how to capture suitable digital images under field conditions with a standard high‐resolution digital camera and (ii) how to analyse the images with an automated digital image analysis procedure. The importance of light conditions, camera angle, size of recorded area, growth stage and direction of harrowing were investigated, in order to establish a standard for image capture and an automated image analysis procedure based on the excess green colour index was developed. The study shows that the automated digital image analysis procedure provided reliable estimations of leaf cover, defined as the proportion of pixels in digital images determined to be green, which were used to estimate crop soil cover. A standard for image capture is suggested and it is recommended that digital image analysis be used to estimate crop soil cover in future research. The prospects of using digital image analysis in future weed harrowing research are discussed.     

Reduced crop sowing density improves performance of rare arable weed species more effectively than reduced fertilisation

Characteristic arable weed species of dryland cereal fields have undergone significant declines, due to agricultural intensification, to the point that some of them are considered rare. Crop edges host higher abundances of arable weed species, therefore they may act as a refuge for the conservation of these rare arable species. Using mesocosms, we experimentally tested how conditions at field edges (i.e. lower sowing densities and less intensive fertiliser applications) operate on the growth (biomass and height) and reproduction (reproductive biomass and flower onset) of six rare arable species. We found the rare arable species achieved lower biomass when growing with wheat compared with growing alone, and biomass of most of species was lower under high wheat sowing density than under low sowing density. In contrast, fertiliser application affected only two of the six arable species tested, especially when they were growing alone. Although the time to flowering was not affected by the conditions tested, reproductive biomass showed the same trends as overall biomass. These results indicate that conservation of rare arable species must primarily consider reductions in crop competition to increase their biomass and reproductive ability.     

Evaluating the potential of Unmanned Aerial Systems for mapping weeds at field scales: a case study with Alopecurus myosuroides

Mapping weed densities within crops has conventionally been achieved either by detailed ecological monitoring or by field walking, both of which are time‐consuming and expensive. Recent advances have resulted in increased interest in using Unmanned Aerial Systems (UAS ) to map fields, aiming to reduce labour costs and increase the spatial extent of coverage. However, adoption of this technology ideally requires that mapping can be undertaken automatically and without the need for extensive ground‐truthing. This approach has not been validated at large scale using UAS ‐derived imagery in combination with extensive ground‐truth data. We tested the capability of UAS for mapping a grass weed, Alopecurus myosuroides , in wheat crops. We addressed two questions: (i) can imagery accurately measure densities of weeds within fields and (ii) can aerial imagery of a field be used to estimate the densities of weeds based on statistical models developed in other locations? We recorded aerial imagery from 26 fields using a UAS . Images were generated using both RGB and R_mod (R_mod 670–750 nm) spectral bands. Ground‐truth data on weed densities were collected simultaneously with the aerial imagery. We combined these data to produce statistical models that (i) correlated ground‐truth weed densities with image intensity and (ii) forecast weed densities in other fields. We show that weed densities correlated with image intensity, particularly R_mod image data. However, results were mixed in terms of out of sample prediction from field‐to‐field. We highlight the difficulties with transferring models and we discuss the challenges for automated weed mapping using UAS technology.     

Effects of rye cover crop residue and herbicides on weed control in narrow and wide row soybean planting systems

Α three‐year, non‐irrigated field study was conducted in 1998, 1999, and 2000 at the Southern Weed Science Research Unit farm, Stoneville, MS to study the effects of rye cover crop residue, soybean planting systems, and herbicide application programs on the control, density and biomass of several weed species and soybean yield. The soybean planting systems comprised 19 cm rows with high plant density, 57 cm rows with medium plant density, and 95 cm rows with low plant density. The herbicide programs evaluated were pre‐emergence, postemergence, pre‐emergence followed by postemergence, and no herbicide. Flumetsulam and metolachlor were applied pre‐emergence, and acifluorfen, bentazon, and clethodim were applied postemergence. The presence or absence of rye cover crop residue and a soybean planting system did not affect weed control of the species evaluated (browntop millet, barnyard grass, broadleaf signal grass, pitted morningglory, yellow nutsedge, Palmer amaranth and hyssop spurge), when herbicides were applied, regardless of the application program. In addition, rye cover crop residue was not an effective weed management tool when no herbicide was applied, because density and biomass of most weeds evaluated were higher than a no cover crop residue system. Among soybean planting systems, narrow with high plant density soybeans reduced density of grasses, broadleaf weeds and yellow nutsedge by 24–83% and total weed biomass by 38%, compared to wide with low plant density soybeans. Although weed pressure was reduced by narrow with high plant density soybeans, herbicide applications had the most impact on weed control, weed density and biomass. All herbicide programs controlled all weed species 81–100% at two weeks after postemergence herbicide applications, in comparison to no‐herbicide. Density of grasses and all broadleaf weeds as well as total weed biomass was lower with the pre‐emergence followed by postemergence program than these programs alone. Soybean yields were higher in the pre‐emergence followed by postemergence, and postemergence only programs than the pre‐emergence alone program. Planting crops in narrow rows is one cultural method of reducing weed pressure. However, even with the use of this cultural practice, prevalent weed pressure often requires management with herbicides.     

Spatial patterns,species richness and cover in weed communities of organic and conventional no‐tillage spring wheat systems

Heterogeneous field conditions are ubiquitous throughout agricultural systems and have given rise to the practice of site‐specific management, in an effort to increase sustainability and/or homogenise growing conditions and thereby increase crop yields. The spatial pattern of weeds in conventional systems is widely accepted to be aggregated, but there have been no scientific studies regarding the spatial pattern of weed distribution in organic systems. Using a combination of aggregation measures and quadrat variance techniques, this study compared the spatial pattern of weed distribution in conventionally managed no‐tillage spring wheat fields to those of organically managed spring wheat fields. Per cent weed cover data (by species) were collected in the summers of 2005 and 2006 from transects located in conventional no‐tillage and organic spring wheat fields. Weed cover was aggregated in both the conventional and the organic systems, but the patterns of aggregation were different for the two systems. Conventional no‐tillage systems showed a patch/gap pattern, while organic systems showed multiple scales of patchiness with few gaps. These results suggest that processes causing aggregation in the two systems may be different and that site‐specific management may be applicable to organic systems as well as conventional spring wheat systems.     

Effect of tillage, cover crop and crop rotation on the composition of weed flora in a sandy soil

The development of integrated weed management strategies requires knowledge of mechanisms that influence compositional changes in weed flora. A 9-year study was initiated in 1988 at Delhi, Canada, on a loamy sand soil to evaluate the effect of tillage systems [conventional (CT) and no-till (NT)] and cover crops (only in NT) on weed density, species composition and associations, and crop yield in a winter wheat ( Triticum aestivum L.)/bean/winter wheat rotation. Three bean types: soyabean ( Glycine max L. Merr.), white bean ( Phaseolus vulgaris L.) and kidney bean ( P . vulgaris L.) were included. The NT system included variations: rye ( Secale cereale L.) or maize ( Zea mays L.) cover crop, volunteer wheat disked after harvest and wheat stubble. Data were collected in 1994, 1995 and 1996. Tillage systems, cover crops and crop type had differential effects on weed densities, species composition and associations. Weed densities were not affected by tillage or cover crops in wheat but, in the beans, densities were greater in the CT than in the NT systems. Various associations of weed species with tillage system, cover crop and crop type were observed. Crop yields were not affected by tillage type or cover crop, except that soyabean yields were highest in plots with cover crops.     

Use of phytotoxic rice crop residues for weed management

There is a general perception among Cambodian rice (Oryza sativa) farmers that, after harvesting, rice crop residues that are incorporated into the field benefit the growth of the subsequent rice crop. However, the effect of this action upon weed establishment and growth has not yet been considered. A series of pot and field trials were conducted to determine whether such action could inhibit weed establishment and/or growth. The pot studies first evaluated the response of the test plant (rice line ST‐3) and three weed species, barnyardgrass (Echinochloa crus‐galli), small umbrella sedge (Cyperus difformis), and water primrose (Ludwigia octovalves), to the residue of 16 rice lines and the field trials were later conducted to evaluate the response of the same test plants to the residue of seven putatively allelopathic rice lines and one non‐allelopathic rice line. The residue of all the studied rice lines, depending on how long they had been incorporated into the soil, reduced the establishment and growth of all three weed species, as well as the rice crop. However, if the residue's incorporation was delayed by 2 weeks or only a proportion of the residue was incorporated, the rice crop could withstand the growth‐inhibiting effect, while the inhibition of the establishment and growth of the three weed species was retained. These responses of rice and the weeds to rice crop residues might provide a basis for a weed management strategy, particularly in the resource‐poor rice‐production systems of Cambodia.     

Modelling the effect of crop and weed on herbicide efficacy in wheat

Recommended field application rates of herbicides have to give effective weed control in every situation and are, thus, often higher than that required for specific fields. An understanding of the interaction between crop:weed competition and herbicide dose may, in many cases, allow herbicide application rates to be reduced, important both environmentally and economically. We have developed a model of the interaction between crop:weed competition and herbicide dose, using an empirical model of the relationship between crop yield and weed biomass (related to weed density), and an empirical model of the relationship between weed biomass and herbicide dose. The combined model predicts crop yield, given herbicide dose and weed biomass at an interim assessment date. These crop yield loss predictions may be used to quantify the herbicide dose required to restrict yield loss to a given percentage. Parameters of the model were estimated and the model tested, using results from experiments, which used cultivated oats ( Avena sativa ) or oilseed rape ( Brassica napus ) as model weeds in a crop of winter wheat ( Triticum aestivum ).For the crop:weed:herbicide combinations investigated there was little increase in crop yield for herbicide dose rates above 20% of recommended field rates, in broad agreement with the model predictions. There may still be potential for further reduction below this level on economic grounds; the model could be used to estimate the `break-even' herbicide dose.