Predicting the competitive effects of weed and crop density on weed biomass, weed seed production and crop yield in wheat

Competition between winter-sown wheat and Viola arvensis Murray or Papaver rhoeas L. was studied in two experiments in two successive years. The effects of varying crop and weed density were modelled in terms of weed biomass over time, weed seed production and crop yield. Biomass model parameters, representing maximum weed biomass and intra- and interspecific competition, were obtained for different assessment dates, enabling biomass levels to be predicted during the two growing seasons. Weed biomass declined, and its maximum level was reached earlier, with increasing crop density. Intraspecific competition was higher in the absence than in the presence of crop, increasing with time and with weed density. Halving the wheat population increased June biomass of V. arvensis by 74% and of P. rhoeas by 63%. Crop yield losses with increasing weed density were greater with low than with medium and high crop populations. P. rhoeas was significantly more competitive than V. arvensis in both years. Weed biomass in 1989 responded more to reductions in crop density following the milder winter of 1988/89 than in the previous year; however crop yields were less affected in 1989 due to summer drought, restricting late weed growth and competition. Weed seed production was related to weed biomass; the progressive lowering of crop density increased seed production, and both species were very prolific in the absence of crop. By combining models, seed production could be derived for a given competitive effect on the crop. Threshold weed populations, based on low weed levels that are not economic to control, could then be equated with the accompanying weed seed production.     

Influence of nitrogen on competition between cereals and their natural weed populations

The effects of nitrogen fertilizer on the growth and density of natural weed populations in spring barley (Hordeum vulgare L.) and winter wheat (Triticum aestivum L.) were investigated in the absence of herbicide. An increased level of applied nitrogen did not enhance: weed germination, tended to decrease the total weed biomass and had a differential effect upon the biomass of individual weed species in both wheat and barky. In competition with barley, Chenopodium album L. and Lamium spp. had lower nitrogen optima than the crop, while Urtica urens L. had a higher nitrogen optimum. In competition with wheat, Stellaria media (L.) Vill., Lamium spp. and Veronica spp. had lower nitrogen optima than the crop. The systematic changes in nitrogen effect with time were analysed by fitting orthogonal polynomials to the growth and density curves. The methodology could be recommended for other studies in which time or other systematic factors are included, as it supplies information which a traditional analysis of variance cannot provide. Since seed production is positively correlated with biomass, so nitrogen level affects seed production and, hence, the seed pool and future weed population, suggesting that fertilizer usage can be exploited in an integrated programme of crop: weed management. A trend towards lower N fertilizer application owing to concerns about the environment willfavour most of the weed species investigated in these experiments and change the composition of weed populations.     

Modelling the effects of sub-lethal doses of herbicide and nitrogen fertilizer on crop–weed competition

The effects of sub‐lethal dose of herbicide and nitrogen fertilizer on crop–weed competition were investigated. Biomass increases of winter wheat and a model weed, Brassica napus, at no‐herbicide treatment with increasing nitrogen were successfully described by the inverse quadratic model and the linear model respectively. Increases in weed competitivity (β₀) of the rectangular hyperbola and parameter B in the dose–response curve for weed biomass, with increasing nitrogen were also successfully described by the exponential model. New models were developed by incorporating inverse quadratic and exponential models into the combined rectangular hyperbola with the standard dose–response curve for winter wheat biomass yield and the combined standard dose—response model with the rectangular hyperbola for weed biomass, to describe the complex effects of herbicide and nitrogen on crop–weed competition. The models developed were used to predict crop yield and weed biomass and to estimate the herbicide doses required to restrict crop yield loss caused by weeds and weed biomass production to an acceptable level at a range of nitrogen levels. The model for crop yield was further modified to estimate the herbicide dose and nitrogen level to achieve a target crop biomass yield. For the target crop biomass yield of 1200 g m^?2 with an infestation of 100 B. napus plants m^?2, the model recommended various options for nitrogen and herbicide combinations: 140 and 2.9, 180 and 0.9 and 360 kg ha^?1 and 1.7 g a.i. ha^?1 of nitrogen and metsulfuron‐methyl respectively.     

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.     

Increased density and spatial uniformity increase weed suppression by spring wheat

It has been hypothesized that increased crop density and spatial uniformity can increase weed suppression and thereby play a role in weed management. Field experiments were performed over 2 years to investigate the effects of the density and spatial arrangement of spring wheat (Triticum aestivum) on weed biomass and wheat yield in weed-infested fields. We used three crop spatial patterns (normal rows, random and uniform) and three densities (204, 449 and 721 seeds m⁻²), plus a fourth density (1000 seeds m⁻²) in the random pattern. Increased crop density reduced weed biomass in all three patterns. Weed biomass was lower and crop biomass higher in wheat sown in the random and uniform patterns than in normal rows in both years. At 449 seeds m⁻², weed biomass was 38% lower in the uniform and 27% lower in the random pattern than in rows. There was evidence of decreasing grain yield due to intraspecific competition only at 1000 seeds m⁻². The results not only confirm that increasing density and increasing crop spatial uniformity increase the suppression of weeds, but also suggest that a very high degree of spatial uniformity may not be necessary to achieve a major increase in weed suppression by cereal crops. Rows represent a very high degree of spatial aggregation. Decreasing this aggregation increased weed suppression almost as much as sowing the crop in a highly uniform spatial pattern. While the random pattern produced as much crop biomass and suppressed weeds almost as well as the uniform pattern, the uniform pattern gave the highest yield.     

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.     

Influence of intra-row cruciferous surrogate weed growth on crop yield in organic spring cereals

In Northern Europe, inter-row hoeing has become a popular tactic for controlling weeds in organic cereals. Hoeing is highly effective and can be implemented from crop emergence until stem elongation to maintain a nearly weed-free inter-row zone. However, hoeing has a lesser effect on weeds growing in the intra-row zone, where crop–weed proximity results in heightened competition. In the hoed cereal system, it is investigated whether tall-growing, competitive, cruciferous weeds in the intra-row zone affect crop biomass, yield and thousand kernel weight (TKW). An additive experimental design is employed to enable the fitting of rectangular hyperbolas, describing and quantifying the effects of increasing intra-row surrogate weed density on crop growth parameters. Regressions were studied under the influence of crop (spring barley and spring wheat), row spacing (narrow [12.5 or 15.0 cm] and wide [25.0 cm]) and nitrogen rate (50 and 100 kg NH₄-N/ha). Cruciferous surrogate weeds were found to impact crop yield and quality severely. For example, ten intra-row plants/m² of surrogate weed Sinapis alba reduced grains yields by 7%–14% in spring barley and by 7%–32% in spring wheat with yield losses becoming markedly greater in wheat compared to barley as weed density increases. Compared to wheat, barley limited yield and quality losses and suppressed intra-row weed growth more. Row spacing did not have a consistent effect on crop or weed parameters; in one of six experiments, the 25 cm row spacing reduced yields and increased intra-row weed biomass in wheat. Nitrogen rate did not affect crop or weed parameters. Results warrant the implementation of additional tactics to control intra-row weeds and limit crop losses.     

Application method of nitrogen fertilizer affects weed growth and competition with winter wheat

The management of crop fertilization may be an important component of integrated weed management systems. A field study was conducted to determine the effect of various application methods of nitrogen (N) fertilizer on weed growth and winter wheat yield in a zero-tillage production system. Nitrogen fertilizer was applied at 50 kg ha⁻¹ at the time of planting winter wheat over four consecutive years to determine the annual and cumulative effects. The nitrogen treatments consisted of granular ammonium nitrate applied broadcast on the soil surface, banded 10 cm deep between every crop row, banded 10 cm deep between every second crop row, and point-injected liquid ammonium nitrate placed between every second crop row at 20 cm intervals and 10 cm depth. An unfertilized control was also included. Density, shoot N concentration and the biomass of weeds was often lower with subsurface banded or point-injected N than with broadcast N. The winter wheat density was similar with all N fertilizer application methods but wheat shoot N concentration and yield were consistently higher with banded or point-injected N compared with broadcast N. In several instances, the surface broadcast N did not increase the weed-infested wheat yield above that of the unfertilized control, indicating that it was the least preferred N application method. Depending on the weed species, the weed seedbank at the conclusion of the 4 year study was reduced by 29–62% with point-injected N compared with broadcast N. Information gained from this study will be used to develop more integrated weed management programs for winter wheat.     

Influence of sowing density and spatial pattern of spring wheat (Triticum aestivum) on the suppression of different weed species

To better understand the potential for improving weed management in cereal crops with increased crop density and spatial uniformity, we conducted field experiments over two years with spring wheat ( Triticum aestivum ) and four weed species: lambsquarters ( Chenopodium album ) , Italian ryegrass ( Lolium multiflorum ), white mustard ( Sinapis alba ), and chickweed ( Stellaria media ). The crops were sown at three densities (204, 449, and 721 seeds m⁻²) and in two spatial patterns (normal rows and a highly uniform pattern), and the weeds were sown in a random pattern at a high density. In most cases, the sown weeds dominated the weed community but, in other cases, naturally occurring weeds were also important. There were strong and significant effects regarding the weed species sown, the crop density, and the spatial distribution on the weed biomass in both years. The weed biomass decreased with increased crop density in 29 out of 30 cases. On average, the weed biomass was lower and the grain yield was higher in the uniform compared to the row pattern in both 2001 and 2002. Despite the differences in weed biomass, the responses of L. multiflorum , S. media , and C. album populations to crop density and spatial uniformity were very similar, as were their effects on the grain yield. Sinapis alba was by far the strongest competitor and it responded somewhat differently. Our results suggest that a combination of increased crop density and a more uniform spatial pattern can contribute to a reduction in weed biomass and yield loss, but the effects are smaller if the weeds are taller than the crop when crop–weed competition becomes intense.     

Invasiveness of agronomic weed species in wheat in Western Australia

Weed seeds are introduced to agronomic systems naturally or through human-mediated seed dispersal, and introduced seeds have a high chance of being resistant to selective, in-crop herbicides. However, colonisation (invasion) rates for a weed species are usually much lower than rates of seed dispersal. The current research investigated colonisation of a winter annual wheat cropping system in Western Australia by a range of winter or summer annual weed species. The weed seeds were sown (at 100 seeds/m²) directly before seeding the crop in 2016 and allowed to grow in the following 3 years of wheat. Selective herbicides were not applied, to simulate growth of weed populations if the initial seed had been resistant to herbicide. Bromus diandrus, Hordeum leporinum, Rumex hypogaeus, Sonchus oleraceus, Polygonum aviculare, Lolium rigidum, Citrullus amarus and Tribulus terrestris colonised the crop, while Dactyloctenium radulans, Chloris truncata and Salsola australis failed to establish over 3 years. The most successful weed was B. diandrus, with a plant density of 1,170/m² by the third year and seed production of 67,740/m². The high density of B. diandrus reduced wheat density by 76% in the third year and reduced average yield by 36%. Lolium rigidum reduced average yield by 11%, and the other weed species did not affect crop yield. Further research is required on the invasiveness of these species in other regions, but it is clear that the spread of B. diandrus to new areas or the introduction of resistant B. diandrus seeds via contaminated grain should be avoided.     

Using a competition model to quantify the optimal trade-off between machine vision capability and weed removal effectiveness

The algorithm of an optical detection system was first investigated for its ability to correctly classify transplanted crops and weeds during the critical early stages of crop establishment and its robustness over a range of different crop species. The trade-off was then examined between increasing the sensitivity of the detection system vs. the possibility of, in doing so, misclassifying some crop plants as weeds and inadvertently removing them. This was achieved by running a competition model using parameters derived from the image analysis and assessing the outcome of scenarios in terms of yield. The optimum parameter values to maximize the detection of the crop and the optimum parameter values to maximize the detection of the weed appeared relatively insensitive to time of image capture or weed density. They also appeared insensitive for different crop species where the crop had similar growth habit. However, competition scenarios indicated that the detection system parameter settings to achieve optimum yields were sensitive to the competitive ability of the weed species. For Veronica persica, crop yield was more sensitive to accidental crop removal than from competition. In contrast, in the presence of Tripleurospermum inodorum, yield loss was more attributable to weed competition. Importantly, linking the detection system with the competition model illustrated the principle that optimum yield may not necessarily be obtained by maximizing weed removal or minimizing crop removal. This first example of combining a detection system with a competition model presents a new opportunity to quantify the sensitivity of image classification in terms of yield.     

Cover crops and mulches influence weed management and weed flora composition in strip‐tilled tomato (Solanum lycopersicum)

This study was conducted in the Mediterranean environment of Central Italy from 2011 to 2013 with the aim of evaluating the effects of winter cover crops and their residues on weed composition in a cover crop‐tomato sequence. Treatments consisted of five soil managements (three cover crop species ‐ hairy vetch, phacelia, white mustard, winter fallow mulched with barley straw before tomato transplanting and conventionally tilled soil), two nitrogen fertilisation levels (0 and 100 kg N ha^?1) and two weed management levels (weed free and weedy) on tomato. Cover crop residues were arranged in strips on the soil surface and then used as beds for transplanting the tomato seedlings in paired rows. Rotary hoeing was performed in the bare strips between paired tomato rows. At tomato harvesting, the weed aboveground biomass and density was higher in nitrogen‐fertilised tomato than unfertilised tomato, except in hairy vetch and barley straw that showed similar values. Hairy vetch used as a cover crop and dead mulch was the most suppressive species with the highest production of residues, while phacelia and mustard were not suitable for controlling weeds. The tomato yield was high in nitrogen fertilised and weed‐free treatments, except in barley straw mulch, which showed similar values among the weed management treatments. The mulch strips caused variations in weed species composition that was mainly composed of perennial ruderal weeds, while in tilled soil, the weed flora was dominated by annual photoblastic weeds.     

Predicting the growth and competitive effects of annual weeds in wheat

The growth and competitiveness of 12 annual weed species were studied in crops of winter wheat, in which weeds were sown to give a wide range of plant densities. Weed growth patterns were identified; early species which senesced in mid-summer were less competitive than those with a growth pattern similar to that of the crop. Most species had little effect on crop yield in 1987, and this was attributed to a high crop den sity. Crop yield-weed density relationships for all species in 1988 and for Galium aparine in 1987 were well described by a rectangular hyperbola. Species were listed in the following competitive order based on the percentage yield loss per weed m^?2: Avena fatua > Matricaria perforata > Galium aparine > Myosotis arvenis > Poa trivialis > Alopecurus myosuroides > Stellaria media > Papaver rhoeas > Lamiumpur-pureum > Veronica persica > Veronica hederi-folia > Viola arvensis. Prediction of yield loss is discussed. The assumptions inherent in using Crop Equivalents (based on relative weights of weed and crop plants), are challenged; with intense competition, weed biomass at harvest failed to replace lost crop biomass, and harvest index was reduced. It is concluded that a competi tive index, derived from yield density relation ships, and expressed as the percentage yield loss per weed m^?2, is more likely to reflect the com petitive ability of a species than an index obtained from plant weights in the growing crop.     

Prediction of the competitive effects of weeds on crop yields based on the relative leaf area of weeds

For implementation of simple yield loss models into threshold-based weed management systems, a thorough validation is needed over a great diversity of sites. Yield losses by competition wsth Sinapis alba L. (white mustard) as a model weed, were studied in 12 experiments in sugar beet (Beta vulgaris L.) and in 11 experiments in spring wheat (Triticum aestivum L.). Most data sets were heller described by a model based on the relative leaf area of the weed than by a hyperbolic model based on weed density. This leaf area model accounted for (part of) the effect of different emerging times of the S. alba whereas the density model did not. A parameter that allows the maximum yield loss to be smaller than 100% was mostly not needed to describe the effects of weed competition. The parameter that denotes the competitiveness of the weed species with respect to the crop decreased the later the relative leaf area of the mustard was determined. This decrease could be estimated from the differences in relative growth rate of the leaf area of crop and S. alba. However, the accuracy of this estimation was poor. The parameter value of the leaf area model varied considerably between sites and years. The results strongly suggest that the predictive ability of the leaf area model needs to be improved before it can be applied in weed management systems. Such improvement would require additional information about effects of abiotic factors on plant development and morphology and the definition of a time window for predictions with an acceptable level of error.     

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.     

Competition between annual weeds and vining peas grown at a range of population densities: effects on the weeds

Linear regression of dry weight of weeds against crop density, together with the use of diversity indices and principal component analysis were used to derive information about changes in the behaviour of annual weeds over the growing season and in response to a wide range of crop densities in vining peas Pisum sativum L. Using linear regression it was possible to quantify reductions in weed dry weights per unit increase in crop plant density The ‘weed losse’ factor was acceptably consistent between experiments. Indices examining richness and evenness showed that numbers of weed species declined with increasing crop density and as the season progressed, but although species evenness became less at successive sampling dates the presence of a pea crop, whatever its density, did not radically alter the composition of the weed flora. Principal component analysis demonstrated that although there was competition within the weed flora, the crop did not replace the dominant weed species on high density plots, but reduced growth of all weed species alike.     

Modelling assimilation rates of 14 temperate arable weed species as a function of the environment and leaf traits

Information on the response of assimilation rate to environmental factors is lacking for many less competitive weed species that need to be considered in the context of increasing farm biodiversity. A pot experiment was sown to parameterize gross assimilation rate at light saturation and initial light use efficiency for 14 common UK annual weeds and winter wheat at four leaf temperatures. Field experiments were also sown to measure inter-specific differences in specific leaf area (SLA), leaf nitrogen content and assimilation rates in the field at near-optimum temperatures. A generic relationship describing the response of assimilation rate to temperature and light using SLA and leaf nitrogen content as conversion factors successfully predicted inter-specific differences in assimilation rates in the field. This relationship could be incorporated into weed–crop competition models to predict the productivity and competitive impact of weed mixtures, including species outside the current data set. Assimilation rates at light saturation in the field were determined largely by SLA. This trait was variable between species and within a species across the growing season and needs to be well described in mechanistic competition models to accurately calculate instantaneous assimilation rates.     

A simple model of crop loss by weed competition from early observations on relative leaf area of the weeds

A new simple empirical model for early prediction of crop losses by weed competition was introduced. This model relates yield loss to relative leaf area of the weeds shortly after crop emergence using the relative damage coefficient q as the single model parameter. The model is derived from the hyperbolic yield density relationship and therefore accounts for the effects of weed density. It is shown that the model also accounts for the effect of different relative times of weed emergence. A strong advantage of the approach is that it can be used when weeds emerge in separate flushes. The regression model described experimental data on sugar-beet – lambsquarters (Beta vulgaris L. –Chenopodium album L.) and maize-barnyard grass (Zea mays L. –Echinochloa crus-galli L.) competition precisely. The model describes a single relationship between crop yield loss and relative leaf area of the weeds over a wide range of weed densities and relative times of weed emergence. Possibilities for scientific and practical application of the model are discussed.