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.     

Modelling the effects of weeds on crop production

In most quantitative studies on interplant competition, static regression models are used to describe experimental data. However, the generality of these models is limited. More mechanistic models for interplant competition, which simulate growth and production of species in mixtures on the basis of the underlying physiological processes, have been developed in the past decade. Recently, simulation models for competition between species for light and water were improved and a detailed version was developed for sugarbeet and fat hen (Chenopodium album L.). The model was validated with data sets of five field experiments, in which the effect of fat hen on sugarbeet production was analysed. About 98% of the variation in yield loss between the experiments (which ranged from –6 to 96%) could be explained with the model. Further analysis with the model showed that the period between crop and weed emergence was the main factor causing differences in yield loss between the experiments. Sensitivity analysis showed a strong interaction between the effect of the variables weed density and the period between crop and weed emergence on yield reduction. Different quantitative approaches to crop-weed competition are discussed in view of their practical applicability. Simulations of experiments, where both the weed density and the period between crop and weed emergence were varied over a wide range, showed a close relation between relative leaf cover of the weeds shortly after crop emergence and yield loss. This relation indicates that relative leaf cover of the weeds accounts for both the effect of weed density and the period between crop and weed emergence. This relation has the potential to be developed into a powerful tool for weed-control advisory systems.     

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.     

Consequences of narrow crop row spacing and delayed Echinochloa colona and Trianthema portulacastrum emergence for weed growth and crop yield loss in maize

Echinochloa colona and Trianthema portulacastrum are weeds of maize that cause significant yield losses in the Indo‐Gangetic Plains. Field experiments were conducted in 2009 and 2010 to determine the influence of row spacing (15, 25 and 35 cm) and emergence time of E. colona and T. portulacastrum (0, 15, 25, 35, 45 and 55 days after maize emergence; DAME) on weed growth and productivity of maize. A season‐long weed‐free treatment and a weedy control were also used to estimate maize yield and weed seed production. Crop row spacing as well as weed emergence time had a significant influence on plant height, shoot biomass and seed production of both weed species and grain yield of maize in both years. Delay in emergence of weeds resulted in less plant height, shoot biomass and seed production. However, increase in productivity of maize was observed by delay in weed emergence. Likewise, growth of both weed species was less in narrow row spacing (15 cm) of maize, as compared with wider rows (25 and 35 cm). Maximum seed production of both weeds was observed in weedy control plots, where there was no competition with maize crop and weeds were in rows 35 cm apart. Nevertheless, maximum plant height, shoot biomass and seed production of both weed species were observed in 35 cm rows, when weeds emerged simultaneously with maize. Both weed species produced only 3–5 seeds per plant, when they were emerged at 55 DAME in crop rows spaced at 15 cm. Infestation of both weeds at every stage of crop led to significant crop yield loss in maize. Our results suggested that narrow row spacing and delay in weed emergence led to reduced weed growth and seed production and enhanced maize grain yield and therefore could be significant constituents of integrated weed management strategies in maize.     

Crop–weed competition rather than temperature limits the population establishment of two annual C4 weeds at the edge of their northern range

Climate change is predicted to affect range expansion of harmful C₄ weeds into the boreal region, given that they are able to successfully colonise both C₃ and C₄ crops. We studied the impact of a 3°C elevation in temperature on the establishment and maintenance of populations of two annual C₄ weeds (Amaranthus retroflexus and Echinochloa crus‐galli) with and without a competing C₃ (barley) or C₄ (maize) crop. Data obtained from field and glasshouse experiments were modelled using a periodic matrix population model. Competition of a weed with a crop appeared to be a more important factor for limiting the maintenance of weed populations than elevation in temperature, as neither of the weed species was able to maintain populations in competition with crops. Even an increase in the frequency of warm years did not result in viable weed populations establishing. However, A. retroflexus was able to form persistent populations in competition with maize when released from competition every fifth year. Simulations parameterised from glasshouse data predicted that both weed species would persist without competition in the current climate, whereas simulations parameterised from field data suggested only A. retroflexus to be able to persist. These results demonstrate that competition affects the range expansion of arable weed species more than elevation in temperature, necessitating the inclusion of crop–weed interactions in models of range shifts as a consequence of climate change.     

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.     

Effect of weed position on yield loss in soyabean and a comparison between relative weed cover and other regression models

The importance of the position of weeds with respect to crop rows in the determination of crop yield-weed density relationships and the usefulness of relative cover (RC) of the weeds as an explanatory variable were studied in soyabean [Glycine max (L.) Merrill] competing with two summer weeds with contrasting canopy structure (Xanthium strumarium L. ssp. italicum and Echinochloa crus-galli L.). The position of the weeds was of little importance in the relationship between yield loss and weed density. This information is important because published experiments have used different types of weed distribution (e.g. evenly distributed or sown in rows). For both weed species it was possible to obtain a single relationship between yield loss and RC for measurements made from 30 days after crop emergence to soyabean canopy closure. The competitive effect of the weeds appeared to be strictly related to RC, indicating that for weeds growing taller than the crop the main competitive factor may be the shading caused by the leaves of the weeds situated above the crop canopy.     

Improved management of Avena ludoviciana and Phalaris paradoxa with more densely sown wheat and less herbicide

Summary The effectiveness of crop competition for better weed control and reducing herbicide rates was determined for Avena ludoviciana and Phalaris paradoxa . Four experiments, previously broadcast with seeds of the two weeds in separate plots, were sown with three wheat densities, and emerged weeds were treated with four herbicide doses (0–100% of recommended rate). The measured crop and weed traits were first analysed across experiments for treatment effects. Grain yield and weed seed production data were then analysed using cubic smoothing splines to model the response surfaces. Although herbicide rate for both weeds and crop density for P. paradoxa had significant linear effects on yield, there was a significant non-linearity of the response surface. Similarly, herbicide rate and crop density had significant linear effects on weed seed production, and there was significant non-linearity of the response surface that differed for the weed species. Maximum crop yield and reduction in seed production of P. paradoxa was achieved with approximately 80 wheat plants m⁻² and weeds treated with 100% herbicide rate. For A. ludoviciana , this was 130 wheat plants m⁻² applied with 75% herbicide rate. Alternatively, these benefits were achieved by increasing crop density to 150 plants m⁻² applied with 50% herbicide rate. At high crop density, application of the 100% herbicide rate tended to reduce yield, particularly with the A. ludoviciana herbicide, and this impacted adversely on the suppression of weed seed production. Thus, more competitive wheat crops have the potential for improving weed control and reducing herbicide rates.     

Weed competition in spring-planted strawberries

Annual weeds germinating after planting strawberry (Fragaria chiloensis (L.) Duch. cv. Cambridge Favourite) in late March had no effect on crop growth if removed by late May. Dense weed cover thereafter severely inhibited stolon growth, virtually eliminating it if allowed to remain beyond mid-August. Shading by weeds inhibited leaf production and caused etiolation of existing leaves. New leaves appeared shortly after weed removal and few plants died unless weed cover persisted for most of the growing season. Further weed germination was allowed on some plots. Although not removed until late autumn, these weeds only had adverse effects on crop growth where initial weeding had occurred before mid-June. In one experiment, delaying weed removal until 6 July, 31 August or 2 November in the first year reduced fruit yield in the second (weed-free) year by 34%, 54% and 67% respectively. In a later experiment, competition from weeds until July or later in the first growing season gave fruit yields similar to those in the first experiment, but totally weed-free plots and those kept clean after weeding in mid-June produced less fruit than plots which remained weedy between mid-June and mid-August. It is suggested that competition from uncontrolled stolon growth in this experiment severely inhibited crown and hence truss production on plots which did not suffer weed competition. Unless left untouched until early September, weeds had less adverse effect on truss production than the stolons which they displaced. The results are interpreted in relation to improving the efficiency of weed control techniques.     

A new hypothesis for the functional role of diversity in mediating resource pools and weed–crop competition in agroecosystems

We develop a new conceptual model we call the Resource Pool Diversity Hypothesis (RPDH) aimed at explaining how soil resource pool diversity may mediate competition for soil resources between weeds and crops. The primary tenets of the RPDH are that (i) in plant communities, the intensity of inter-specific competition can depend upon the degree to which niche differentiation and resource partitioning occur among species, (ii) agricultural systems are unique in that management practices, such as crop rotation, source of fertility and weed management, result in inputs to the soil and (iii) these inputs directly or indirectly become soil resource pools from which crops and weeds may partition resources. The RPDH leads to the novel prediction that along a gradient of increasing cropping system diversity, yield loss due to weed–crop competition (i.e. the impact on yield per unit weed density) for soil resources should decrease. Similarly, the degree to which crops and weeds overlap in soil resource niche breadth (which is determined by species-specific functional traits for resource acquisition), will determine the extent to which weed–crop competition weakens as resource pool diversity increases. While there have been no direct tests of the RPDH, we highlight evidence from the agricultural literature that provides strong support for components of the hypothesis. Validation of the RPDH would have important implications across a broad range of cropping systems for the development of management strategies that aim to reduce yield loss impact per unit weed plant density and the fundamental principles of integrated weed management, such as the concepts of weed thresholds and critical periods.     

Critical period of weed competition in three vegetable crops in relation to management practices

The critical period of weed competition was determined in three vegetable crops: early cabbage (Brassica oleracea var. capitata L.), pickling cucumbers (Cucumis sativus L.), and field-seeded processing tomatoes (Lycopersicon esculentum L.). There were significant interactions between weed-removal treatments, year, and row width. Cabbage yields were reduced if plots were not kept weed-free for at least 3 weeks after transplanting or if weeds which emerged with the crop were allowed to remain longer than 4–5 weeks, Cucumber yields were reduced if plots were not kept weed-free for up to 4 weeks after seeding or if plots remained weed-infested longer than 3–4 weeks. Higher crop population densities (narrower row widths) in cabbage and cucumbers resulted in smaller plants, earlier competition from weeds, and therefore a shorter period that the crop could remain weed-infested without suffering reduced yields. Yields of direct-seeded tomatoes were reduced if plots were not kept weed-free for up to 9 weeks after seeding or if weeds which emerged with the crop were allowed to remain longer than 5 weeks. In each crop the timing of the critical period of competition was verified by weed removal only during this interval. There was a true critical period in direct-seeded tomatoes, but not in cabbage or cucumbers where a single weeding was sufficient to prevent yield losses.     

Critical periods of weed competition in cotton in Greece

Four experiments were conducted in central Greece during 1997 and 1998 to determine the late-season presence of weeds in cotton (Gossypium hirsutum L.) and the critical times for removing weeds. Experiments were conducted in natural, heavily infested cropland. The presence of weeds for more than 3 weeks after crop emergence caused significant reductions in crop growth and lint yields. However, weeds that emerged 11 weeks or more after crop emergence did not adversely impact yields. Total weed biomass increased with increasing time prior to weed removal. A weed-free period of 11 weeks after crop emergence was needed to prevent significant reductions in cotton height, biomass, number of squares, and yield. These results indicated that postemergence herbicides or other control measures should be initiated within 2 weeks after crop emergence to avoid significant yield reduction. For greater efficiency, soil-applied herbicides in cotton should provide effective weed control for at least 11 weeks. Curvilinear regression equations were derived to describe the relationship between critical periods of weed presence and cotton growth and fruit development.     

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.     

Competition of sorghum cultivars and densities with Japanese millet (Echinochloa esculenta)

Field studies were conducted at two locations in southern Queensland, Australia during the 2003–2004 and 2004–2005 growing seasons to determine the differential competitiveness of sorghum (Sorghum bicolor L. Moench) cultivars and crop densities against weeds and the sorghum yield loss due to weeds. Weed competition was investigated by growing sorghum in the presence or absence of a model grass weed, Japanese millet (Echinochloa esculenta). The correlation analyses showed that the early growth traits (height, shoot biomass, and daily growth rate of the shoot biomass) of sorghum adversely affected the height, biomass, and seed production of millet, as measured at maturity. “MR Goldrush” and “Bonus MR” were the most competitive cultivars, resulting in reduced weed biomass, weed density, and weed seed production. The density of sorghum also had a significant effect on the crop's ability to compete with millet. When compared to the density of 4.5 plants per m², sorghum that was planted at 7.5 plants per m² suppressed the density, biomass, and seed production of millet by 22%, 27% and 38%, respectively. Millet caused a significant yield loss in comparison with the weed‐free plots. The combined weed‐suppressive effects of the competitive cultivars, such as MR Goldrush, and high crop densities minimized the yield losses from the weeds. These results indicate that sorghum competition against grass weeds can be improved by choosing competitive cultivars and by using a high crop density of >7.5 plants per m². These non‐chemical options should be included in an integrated weed management program for better weed management, particularly where the control options are limited by the evolution of herbicide resistance.     

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.     

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.     

Modelling interactions between herbicide dose and multiple weed species interference in crop–weed competition

The effects of a range of herbicide doses on crop–multiple weed competition were investigated. Competitivity of Galium aparine was approximately six times greater than that of Matricaria perforata with no herbicide treatment. Competitivities of both weeds decreased with increasing herbicide dose, being well described by the standard dose–response curve with the competitivity of M. perforata being more sensitive than that of G. aparine to a herbicide mixture, metsulfuron‐methyl and fluroxypyr. A combined model was then developed by incorporating the standard dose–response curve into the multivariate rectangular hyperbola competition model to describe the effects of multiple infestation of G. aparine and M. perforata and the herbicide mixture on crop yield. The model developed in this study was used to predict crop yield and to estimate the herbicide dose required to restrict crop yield loss caused by weeds to an acceptable level. At the acceptable yield loss of 5% and the weed combination of 120 M. perforata plants m^?2 and 20 G. aparine plants m^?2, the model recommends a mixture of 1.2 g a.i. ha^?1 of metsulfuron‐methyl and 120 g a.i. ha^?1 of fluroxypyr.     

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.     

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.