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.     

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.     

杂草密度与作物产量损失的预测模型

通过对国内外多个用于杂草密度和作物产量损失关系的经验模型比较分析，并对１０组不同来源的杂草与作物竞争资料进行模拟，证明模型Ｙ_Ｌ＝ｄ／（ａ＋ｂｄ）具有实际的生物学意义，能确地描述多种杂草和多种作物间的竞争关系，预测杂草竞争对作物可能造成的危害和损失。     

Sugarbeet yield response to competition from Sinapis arvensis or Lolium perenne growing at three different distances from the beet and removed at various times during early growth

A sugarbeet field experiment was conducted in 1999 and 2000 to measure beet yield where Sinapis arvensis or Lolium perenne were growing in the crop row at 2, 4 or 8 cm from the beet plants. The weeds were removed by cutting once in the growing season in either late May, mid‐June or early July. The number of neighbouring beet plants to every target beet plant was recorded. Projected leaf cover of a subset of the data with non‐cut weeds was analysed by using image analysis to investigate whether this could be used to predict beet yield loss early in the growing season. Increasing the distance between beet and weed from 2 to 8 cm increased the beet yield significantly by an average of 20%, regardless of weed species. The dry weight of non‐cut and re‐growing weeds at harvest time decreased when cutting was postponed to the period between mid‐June and early July. The number of neighbours described a sigmoidal yield decline of the single beet plants. Results from image analysis showed that approximately 33 g of beet yield was lost in October/November for each per cent relative projected leaf cover of the weeds in May, despite variation in growing conditions. The results are discussed in relation to potentials for robotic in‐row weed control.     

Weed competition in irrigated cotton (Gossypium barbadense L.) and groundnut (Arachis hypogaea L.) in the Sudan Gezira

Losses of crop yield due to weed competition in unweeded plots averaged nearly 60% of weed-free yields in cotton and 70% in groundnuts. Weed competition was not directly related to weed groundcover but was dependent on the seasonal growing conditions. The critical period of weed competition in both crops was the 6 weeks between 4 and 10 weeks after crop emergence. During this period cotton could tolerate up to 25% weed groundcover without appreciable loss in crop yield. Groundnuts could tolerate not more than 10% weed cover before yield loss occurred. A main factor in achieving standards of weed control within these limits was preventing the early growth of monocotyledonous weed species: pre-sowing application of trifluralin and benfiuralin provided this over a wide range of growing conditions.     

Relationships between crop yield and weed time of emergence/removal: modelling and parameter stability across environments

Seventeen Italian experiments relating to maize, soyabean and durum wheat were used to analyse the variability of duration of tolerated competition (DTC) and weed-free period (WFP) curves across reasonably homogeneous areas. The data sets were analysed by regression analysis using four models relating yield loss to weed density, time of emergence and removal. These models differ in the way they account for the effect of time of weed removal on potential competitiveness. A sigmoidal relationship between these two variables appears necessary. The model with the best overall performance was then used to test the stability of the parameters that give the shape of the curve in relation to time of emergence and removal. This was done by comparing a full model with shape parameters specific to each experiment and a reduced model with a common set of parameters for all the experiments referring to a specific crop. For all three crops, the residual sum of squares of the reduced model did not increase significantly, indicating that, across tested environments, the yield loss caused by mixed weed infestations can be expressed by a single set of parameters relating weed competitivity to time of emergence and removal. For a given area, it should therefore be possible to predict yield loss on the basis of a quite limited set of experiments, thus greatly simplifying the development and use of decision support systems (DSS).     

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.     

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.     

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.     

Prediction of competition between oilseed rape and Stellaria media

Ten experiments have investigated competition between winter oilseed rape and Stellaria media (common chickweed). Yield losses caused by this weed were often high, but differed greatly between experiments, 5% yield loss being calculated to be caused by 1.4–328 plants m^?2. Predictions of yield loss based on relative weed dry weights [weed dry weights/(crop + weed dry weights)] in December were somewhat less variable than those based on weed density, 5% yield loss being caused by 1.4–10.6% relative weed dry weight. The variations in yield loss were related to variations in the competitiveness of the oilseed rape and the S. media, caused by weather differences between years and sites, and the long period between weed assessment and harvest (8–10 months). However, despite the lack of precise relationships, there were indications that the greater the crop dry weights in December, the lower the final yield loss. Delayed sowing of oilseed rape until late September did not clearly increase the competitive effects of the weed compared with late August/early September sowings. Weed competition was not clearly affected by reduced crop density (44–113 plants m^?2), because of the compensatory ability of the lowest density. The results of the experiments are discussed in relation to the prediction of yield loss and, thus, possible adjustment of weed control strategies to meet expected crop losses.     

Influence de la densité et de la période de concurrence de Solanum nigrum L. sur la tomate de semis direct, en relation avec le désherbage

Effects of density and period of competition by Solanum nigrum L. on direct seeded tomatoes in relation to weed control The effects of density and period of competition from Solanum nigrum L. were measured in direct seeded tomatoes given weed control treatments currently used in south-east France. S. nigrum emerging after a diquat treatment at the 2–3 leaf stage of the crop and thinned to low densities (<12.8 plants ha^?1) at the 5–6 leaf stage of the crop caused significant yield loss if left to compete with the crop until harvest. Yield reduction was smaller if the same weed densities were present only until the onset of flowering. The regression curves of yield on weed density differed as annual climatic variations affected sowing date and plant growth; a comparison between years was made using the relation ‘crop yield × weed biomass/crop biomass’. Significant interactions between weed density and period of competition were found with yield of both green and red fruit. For late sown crops with low densities of S. nigrum two weed control treatments at the 5–6 leaf stage and at the onset of flowering were sufficient to prevent yield loss.     

Evaluation of three empirical models depicting Ambrosia artemisiifolia competition in white bean

The performance of three empirical models describing white bean yield loss (Y_L) from common ragweed competition was compared using field experiments from Staffa and Woodstock, both in Ontario, Canada, in 1991 and 1992. One model was based upon both weed density and relative time of emergence. The other two models described yield loss as a function of weed leaf area relative to the crop. The model based on both weed density and relative time of emergence best described the data sets. The predicted maximum yield loss (A) and the parameter for relative time of weed emergence (C) varied across locations and years whereas the yield loss at low weed density (I) was relatively more consistent across locations and years. Use of thermal time (base temperature=10^oC) rather than calendar days did not change the overall fit of the model, but reduced the value of the parameter for the relative time of weed emergence (C). The two parameter leaf area model accounting for maximum yield loss (m) gave a better fit to the data compared with the one parameter model. The relative damage coefficient (q) varied with time of leaf area assessment, location and year. Values of q calculated from relative leaf area growth rates of the crop and weed were similar to observed values. The relationship between q and accumulated thermal time was linear but varied with location and year. As management tools, models based upon relative leaf area have advantages over models based on density and relative time of emergence since the level of weed infestation needs only to be assessed once, whereas density and emergence time require frequent observations. The ability to assess accurately and quickly both the crop and weed leaf area, however, may limit the practical application of models based on leaf area. The inability of empirical models to account for year–to–year variation in environmental conditions was observed.     

硬草主要生物学特性及防除途径的研究

硬草是上海和江苏淮北地区麦田的主要禾本科杂草。通过对硬草的生物学特性，发生为害规律，与作物之间的竞争以及防除措施的研究，初步认为：１．硬草发生数量极大，对小麦具有较强的竞争能力；２．麦田硬草有较明显的出草高峰，这易受气候因素的影响；３．硬草与小麦竞争的临界期为小麦出苗后的２０－５０天之间，即小麦主茎叶龄４－６叶期。４．绿肥作物苕子能明显抑制硬草的萌发与生长，利用小麦－水稻－苕子－水稻轮作或小麦－水     

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.     

Comparison of empirical models depicting density of Amaranthus retroflexus L. and relative leaf area as predictors of yield loss in maize (Zea mays L.)

The outcome of crop-weed competition should be predicted as early as possible in order to allow time for weed control measures. Maize grain yield losses caused by interference from Amaranthus retroflexus L. (redroot pigweed) were determined in 1991 and 1992. The performance of three empirical models of crop-weed competition were evaluated. Damage functions were calculated based on the weed density or relative leaf area of the weed. In the yield loss-weed density model, values of I (percentage yield loss at low weed density) were relatively stable for similar emergence dates of A. retroflexus across years and locations. Estimated maximum yield loss (A) was more variable between locations and may reflect environmental variation and its effect on crop-weed competition, at least in 1991. The two-parameter yield loss-relative leaf area model, based on m (maximum yield loss caused by weeds) and q (the relative damage coefficient) gave a better fit than the single-parameter version of the model (which includes only q). In both relative leaf area models, the values of q varied between years and locations. Attempts to stabilize the value of q by using the relative growth rate of the leaves of the crop and weed were successful; however, the practical application of such relative leaf area models may still be limited owing to the lack of a method to estimate leaf area index quickly and accurately.     

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.     

Experimental methods in plant competition research in crop-weed systems

The implications of recent studies on the inappropriatness of replacement series and additive methods in competition studies, and some possible alternatives, are discussed in the context of weed research, Replacement series are usually inadequate to assess competitive interactions and can be misleading. In particular they may be biased in favour of the larger species. Many of the criticisms of replacement series also apply to additive experiments. Response models relating yield per individual to the densities of the species in the mixture provide methodology for answering many questions about mixtures. This paper proposes a framework for using these models to: (i) measure the effect of weed species on yield per individual and yield per unit area for the crop and weed species; (ii) develop methods of biological control of weeds both within a seaons and over seasons, based on the interference between crop and weed species and the population biology of the weed species; (iii) establish a cost-benefit analysis of certain of the biological weed-control programmes. The inclusion of the effect of relative emergence time and management practices in response models is considered as well as experimental design for crop-weed experiments.     

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.     

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.     

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.