Annual weed distributions can be mapped with kriging

The authenticity of weed distribution maps prepared by the geostatistical estimation method, kriging, was investigated. We concentrated on the total number of weed plants and the dominant weed genus Veronica spp. in a 2.1-ha field of winter wheat. Different sampling distances were evaluated. Our analyses showed that kriging weed densities based on seedling counts collected in, 0.25.m² circles in a sampling grid of approximately 10 m × 10 m gave good agreement with actual observations. Reducing the sampling grid to 20 m × 30 m gave poor agreement. New sampling methods combined with positioning devices and injection sprayers are discussed with reference to site-specific weed management.     

A classification methodology for the risk of weed infestation using fuzzy logic

Despite modern weed control practices, weeds continue to be a threat to agricultural production. Considering the variability of weeds, a classification methodology for the risk of infestation in agricultural zones using fuzzy logic is proposed. The inputs for the classification are attributes extracted from estimated maps for weed seed production and weed coverage using kriging and map analysis and from the percentage of surface infested by grass weeds, in order to account for the presence of weed species with a high rate of development and proliferation. The output for the classification predicts the risk of infestation of regions of the field for the next crop. The risk classification methodology described in this paper integrates analysis techniques which may help to reduce costs and improve weed control practices. Results for the risk classification of the infestation in a maize crop field are presented. To illustrate the effectiveness of the proposed system, the risk of infestation over the entire field is checked against the yield loss map estimated by kriging and also with the average yield loss estimated from a hyperbolic model.     

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.     

Precision farming for weed management: techniques

Site-specific weed control techniques have gained interest in the precision farming community over the last years. Managing weeds on a subfield level requires measuring the varying density of weeds within a field. Decision models aid in the selection and adjustment of the treatments, depending on the weed infestation. The weed control can be done either with herbicides or mechanically. A site-specific herbicide application technology can save large amounts of herbicides. Mechanical weed control techniques adapting to the weed situation in the field are applicable to a wide spectrum of crops. Site-specific techniques for the detection and management of weeds are presented. A system for the discrimination of different weed species and crops from images is described, which generates weed maps automatically. Models for the yield effect of weeds are developed and applied in on-farm-research experimental setups. Economic weed thresholds are derived and used for a herbicide application with a patch sprayer.     

Spatial correlation between weed species densities and soil properties

The spatial cross‐correlation between weed species densities and six soil properties within fields was analysed using cross‐semivariograms. The survey was carried out in three successive years in two fields. The most consistent relationship between weed species density (numbers m^?2) and soil properties was negative cross‐correlation between the density of Viola arvensis Murray and clay content. This correlation was found in both fields; however, the range of spatial dependence varied between fields. In one of the fields, the density of Lamium purpureum L. was positively cross‐correlated with the phosphorus content in the soil in all years. The density of Veronica spp. and Poa annua L. was negatively cross‐correlated with pH in all three years. Other spatial cross‐correlations that were found in this study were inconsistent over time or field site. The densities of some of the weed species were spatially cross‐correlated with more than one soil property. The results showed that the range of spatial dependence varied not only between fields, but also between weed species and soil properties, as well as between years. This study indicates that the weed pattern is field‐specific and that the spatial variation in soil properties within a field is one of several factors affecting weed patchiness.     

Predicting the risk of weed infestation in winter oilseed rape crops

Chemical weed control before crop and weed emergence is a systematic practice in winter oilseed rape crops in France. It would be profitable both for farmers and the environment to predict the level of weed infestation early on in the growing season and to control weeds only when necessary using post‐emergence weed control. The objective of this paper was to develop and evaluate simple models to predict weed biomass in oilseed rape crops. The model input variables were related to weed population characteristics and farmers’ practices. The models can be used to classify oilseed rape plots into two categories: plots with a level of weed infestation above a threshold or those with level of weed infestation below a threshold. A data set including 3 years of experiments, conducted across several regions in France, was used to estimate the parameters and to evaluate the models. High values of sensitivity and specificity were obtained when weed biomass was predicted as a function of sowing date, type of soil tillage, soil mineral nitrogen, crop density, weed density at emergence, and main characteristics of the most abundant weed species. Model performance strongly decreased when input variables related to the weed population were not taken into account. The best models correctly classified 90% of the plots with high weed infestation and 64% of the plots with low weed infestation.     

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.     

Annual weed competition in wheat crops: the effect of weed density and applied nitrogen

Experiments investigating the effect of weed density on the yjeld of a wheat crop at three levels of applied nitrogen were conducted in north-western Victoria. Australia, during 1970. There were five sites, each infested with a pure stand of one of the following annual broad-leaved weed species: Lithospermum arvense, Brassica tournifortii. Lamium amplt'xicaule, Amsinckia hispida and Fumaria parviflora. At the three-leaf stage of crop growth, the weed populations were systematically thinned with a specially developed spray boon) (which is described) to give a range of weed densities in competition) with the crop. The relalionship between dry matter production and population density for all but one weed species was curvilinear, but the degree of curvature was small and competition in the wheat crop was linear for four of the five weed species. There were large differences in the competitive ability of individual weed species and these have been described by regression equations. Applied nitrogen increased wheat yields at all sites but weed competition was not affected. The use of these grain yield-weed density relationships in predicting crop losses from weed competition is discussed.     

Effects of density and sowing pattern on weed suppression and grain yield in three varieties of maize under high weed pressure

We tested the hypothesis that improved weed suppression by maize can be achieved through increased crop density and spatial uniformity. Field experiments on three varieties of maize sown at three densities (5, 7 and 10.5 seeds m^?2) and in two spatial patterns (grid pattern and rows) under very high weed pressure from Brachiaria brizantha were performed in 2012 and 2013. We measured weed biomass 1 month after sowing and at harvest, and grain yield at harvest. Density, variety and sowing pattern all had strong and significant effects on both weed biomass and yield. On average, weed biomass was reduced (by 72% in the first year and 58% in the second year), and grain yield was increased (by 48% and 44%) at the highest density in the grid pattern compared with standard sowing practices (medium density, row pattern). There was a significant density × variety interaction, which is evidence for genetic differences in the response of the varieties to density in characteristics that influence weed suppression. The variety that suppressed weeds best at high density had the lowest variation in the angle of insertion of the oldest living leaf at harvest (leaf 6), supporting the hypothesis that reduced phenotypic plasticity may be advantageous for weed suppression under high density and spatial uniformity. Increased density and uniformity can contribute to weed management in maize in many cases, potentially reducing the need for herbicides or mechanical weed control.     

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.     

Assessing regional scale weed distributions, with an Australian example using Nassella trichotoma

Knowledge of the spatial distribution of weed infestations over regional scales is essential for effective management of source populations and to assess future threats. To this end, the distributions of Nassella trichotoma across a study area in south‐east New South Wales, Australia, were analysed using the geographically local Getis–Ord G_i* spatial hotspot clustering statistic. The clustering of N. trichotoma observations was analysed at three infestation levels: presence (at any density), patch level and the occasional plant level. The results indicate that there are c. 578 km² of cells containing N. trichotoma in strongly clustered infestations, 11.2 km² within weakly clustered infestations distinct from the main clusters, and 55 km² that are not clustered. There are 117 km² of strongly clustered patch level cells, 3 km² in distinct but weak clusters, and none outside of a cluster area. Of the occasional plant level cells, 329 km² are strongly clustered, 6.2 km² are in distinct but weak clusters, and 19 km² are not clustered. These results provide a mechanism by which control efforts can be prioritized. The analysis approach described in this paper provides a consistent, quantitative and repeatable approach to assess weed infestations across regional scales and can be applied to any weed species for which spatial distribution data are available.     

Detecting the spatial component of variation in the weed community at the farm scale with variation partitioning by canonical correspondence analysis

Variation partitioning by canonical correspondence analysis (CCA) was applied to analyse spatial variation in the species composition of a weed community for an area of farmland in southern Finland. The farmland, covering 450 ha, was sampled with a 60 m × 60 m grid. Data on weed species were collected along with the following groups of explanatory variables: spatial variables (the terms of second-order polynomial trend surface regression equation generated on the x and y co-ordinates of sample quadrats: x, y, x², xy, y², x²y and xy²), farmer variables (nine farms), soil variables (four soil types and pH value), crop variables (barley, oats, sugarbeet, potato and turnip rape) and physical variables (area of field, altitude, slope and aspect in four directions). The main variation in species composition along the first and second CCA axes was caused by interplay between farmer and crop variables. Farmer and crop variables explained more of the variation than did soil or physical variables. All the variables were to some extent spatially structured. The spatial variables contributed 54.5% of the total variation, of which pure spatial variation accounted for 12.2%. The highest covariation with spatial variables was detected with farmer (33.7%) and crop variables (25.7%). Variation partitioning by CCA is recommended for studying the relationship between the spatial variation in weed communities and explanatory variables.     

Avena sterilis and Lolium rigidum infestations hamper the recovery of diverse arable weed communities

Intensification of agricultural practices has severely reduced weed diversity in arable fields, which affects the delivery of ecosystem services. However, in parallel, some species have benefited from intensive farming and have vastly increased their abundance, as is the case for Lolium rigidum and Avena sterilis in cereal fields. These highly competitive species severely reduce yields but can also compete with other weed species, and, when less intensive practices are applied, they might limit the recovery of weed diversity and the success of arable species reintroductions. A gradient of infestation was established in a winter wheat field in Catalonia (north‐eastern Spain) by sowing seeds of both species at three different densities to test their effects on the abundance, diversity and composition of the natural weed community. The emergence of seeds and the survival and biomass of transplanted seedlings of two rare species, Agrostemma githago and Vaccaria hispanica, were also evaluated. Avena sterilis and L. rigidum infestations reduced the diversity, abundance and biomass and changed the composition of the natural weed community, even at low infestation densities. Moreover, infestations of both species affected the overall performance of A. githago and V. hispanica. This study reveals that A. sterilis and L. rigidum are highly competitive and that their infestations might hamper the recovery of diverse weed communities. Their densities should be considered when selecting suitable sites for promoting diversity and reintroducing rare species.     

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.     

A survey of weed seed contamination of rice paddy in Cambodia

Cambodia has experienced a rapid shift from transplanted to hand broadcast seeded rice, with a consequent increase in seeding rates from 25–30 to 100–200 kg ha^?1. To reduce costs, farmers keep their own seed for sowing with the risk of greater weed seed contamination of the sowing seed. A survey of weed seed contamination in harvested rice paddy was conducted in two provinces of Cambodia (Battambang and Takeo) at the end of the wet season in 2016. Farmers were interviewed about rice‐seeding practices, and a total of 110 farmers' fresh paddy samples were inspected for weed seed contamination from the two provinces. Sowing seed samples collected from 28 seed producer lots and 71 samples of farmer‐kept seed were also analysed for weed seed contamination. In both provinces, the majority of farmers kept their own seed or bought seed from a neighbour. Farm‐kept seed for sowing accounted for 88% of sown seed in Battambang and 89% in Takeo. Seeds of 41 different weed species from 13 plant families were found in the farmers' freshly harvested paddy samples. Overall, farmers managed to reduce the number of weed propagules by 60% and seed producers by 95%. There was no significant difference between farmer‐kept seed and seed producer/seed company seed for the total number of weed seeds present. When shown photos, farmers' rankings of the 10 most common weed species found in freshly harvested paddy did not closely correspond to the actual weed seed frequency in the paddy. When farmers were asked to rank the frequency of weeds in their fields without the option to choose from a list, they ranked the weeds differently. Farmers ranked Ischaemum rugosum, Echinochloa spp. and Fimbristylis miliacea as the three most frequent weed species in their fields. The most frequent weeds in harvested paddy, apart from weedy rice, were I. rugosum and Melochia corchorifolia. Farmers did not rank M. corchorifolia as a frequently occurring weed, and most farmers could not recognise M. corchorifolia from photographs. The priority for improved seed hygiene is to place the emphasis on assisting farmers to further improve their seed purification techniques and to caution them to inspect seed before purchasing from neighbours, seed producers and seed companies in the absence of the implementation of seed certification regulation.     

Distribution of parthenium weed (Parthenium hysterophorus L.), an alien invasive weed species threatening the biodiversity of Islamabad

Biological invasion by alien invasive species is now recognized as one of the major threats to native species and ecosystems. Parthenium weed ( Parthenium hysterophorus L.), an alien invasive weed species, is spreading throughout Pakistan. Worldwide, it has been designated as one of the most troublesome weed species. The adverse effects of this weed on human beings, livestock, crop production, and biodiversity are well-documented. As a result of a lack of information on its spread in Pakistan since its invasion, a phytosociological survey, with special reference to parthenium weed, was carried out in Islamabad from August–October 2002. Six main sectors of Islamabad were selected for sampling. The phytosociological survey of these sectors of Islamabad revealed a total of 30 weed species to be associated with P. hysterophorus . The survey also showed a high relative frequency, relative density, and importance value of P. hysterophorus in general; however, the percentage relative frequency of the weed in these sectors ranged from 10.6–30.3%. This survey revealed that P. hysterophorus had an appreciable degree of sociability with Senna occidentalis (L.) Link, Malvastrum coromandelianum (L.) Garcke and Lantana camara (L.). The data on the association of L. camara with P. hysterophorus suggests that a transition phase of competition or succession is in progress between these two alien species. The population of many common medicinal plants growing in the wastelands of Islamabad might be rapidly declining because of the aggressive colonization by P. hysterophorus . The ever-increasing infestation of this weed in urban areas also poses a serious threat to the health of the inhabitants of Islamabad.     

Threshold level and seed production of velvetleaf (Abutilon theophrasti Medicus) in maize

Four tests were carried out in 1980 and 1981 to determine: (a) the economic threshold density of Abutilon theophrasti Medicus (velvetleaf) in maize, and (b) seed production with varying densities of infestation, both in the presence and in the absence of maize. The infestation was artificially created, and the density of the weed ranged from 0 to 80 plants m^?2. The economic threshold, calculated using the Cousens (1987) model, varied between 0?3 plants m^?2 and 2?4 plants m^?2, depending on the variables considered. The presence of maize reduced the seed-rain of A. theophrasti by 50%. This seed-rain reached its maximum level at 20–30 plants m^?2 in maize, and at 30–35 plants m^?2 in weed monoculture. However, with only 4–5 plants m^?2 in competition with maize, A. theophrasti produced 8–10 thousand seeds m^?2. The usefulness of threshold density in weed management is debatable when one considers the ecological characteristics of the A. theophrasti seed, and the great capacity of seed production of this weed.     

Response of Sorghum halepense demographic processes to plant density and rimsulfuron dose in maize

In spatially heterogeneous weed infestations, variable dose technologies could be used to minimise herbicide use; high doses could be applied to reduce high‐density patches and low doses to maintain weed populations in low‐density portions of a field. To assess the potential short‐ and long‐term effects of variable herbicide dose and site‐specific management, the major weed demographic processes were described and parameterised in this study. Various doses of rimsulfuron (from 0 to 12.5 g a.i. ha^?1) were applied to different densities of Sorghum halepense (0–100 plants m^?2). Contrary to similar studies with other weed species, higher herbicide efficacy was not observed at low densities, suggesting that the same rimsulfuron dose should be applied regardless of the S. halepense density. The highest percentage of control was obtained with the full rimsulfuron dose. However, it did not guarantee a decrease of the infestation in the following season in the field areas where the initial S. halepense density was lower than 60 plants m^?2. Reduced doses of rimsulfuron to control S. halepense cannot be recommended based on our results.     

Evaluating field‐scale sampling methods for the estimation of mean plant densities of weeds

The weed flora (comprising seven species) of a field continuously grown with soyabean was simulated for 4 years, using semivariograms established from previous field observations. Various sampling methods were applied and compared for accurately estimating mean plant densities, for differing weed species and years. The tested methods were based on (a) random selection wherein samples were chosen either entirely randomly, randomly with at least 10 or 20 m between samples, or randomly after stratifying the field; (b) systematic selection where samples were placed along diagonals or along zig‐zagged lines across the field; (c) predicted Setaria viridis (L.) P. Beauv seedling maps which were used to divide the field into low‐ and high‐density areas and to choose the largest sample proportion in the high‐density area. For each method, sampling was performed with 5–40 samples. Systematic methods generally resulted in the lowest estimation error, followed by the random methods and finally by the predicted‐map methods. In case of species over‐ or under‐represented along the diagonals or the zig‐zag sampling line, the systematic methods performed badly, especially with low sample numbers. In those instances, random methods were best, especially those imposing a minimal distance between samples. Even for S. viridis, the methods based on predicted S. viridis maps were not satisfactory, except with low sample numbers. The relationships between sampling error and species characteristics (mean density, variability, spatial structures) were also studied.     

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.