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.     

Potential of weed seedbanks for managing weeds: a review of recent New Zealand research

Weed seedbanks are the primary source of weeds in cultivated soils. Some knowledge of the weed seedbank may therefore be appropriate for integrated weed management programs. It would also be very useful in planning herbicide programs and reducing the total herbicide use. However, a number of problems are inherent in the estimation of the seedbank size for arable weeds that usually have annual life cycles. In a long-term research project we have investigated the dynamics of weed seedbanks in corn fields for the past 8 years. Specific studies have included (i) developing cheap and efficient methods for estimating the weed seedbank; (ii) developing guidelines for efficient soil sampling (including the number and size of samples); (iii) influence of cultivation methods on weed seed distribution; (iv) mapping the spatial variability of the seedbank; (v) estimating the rate of seedbank decline for certain weed species; and (vi) assessing the potential of using the weed seed content in the soil to predict future weed problems. This paper reviews and summarizes the results of our research on the above aspects. The strong correlation between seedlings emerged in the greenhouse and seeds extracted in the laboratory for the most abundant weed species has demonstrated the potential for using the weed seed content of the soil to predict future weed infestations. The next step is to establish correlations with field emergence under commercial conditions using the sampling guidelines developed in our studies. Subsequently, we aim to offer the weed seedbank estimation as a commercial service to farmers for planning the most appropriate weed management options.     

Comparison of sampling methodologies for site-specific management of Avena sterilis

The ability to manage weed infestations in a spatially precise manner requires efficient and accurate methods of mapping weed distributions. A study was conducted to compare four different ground-based methods for collecting georeferenced information on infestations of Avena sterilis in winter wheat and barley. Sampling was performed at harvest by scoring panicle density, either from the ground or from a combine, by counting the number of panicle contacts with a stick moved horizontally over the crop canopy by an observer walking through the field, and by sampling A. sterilis seed rain on the ground. No significant differences were observed among the populations estimated by the four methods. A partial budget analysis of the in-season costs and benefits of spraying patches using these methods showed that visual scoring from the combine was the most appropriate method for the creation of weed management maps to be used for patch spraying in the following season. As a large variety of spatial patterns may be found in fields, the recommended sampling method might be field-specific and optimality should be verified for general use.     

Designing a sampling scheme to reveal correlations between weeds and soil properties at multiple spatial scales

Weeds tend to aggregate in patches within fields, and there is evidence that this is partly owing to variation in soil properties. Because the processes driving soil heterogeneity operate at various scales, the strength of the relations between soil properties and weed density would also be expected to be scale‐dependent. Quantifying these effects of scale on weed patch dynamics is essential to guide the design of discrete sampling protocols for mapping weed distribution. We developed a general method that uses novel within‐field nested sampling and residual maximum‐likelihood (reml ) estimation to explore scale‐dependent relations between weeds and soil properties. We validated the method using a case study of Alopecurus myosuroides in winter wheat. Using reml , we partitioned the variance and covariance into scale‐specific components and estimated the correlations between the weed counts and soil properties at each scale. We used variograms to quantify the spatial structure in the data and to map variables by kriging. Our methodology successfully captured the effect of scale on a number of edaphic drivers of weed patchiness. The overall Pearson correlations between A. myosuroides and soil organic matter and clay content were weak and masked the stronger correlations at >50 m. Knowing how the variance was partitioned across the spatial scales, we optimised the sampling design to focus sampling effort at those scales that contributed most to the total variance. The methods have the potential to guide patch spraying of weeds by identifying areas of the field that are vulnerable to weed establishment.     

Weed seed predation rate in cereals as a function of seed density and patch size,under high predation pressure by rodents

Weed seed predation is an ecosystem service, influencing weed population dynamics. The impact of weed seed predation on weed population dynamics depends on how predators respond to seed patches at the field scale. Seed predation will be most effective if the proportion of seeds predated increases with increasing size and seed density of patches. Density‐dependent rodent seed predation was measured by varying seed density and patch size in four irrigated conventionally managed cereal fields in north eastern Spain. Artificial weed seed patches were created by applying a range of Lolium multiflorum seed densities from 0 to 7500 seeds m^?2 in 225 m² patches (2008) or in patches that varied in size from 1 to 9 m² (2009). Seed predation was estimated using seed cards and seed frames. The granivorous rodents Mus spretus and Apodemus sylvaticus caused high seed predation rates (92%) in three fields, whereas in a fourth field, it was lower (47%). Rodents responded in an inversely density‐dependent manner, but this had little biological meaning as even in patches seeded with the highest density, the input to the soil seedbank was reduced by 88%. For the period of time this experiment lasted, hardly any new seeds would have entered the seedbank.     

当归茎线虫病田间分布型及抽样技术研究

为提高当归茎线虫病(Ditylenchus destructor)田间抽样的准确度,用7种聚集指标判断了当归茎线虫病的田间分布型.结果表明,当归茎线虫病在田间呈聚集分布,其中奈曼分布(核心分布)的适合率为100%,嵌纹分布(负二项分布)的适合率为77.8%.理论抽样数量约820株.4种抽样方法差异均不显著,在保证抽样数量合理的情况下,4种方法均可采用.     

Temperature influences postdispersal predation of weed seeds

Temperature is a key factor for the living organisms on earth. It influences weed management practices, either directly or indirectly. Field experiments were conducted to determine the effect of temperature on the postdispersal seed predation of four important weed species (Cuscuta compestris, Stellaria media, Taraxacum officinale and Veronica persica) in two lucerne fields in Mashhad and Chenaran, north‐eastern Iran. These two cities have the same climate: temperate and cold alpine but the temperature varies between them. Wire mesh cages were used to determine the relative importance of birds in predation and pitfall traps were used to detect the species and the activity density of invertebrate predators. The results showed that the predation preference of different weed species was significantly different between and within fields. Seed predation fluctuated widely throughout the sampling periods, matching the periodic forage harvest and regrowth cycle of lucerne. Despite the level of seed predation fluctuating, it declined toward the last sampling periods. Using wire mesh exclusion cages showed no significant effect of birds on weed seed predation in both fields. Ants, crickets and carabid beetles were the invertebrate seed predators that were caught in the pitfall traps. There were significant correlations between the mean temperature and predator activity densities and also between the predated seeds and the mean air temperature in both locations. The results of this study indicate the significant effect of temperature on postdispersal weed seed predation. Therefore, with respect to climate change and increasing global warming, it would be possible to focus on postdispersal seed predation in weed management in the future.     

Estimating Taylor's power law parameters for weeds and the effect of spatial scale

The spatial variability of weeds within fields was studied for six sets of count data. Heterogeneity for a given mean population density was measured using the variance of the counts between sample units at different locations; relatively large values of sample variance imply aggregation. The dependence of variance on mean was measured using the relationship known as Taylor's power law, ubiquitous in animal ecology but seldom used for plant populations. This was fitted to an extensive set of plant counts and 69 estimates of its parameters b, an index of aggregation, and log₁₀a were computed. Estimates were corrected for bias when the number of samples was small. Overall, b varied between 1.32 and 2.61, and log₁₀a varied between -0.85 and 1.58. agreeing well with previous estimates for both plant and animal populations. Parameter estimates varied with sample size and spatial sample scale, but unpredictably. Parameter values when species counts were combined were compared with individual species analyses. Knowledge of the likely range of these parameters for weed populations provides an important basis for future modelling of the relationship between weed density and crop yield loss.     

Effect of the rust fungus Puccinia chondrillina TU 788 on plant size and plant size variability in Chondrilla juncea

Chondrilla juncea is one of the most serious introduced weed species in Australia. Successful biological control has been achieved by the release of the rust fungus Puccinia chondrillina. Although P. chondrillina is thought to reduce the competitive ability of C. juncea by reducing plant size, the precise mechanism by which the pathogen controls its host is poorly understood. In this experiment, we examined the effect of P. chondrillina TU 788 infection on individual plant size, and size variability, in two genotypes (one resistant, one susceptible) of C. juncea. Exposure to P. chondrillina significantly reduced the average size of susceptible C. juncea plants, a reduction apparent in both roots and shoots. Plant size variability of the susceptible C. juncea genotype was also reduced by P. chondrillina. Plant size, and plant size variability of the resistant genotype were unaffected by exposure to rust, or association with rust‐affected plants. The effect of P. chondrillina on plant size in rust‐susceptible C. juncea plants shows how effective bio‐control of this weed may occur in field populations.     

Soybean yield and yield components as influenced by canopy heights and duration of competition of velvetleaf (Abutilon theophrasti Medik.)*

Soybean yields, pod and branch numbers were inversely related to the height of velvetleaf (Abutilon theophrasti). This effect was attributed to increasing interception of light with increasing height of A. theophrasti. Reduction; in soybean yield and yield components were greater if A. theophrasti was maintained at various heights for only 3 weeks rather than 6 weeks following soybean emergence. This effect was attributed to a longer duration of light competition by the weed. Even when the A. theophrasti canopy was kept 25% below that of soybean for 4 weeks, soybean yields, pod and branch numbers decreased when the weed was allowed to regrow during the remainder of the season, but not if the weed was removed after the initial 4-week clipping period. No reduction in seed yields, pod and branch numbers was noted if A. theophrasti plants 25% shorter than soybeans were removed or allowed to resume growth after the initial 6 or 8 weeks of clipping. Soybean seed size was slightly affected by A. theophrasti canopy height and duration of competition.     

Incorporation of weed spatial variability into the weed control decision-making process

Floral surveys were carried out on a field of 28 m × 100 m on the nodes of a regular 2 m × 2 m grid, using a rectangular sampling area of 25 cm × 30 cm. In total, 765 units were sampled, each one characterized by the spatial co-ordinates and the number of seedlings of different weed species. The spatial representation of the weeds was obtained with kriging. Simulations were carried out for Amaranthus spp., which had the highest frequency and density (221 plants m^?2), and Portulaca oleracea L., a species that combined a more aggregated distribution with a medium–high density (27 plants m^?2). The results obtained clearly indicated that the usefulness of geostatistical procedures depends on the type of question posed by the user. If the goal is to estimate weed density and, consequently, crop yield loss, kriging appears to overburden the decision-making process, without improving the estimates obtained. This procedure becomes useful for obtaining weed infestation maps to be used for intermittent spraying applications. The reliability of these maps increases with the number of samples used for kriging. With the more aggregated species, at least 50 samples are required to obtain an infestation map. The reduction in the area to be treated depends on the threshold level adopted and on the number of samples used for kriging. With a threshold around the break-even point for most post-emergence treatments, this reduction varies from 10% to 40% with maps obtained from 50 and 175 samples respectively. The usefulness of infestation maps obtained with kriging for improving the decision-making process is strictly dependent on the weed patch dynamics: if these patches remain relatively stable over time, kriging can be carried out periodically without overburdening the decision-making process, whereas, if they are not stable, maps need to be drawn up each year, with a significant increase in costs.     

The efficiency of a vacuum device for estimating soil-surface seed abundance on lowland farms

Accurate sampling methods for estimating soil-surface seed abundance in agro-ecosystems are vital for understanding arable plant population dynamics, as well as quantifying seed availability as a food resource for farmland birds, mammals and arthropods. We tested the sampling efficiency of a portable, petroleum spirit powered leaf blower-vacuum in recovering four different seed size classes on the soil-surface of seven lowland farm habitats. Vacuum sampler efficiency was dependent on seed size, habitat type and exposure of seeds to environmental conditions. Larger seeds were more readily recovered and overall seed recovery was consistently higher on habitats with low vegetation cover, such as newly-sown cereal fields. We discuss the limitations of the device, but commend its use with correction factors to estimate soil-surface seed abundance in agricultural habitats. This study highlights the potential biases when estimating soil-surface seed abundance, the importance of correcting such biases and the need for better sampling techniques for weed science.     

Observed changes in soyabean growth and seed yield from Abutilon theophrasti competition as a function of carbon dioxide concentration

Soyabean (Glycine max) was grown at ambient and projected levels of atmospheric carbon dioxide (+250 μmol mol^?1 above ambient) over two field seasons with and without the presence of a weed, Abutilon theophrasti, to quantify the potential effect of rising atmospheric carbon dioxide concentration on weed–crop interactions and potential yield loss in soyabean. Under weed‐free conditions, elevated CO₂ resulted in stimulations in soyabean seed yield and associated components, including pod number. At an approximate density of 6 plants m^?2, A. theophrasti competition resulted in a significant reduction (?40%) in soyabean seed yield. Although differences in seed yield reduction by A. theophrasti were observed as a function of year, the relative decrease in seed yield with A. theophrasti biomass did not differ in response to CO₂. Although careful weed management will be necessary if CO₂‐induced increases in seed yield for soyabean are to be achieved, these data suggest that soyabean seed yield may be more resilient in competition with A. theophrasti as a function of rising atmospheric levels of carbon dioxide.     

Seed production of Raphanus raphanistrum following herbicide application during reproduction and effects on wheat yield

The influence of weather and agronomic factors on the activity of six selective herbicides applied at reproductive stages of development for the reduction in seed production of Raphanus raphanistrum in wheat was evaluated. The herbicides used in this way generally reduced seed production by between 80% and 100%. Triasulfuron and mixtures of triasulfuron + MCPA consistently provided the greatest reduction in seed production. This was greater when herbicides were applied at the bud and early flowering stages of R. raphanistrum and the efficacy of the herbicides increased as maximum temperature on the day of spraying increased over the range 14–24°C. An applied model developed from these results predicts the reduction in seed production of R. raphanistrum, for each herbicide, given the stage of weed development and maximum temperature on the day of its application. Wheat yield was significantly reduced as densities of R. raphanistrum increased, with predicted losses at low densities being approximately half of those reported in the literature. There was no consistent evidence that the late application of herbicides had any negative effect on wheat yield through crop injury, nor was there any indication of yield improvement. It is concluded that certain herbicides applied during the reproductive phase of development have considerable potential to reduce R. raphanistrum seed production in wheat crops. As part of an integrated strategy, such late post‐emergence application of selective herbicides to regulate seed production has a likely role for managing weed seedbanks, but little or no value for counteracting weed competition.     

A stochastic simulation model for evaluating the concept of patch spraying

The long-term economic benefits of `patch' spraying are likely to be related to the initial spatial distribution of the target weeds, the demographic characteristics of the species and the weed control and crop husbandry practices to which they are subjected. This paper describes a stochastic simulation model developed to investigate the interaction between weed seed dispersal and patch spraying. Simulated weed plant and seed populations are generated and compared with data from field observations. Lloyd's Patchiness index is used to quantify the patchiness of the weed density distribution, and the parameter k of the negative binomial distribution is used as a measure of distribution shape. A method of assessing the spatial scale of weed aggregation is proposed, in which spatial weed density information is transformed into the frequency domain, using a discrete two-dimensional Fourier transform. In this paper, we simulate `on/off' patch spraying (full or zero herbicide application rate). A quantitative analysis of the effects of sprayer resolution and weed seed dispersal range on the herbicide reduction and yield benefits from patch spraying is performed for three initial spatial seedbank distributions. The model is parameterized for the grass weed Alopecurus myosuroides Huds. Herbicide is applied in square areas (whose size is defined by the spatial resolution of the sprayer) in which mean weed density is greater than or equal to one plant m^–2. For a system conforming to this specification we show that for the control of A. myosuroides , it is unlikely that patch spraying would be profitable in the long term if the control area is larger than 6 m × 6 m. In some circumstances higher resolution may be required.     

Factors impacting the detection of weed seed contaminants in seed lots

BACKGROUND

The setting and following of phytosanitary standards for weed seeds can lessen the impacts of weeds on agriculture. Standards adopted by seed companies, laboratories and regulators ensure the contamination rates do not exceed some thresholds. Globally sample size standards are set based on the amount needed to obtain a contaminant in a random sample of the seed lot, not detectability. New Zealand requires a 95% confidence that the maximum pest limit of 0.01% of quarantine weed seed contamination is not exceeded in an imported seed lot. We examined 24 samples each containing approximately 150 000 seeds of either perennial ryegrass (12 samples) or white clover seeds (12 samples) that were then spiked with seeds (contaminants) from 12 non-crop species (3–8 seeds of each). We considered factors that may impact detection rates: shape, color, size, and texture relative to the crop, and technician (including a commercial seed laboratory).

RESULTS

A linear mixed model fitted to the data indicated significant observer, crop, and seed color, shape, and size effects on detection. Detectability increased by 20% ± 7.7 (± standard error) when seeds had a distinct shape or color (28% ± 8.1), or were larger (23% ± 8.7) rather than smaller, relative to the crop. Commercial laboratory identifications were usually correct at the level of genus, and species for common weeds, but some misidentifications occurred.

CONCLUSION

Sample sizes for border inspections should be based on detectability of regulated weed seeds in the crop in combination with weed risk for the crop and location. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.     

Ecophysiological study on weed seed banks and weeds in Cambodian paddy fields with contrasting water availability

Weed infestations are a major cause of yield reduction in rice (Oryza sativa) cultivation, particularly with direct‐seeding methods, but the relationship between weed dynamics and water availability in Cambodian paddy fields has not been documented previously. We surveyed the weed abundance and weed seed banks in the soil of paddy fields with inferred differences in their water regime in 22 farm fields in three provinces of Cambodia in the 2005 and 2006 rainy seasons. We studied rain‐fed lowland fields in upslope and downslope topographic positions and fields at different distances from the irrigation water source inside an irrigation rehabilitation area. The weed seed banks were estimated by seedling emergence in small containers and weed abundance and vigor were estimated by a simple scoring system. The estimated weed seed bank in the top 5 cm of soil ranged from 52.1 to 167 × 10³ seeds m^?2 (overall mean of 8.5 × 10³ seeds m^?2) and contained a high proportion (86%) of sedge species, such as Fimbristylis miliacea L. and Cyperus difformis. Several fields had particularly large seed banks, including one near the reservoir. No clear difference was found in the weed seed banks between the irrigated fields that were located close to (upstream) and distant from (downstream) the water source or between the irrigated and rain‐fed lowland fields, but the weed scores were larger in the rain‐fed fields and the downstream fields within the irrigated area. A water shortage during the late growing season in 2005 led to a proliferation of weeds in some fields and an associated increase in weed seedbank size in 2006. However, the weed scores in 2006 were more strongly associated with that year's water conditions than with the weed seedbank size.     

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.     

Assessment of the sample size to estimate the weed seedbank in soil

It was found that, in order to estimate the number of weed seeds in soil with a desirable degree of accuracy and confidence level. the sample size depends to large extent on the spatial distribution pattern of the seeds in the soil. The seeds of most weeds found in cultivated soils are distributed according to one of two statistical distributions: Poisson or Negative Binomial. For an acceptable degree of accuracy in estimating the number of seeds in the soil, the sample size must be large, Taking this into account, in this study a practical solution based on a theoretical approach is proposed for the problem of establishing the sample size for a species distributed according to either statistical pattern. In addition, given the sample size, it was possible to determine the estimation error to be expected. This theoretical approach is compared with that proposed in previous studies. Two abaci, based on simple expressions, are provided to determine the sample size, according to the Poisson or the Negative Binormal distribution of the weed species. For Poisson distribution, the sample size is determined (given the desired maximum relative error estimation and the confidence level) as a function of only one parameter: the expected number of seeds per sampling unit m (estimaied by the sample mean). For Negative Binomial distribution, the sample size is determined as a function of two parameters: m and p (estimated according to the relationship between the sample mean and the sample variance). A sample size n nol very different from those given in previous studies is obtained, but the lower limit found for the n -values is lower than that found in these studies.     

Spatial and temporal patterns of Lolium rigidum–Avena sterilis mixed populations in a cereal field

Through a detailed case study of a two‐species (Lolium rigidum and Avena sterilis) weed community at contrasting scales, this paper examined factors that affect weed distribution across space and time in a commercial wheat field in north‐east Spain. A. sterilis showed relatively stable spatial distribution and spatial structure of its population over time at large scale, with well‐defined patches, although weed density rose quickly. L. rigidum showed poorly defined patches that were not stable across time. Interaction between species could explain to some degree the spatial distribution at large scale: a negative relationship was detected between the spatial structures of both weed populations. At fine scale, both species showed a clear interaction effect from primary dispersal (more important in A. sterilis) and secondary dispersal from combine harvesting (more important in L. rigidum).