Herbicidal activities of clove oil and its primary constituent eugenol on broccoli, common lambsquarters, and redroot pigweed and the role of crystalline leaf epicuticular wax (LEW) in susceptibility and retention of these essential oils were studied. Clove oil (2.5%) and eugenol (1.5%) were applied to leaves of greenhouse-grown broccoli, common lambsquarters, and redroot pigweed seedlings and effects on seedling growth and leaf cell membrane integrity were studied. Compared with eugenol, clove oil caused greater inhibition of seedling growth in all species. Both eugenol and clove oil caused greater loss of membrane integrity and inhibition of seedling growth in redroot pigweed, which has no crystalline LEW, compared with common lambsquarters, which has a thick layer of crystalline LEW. In broccoli seedlings with LEW, clove oil caused greater inhibition of growth than eugenol. Both clove oil and eugenol caused greater electrolyte leakage from broccoli leaves without LEW than in the leaves with LEW. Removal of LEW increased electrolyte leakage, an indicator of cell membrane damage, by 97% in eugenol-treated and 26% in clove oil–treated broccoli leaves. Susceptibility of broccoli seedlings and possibly some weed species may, therefore, be affected by factors (e.g., genetic, environmental) that influence the amount of LEW. Although the presence of LEW greatly reduced the retention of the essential oil solutions, there was no significant difference between the retention of clove oil and eugenol solutions, indicating that differences in their phytotoxicity to broccoli leaves was not due to differential foliar retention.

The next generation of weed seed germination models will need to account for variable soil microclimate conditions. To predict this microclimate environment we have developed a suite of individual tools (models) that can be used in conjunction with the next generation of weed seed germination models. The three tools that will be outlined here are GlobalTempSIM, GlobalRainSIM, and the soil temperature and moisture model (STM2). Each model was compared with several sets of observed data from worldwide locations. Overall, the climate predictors compared favorably. GlobalTempSIM had a bias between −2.7 and +0.9 C, mean absolute errors between 1.9 and 5.0 C, and an overall Willmott d-index of 0.79 to 0.95 (where d = 1 represents total agreement between observed and modeled data) for 12 global validation sites in 2007. GlobalRainSIM had a bias for cumulative precipitation ranging from −210 to +305 mm, a mean absolute error between 29 and 311 mm, and a corresponding d-index of 0.78 to 0.99 for the sites and years compared. The high d-indices indicate that the models adequately captured the annual patterns for the validation sites. STM2 also performed well in comparisons with actual soil temperatures with a range of −2 to +4.6 C biases and mean absolute errors between 0.7 and 6.8 C, with the d-index ranging from 0.83 to 0.99 for the soil temperature comparisons. The soil moisture prediction annual bias was between −0.09 and +0.12 cm3 cm−3, mean absolute errors ranging from 0.02 to 0.16 cm3 cm−3, and possessed a d-index between 0.32 and 0.91 for the validation sites. These models were developed in JAVA, are simple to use, operate on multiple platforms (e.g., Mac, personal computer, Sun), and are freely available for download from the U.S. Department of Agriculture Agricultural Research Service website (http://www.ars.usda.gov/Services/docs.htm?docid=11787).

A trait-based community assembly approach to weed management may enhance our understanding of how weed communities respond to specific management practices and increase the utility of weed management based on ecological principles. Therefore, identifying management practices that operate as assembly filters and the species traits upon which they act is an important first step in developing a more predictive weed science. Here, I report results from a 3-yr investigation of the effects of timing of annual tillage (spring vs. fall) on the annual assembly of arable weed communities. The timing of tillage had consistent and dramatic effects on the composition of weed communities; spring tillage led to weed communities dominated by early emerging spring annual forbs and C4 grasses, and fall tillage led to communities dominated by later-emerging forbs and C3 grasses. Traits determining a species' susceptibility to tillage time likely include germination syndrome and life cycle, both of which influence how species respond to changes in soil resource levels and light availability driven by seasonal disturbance regime. Manipulating the timing of tillage and other major soil disturbances may therefore be an important tool for managers interested in influencing community composition or targeting species with similar germination and life-history traits.

Although foliar herbicide absorption has been studied intensively, there is currently no standardized method for data analysis when evaluating herbicide absorption over time. Most peer-reviewed journals require the treatment structure of data be incorporated in the analysis; however, many herbicide absorption studies published in the past 5 yr do not account for the time structure of the experiment. Herbicide absorption studies have been presented in a variety of ways, making it difficult to compare results among studies. The objective of this article is to propose possible nonlinear models to analyze herbicide absorption data and to provide a stepwise framework so that researchers may standardize the analysis method in this important research area. Asymptotic regression and rectangular hyperbolic models with similar parameterizations are proposed, so that the maximum herbicide absorption and absorption rate may be adequately modeled and statistically compared among treatments. Adoption of these models for herbicide absorption analysis over time will provide a standardized method making comparison of results within and among studies more practical.

Experiments of two types were conducted. (1) Weeds were allowed to grow for different periods after planting sugar beets; they were then removed and the beets hand-weeded until harvest. (2) Sugar beets were hand-weeded for different periods after planting; then no further weeding was done. Weed competition reduced beet yields up to 94%. Weeds that emerged soon after beet planting reduced yields the most, but they exerted little yield-reducing competition until later than 12 weeks after planting the beets (9 weeks after beet emergence). Full-season weed control resulted when beets were hand-weeded for 10 to 12 weeks after planting. Weeds that emerged later were controlled by crop competition.

A procedure is described for the rapid analysis of leaf samples to determine triazine resistance. The technique uses a commercially available fluorometer and is based upon the fact that photosynthesis-inhibiting herbicides increase chlorophyll fluorescence (because of dissipation of absorbed radiant energy in the absence of useful photochemistry). Resistant and susceptible biotypes of six weed species were assayed. Fluorescence of susceptible leaf sections increased dramatically over a 1- to 3-h exposure to atrazine [2-chloro-4-(ethylamino)-6-(isopropylamino)-s-triazine], but resistant leaf sections showed no fluorescence increase. Substantial fluorescence increases of both resistant and susceptible leaf sections were induced by diuron [3-(3,4-dichlorophenyl)-1,1-dimethylurea]. In the absence of herbicides, fluorescence was higher in resistant than in susceptible leaf sections, suggesting that the resistant biotypes are less efficient photosynthetically. Fluorescence analysis was used to characterize atrazine inhibition of photosynthesis in leaf sections of three crop species. Differences in atrazine-induced fluorescence between crop lines were relatively small and were not well correlated with atrazine tolerance. The fluorometer is a convenient device for monitoring photosynthesis inhibition, however, and could be useful in detecting plants having resistance to photosynthesis-inhibiting herbicides.

Catchweed bedstraw and wild mustard each produce two populations per year: a winter population (WP) in June, and a summer population (SP) in September. Experiments were conducted to determine whether the WP and SP differ in seed mass and seasonal germination. Seeds of both weeds were buried at 0, 5, 10, and 20 cm in cultivated fields, and retrieved at monthly intervals for 24 mo for germination tests in the laboratory. Additionally, seedling emergence from seeds buried at 0, 5, and 10 cm in the field was evaluated for 1 yr. Seeds from the WP were heavier than those from the SP for both species. Germination of exhumed seeds was affected by burial depth and by seed population. It was highest for seeds that remained on the soil surface and declined with increasing depth of burial. The WP of catchweed bedstraw produced two germination peaks per year, whereas the SP and all populations of wild mustard had only one peak. The WP of both weeds germinated earlier than the SP. Seedling emergence for both species in the field was greater for the WP than for the SP. Increasing soil depth reduced seedling emergence of both the WP and SP of wild mustard and affected only the WP of catchweed bedstraw. We conclude that the WP and SP of catchweed bedstraw and wild mustard seeds used in this study differed in seed mass, seasonal germination, and seedling emergence. The ability of a WP to produce large seeds that germinate early and have two germination peaks per year could make these populations a serious problem in cropping systems.

The objective of this research was to evaluate the accuracy of remote sensing for detecting weed infestation levels during early-season Glycine max production. Weed population estimates were collected from two G. max fields approximately 8 wk after planting during summer 1998. Seedling weed populations were sampled using a regular grid coordinate system on a 10- by 10-m grid. Two days later, multispectral digital images of the fields were recorded. Generally, infestations of Senna obtusifolia, Ipomoea lacunosa, and Solanum carolinense could be detected with remote sensing with at least 75% accuracy. Threshold populations of 10 or more S. obtusifolia or I. lacunosa plants m−2 were generally classified with at least 85% accuracy. Discriminant analysis functions formed for detecting weed populations in one field were at least 73% accurate in identifying S. obtusifolia and I. lacunosa infestations in independently collected data from another field. Due to highly variable soil conditions and their effects on the reflectance properties of the surrounding soil and vegetation, accurate classification of weed-free areas was generally much lower. Current remote sensing technology has potential for in-season weed detection; however, further advancements of the technology are needed to insure its use in future prescription weed management systems.

Implementation of an integrated weed management system requires prediction of the effect of weed competition on crop yield. Predicting outcomes of weed competition is complicated by genetic and environmental variation across years, locations, and management. Mechanistic models have the potential to account for this variability. Weed phenological development is an essential component of such models. Growth cabinet studies were conducted to characterize common ragweed's phenological response to temperature, photoperiod, and irradiance. Ragweed development occurred over a temperature range of 8.0 to 31.7 C, and this response to temperature was best characterized using a nonlinear function. A maximum leaf appearance rate of 1.02 leaves d−1 occurred at 31.7 C. Ragweed has a short juvenile phase, during which it was not sensitive to photoperiod. Following this juvenile phase, sensitivity to photoperiod was constant and continued until pistillate flowers were observed. Photoperiods of 14 h or less were optimal and resulted in maximum rates of development. Irradiance level affected ragweed phenological development only when combined with the additional stress of low temperatures. Data generated in this study can be used for the development of mechanistic weed competition models.

Field research was conducted to determine the potential of hyperspectral and multispectral imagery for late-season discrimination and mapping of grass weed infestations in wheat. Differences in reflectance between weed-free wheat and wild oat, canarygrass, and ryegrass were statistically significant in most 25-nm-wide wavebands in the 400- and 900-nm spectrum, mainly due to their differential maturation. Visible (blue, B; green, G; red, R) and near infrared (NIR) wavebands and five vegetation indices: Normalized Difference Vegetation Index (NDVI), Ratio Vegetation Index (RVI), R/B, NIR-R and (R − G)/(R + G), showed potential for discriminating grass weeds and wheat. The efficiency of these wavebands and indices were studied by using color and color-infrared aerial images taken over three naturally infested fields. In StaCruz, areas infested with wild oat and canarygrass patches were discriminated using the indices R, NIR, and NDVI with overall accuracies (OA) of 0.85 to 0.90. In Florida–West, areas infested with wild oat, canarygrass, and ryegrass were discriminated with OA from 0.85 to 0.89. In Florida–East, for the discrimination of the areas infested with wild oat patches, visible wavebands and several vegetation indices provided OA of 0.87 to 0.96. Estimated grass weed area ranged from 56 to 71%, 43 to 47%, and 69 to 80% of the field in the three locations, respectively, with per-class accuracies from 0.87 to 0.94. NDVI was the most efficient vegetation index, with a highly accurate performance in all locations. Our results suggest that mapping grass weed patches in wheat is feasible with high-resolution satellite imagery or aerial photography acquired 2 to 3 wk before crop senescence.

Growing enough cover crop biomass to adequately suppress weeds is one of the primary challenges in reduced-tillage systems that rely on mulch-based weed suppression. We investigated two approaches to increasing cereal rye biomass for improved weed suppression: (1) increasing soil fertility and (2) increasing cereal rye seeding rate. We conducted a factorial experiment with three poultry litter application rates (0, 80, and 160 kg N ha−1) and three rye seeding rates (90, 150, and 210 kg seed ha−1) in Pennsylvania and Maryland in 2008 and 2009. We quantified rye biomass immediately after mechanically terminating it with a roller and weed biomass at 10 wk after termination (WAT). Rye biomass increased with poultry litter applications (675, 768, and 787 g m−2 in the 0, 80, and 160 kg N ha−1 treatments, respectively), but this increased rye biomass did not decrease weed biomass. In contrast, increasing rye seeding rate did not increase rye biomass, but it did reduce weed biomass (328, 279, and 225 g m−2 in the 90, 150, and 210 kg seed ha−1 treatments, respectively). In 2009, we also sampled ground cover before rolling and weed biomass and density at 4 WAT. Despite no treatment effects, we found a correlation between bare soil before rolling (%) and weed biomass at 4 WAT. Our results suggest that increased rye seeding rate can effectively reduce weed biomass and that ground cover in early spring can influence weed biomass later in the growing season.

Macronutrient inputs to annual cropping systems can benefit weeds as well as crops, sometimes decreasing or eliminating the benefits of fertilization. This interaction between fertility management and integrated weed management is becoming increasingly important as these fields increase their focus on efficiency and prevention, respectively. The risk of increased weed competition reflects the fact that weed biomass and height may be highly responsive to nitrogen, phosphorus, and/or potassium. This generalization is supported by monoculture studies of species such as redroot pigweed (Amaranthus retroflexus L.), common lambsquarters (Chenopodium album L.), and barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.] and by ecological theory. However, field studies indicate variation in the effects of macronutrients on weed–crop competition and crop yield, even within species groups. To address challenges in interpreting, comparing, and extrapolating from these diverse reports, we propose a conceptual framework that summarizes the mechanisms underlying observed variation within and between studies. This framework highlights functional traits and trends that help predict yield outcomes in binary weed–crop interactions. Important factors include timing of emergence, maximum heights of the weed and crop, and relative responsiveness to the added nutrient. We also survey recent work on the effects of nutrient source (e.g., the composition of organic amendments) on weed–crop competition. Because different sources vary in their nutrient release dynamics and supplied nutrient ratios, they may have dramatically different effects on weed–crop competition and crop yield. Finally, we offer a guide to best practices for studies of fertility effects on weed–crop competition. Although this review highlights several topics requiring further research, including fertility effects on multispecies interactions and interactions with other environmental factors, emerging methods offer considerable promise. Ultimately, an improved understanding of nutrient effects on weed–crop competition will contribute to the efficient and effective management of diverse cropping systems.

Field and greenhouse research was conducted during 1980 and 1981 to evaluate the effects of carrier volume, surfactant concentration, and treatment date on glyphosate [N - (phosphonomethyl)glycine] toxicity to annual-grass weeds and volunteer small grains. Glyphosate phytotoxicity increased as carrier volume was decreased from 190 to 24 L/ha. The presence of a surfactant in the spray solution did not influence grass control when glyphosate was applied in a carrier volume of 24 L/ha. When glyphosate was applied in 48 or 95 L/ha, the presence of surfactant resulted in better grass control than glyphosate without surfactant. When applied in 190 L/ha, glyphosate with 0.5% (v/v) surfactant gave better grass control than glyphosate alone or commercially formulated glyphosate. When glyphosate was applied to plants under water stress, little control was achieved regardless of plant growth stage. Glyphosate application to grass after head initiation also resulted in reduced control. Maximum weed control with glyphosate was attained when applications were made to seedlings growing actively because of adequate soil moisture and favorable temperatures.

Late-season giant ragweed emergence in Ohio crop fields complicates decisions concerning the optimum time to implement control measures. Our objectives were to develop a hydrothermal time emergence model for a late-emerging biotype and validate the model in a variety of locations and burial environments. To develop the model, giant ragweed seedlings were counted and removed weekly each growing season from 2000 to 2003 in a fallow field located in west central Ohio. Weather data, soil characteristics and geographic location were used to predict soil thermal and moisture conditions with the Soil Temperature and Moisture Model (STM2). Hydrothermal time (θHT) initiated March 1 and base values were extrapolated from the literature (Tb = 2 C, ψb = −10 MPa). Cumulative percent emergence initially increased rapidly and reached 60% of maximum by late April (approximately 400 θHT), leveled off for a period in May, and increased again at a lower rate before concluding in late July (approximately 2,300 θHT). The period in May when few seedlings emerged was not subject to soil temperatures or water potentials less than the θHT base values. The biphasic pattern of emergence was modeled with two successive Weibull models that were validated in 2005 in a tilled and a no-tillage environment and in 2006 at a separate location in a no-tillage environment. Root-mean-square values for comparing actual and model predicted cumulative emergence values ranged from 8.0 to 9.5%, indicating a high degree of accuracy. This experiment demonstrated an approach to emergence modeling that can be used to forecast emergence on a local basis according to weed biotype and easily obtainable soil and weather data.

The influence of artificial shading (0, 30, 47, 70, 80, and 94% shade) on growth of yellow nutsedge (Cyperus esculentus L.) and the time required for developing canopies of several crops to intercept a given amount of light were investigated in field studies to estimate the potential of crops to compete with yellow nutsedge for light. Average number of shoots and tubers and total dry matter production of yellow nutsedge increased in direct proportion to increased amounts of light (correlation coefficient (r ≥.98). Compared to no shade, flower production was substantially reduced by 30 and 47% shade and was essentially absent under more dense treatments. Photosynthetically active radiation (PAR) measured at weekly intervals indicated that light interception occurred first within the drill row of crops, then on shoulders of planting beds, and finally in furrows. The most rapidly developing canopies studied [corn (Zea mays L.), potatoes (Solanum tuberosum L.), and safflower (Carthamus tinctorius L.)] intercepted 90% or greater PAR, including illumination in furrows, within 8 to 9 weeks after planting. About 12, 12, and 16 weeks were required for 80% interception for cowpeas [Vigna unguiculata (L.) Walp.], milo [Sorghum bicolor (L.) Moench.], and cotton (Gossypium hirsutum L.), respectively. Fall-planted barley (Hordeum vulgare L.) intercepted about 90% PAR by March 12. Alfalfa (Medicago sativa L.) intercepted about 90% PAR within 2 to 3 weeks after individual cuttings. Although onions (Allium cepa L.) planted in December intercepted 95% of the PAR in each of the two drill rows per bed about 26 weeks after planting, only 20 to 30% interception occurred in furrows and row middles.

Seedling emergence and growth of downy brome (Bromus tectorum L.), medusahead (Taeniatherum asperum (Sim.) Nevski), and tumble mustard (Sisymbrium altissimum L.) were favored by seed burial, pitting of the soil surface, and soil movement. These conditions maintained temperatures and soil and atmospheric moisture in the range required for establishment.

The rapid spread of glyphosate-resistant sourgrass populations generates concern in the agricultural production sector in Brazil. Nonetheless, there is not much information related to the frequency and dispersion of sourgrass throughout recent years. We investigated the frequency and dispersion of glyphosate-resistant sourgrass populations in Brazilian agricultural regions as part of a larger-scale weed resistance monitoring study. A discriminatory rate of 960 g ae ha−1 of glyphosate was used on plants at the 2- to 3-tiller stage, originating from 2,593 populations of sourgrass sampled in 329 counties in 14 Brazilian states between 2012 and 2015. The dispersion of sourgrass populations originated in western Paraná State, next to the Paraguay border, where the first resistance case was reported. Its dispersion to the central region of Brazil, mainly in soybean-producing areas, is most likely a consequence of agricultural equipment movement and wind-mediated dispersal. Glyphosate-resistant sourgrass populations were found in every geographical region across all Brazilian states tested. These data highlight the importance of an appropriate weed resistance monitoring program to track the evolution and dispersion of resistance to mitigate these issues by focusing efforts regionally and raising awareness among stakeholders in each region.

A weed survey of 115 Nova Scotia lowbush blueberry fields was conducted during the summers of 1984 and 1985 to determine the most common and prevalent weeds associated with blueberry production. A total of 119 weed species were observed within the surveyed blueberry fields. The most common weed species were bunchberry, colonial bentgrass, poverty oatgrass, sheep sorrel, and false lily-of-the-valley. Weeds with low relative abundance in this study, but which may become more widespread, include three-toothed cinquefoil, Kentucky bluegrass, hair fescue, canker-root, and Canadian St. Johnswort.

The intraspecific (competition between same species) and interspecific (competition between different species) competitiveness of tall morningglory [Ipomoea purpurea (L.) Roth] in soybeans [Glycine max (L.) Merr.] was evaluated for 3 yr at Fayetteville, Arkansas. Tall morningglory was planted at densities of one plant per 61, 30, and 15 cm of row, and competition duration ranged from 2 weeks to full-season. Soybeans were more competitive than tall morningglory for the first 6 to 8 weeks after emergence. The competitiveness of tall morningglory was dependent upon a rapid increase in photosynthetic area which occurred 4 to 6 weeks after emergence. Reductions in leaf area index (LAI) or plant dry weight and crop growth rate (CGR) of soybeans were closely correlated to percent soybean yield reduction. Tall morningglory could remain in soybeans for 12, 10, and 6 weeks without significantly reducing soybean yield at one plant per 61, 30, and 15 cm of row, respectively. Tall morningglory was three to four times more competitive during the soybean reproductive stage than during the vegetative stage.

Excavation at biweekly intervals for 20 weeks of nutsedge clones grown from single tubers indicated that no dormant tubers formed until 6 weeks after foliar emergence. Tuber chains or fully mature rhizomes were not observed until the tenth week or long tuber chains until the eighteenth week. Rhizome length and tuber-basal bulb number increased throughout the season. Development of clones varied.