Agricultural equipment can disperse weed seeds over large distances. Efforts to minimize or prevent equipment-mediated dispersal should be a key component in any integrated weed management plan. Several experiments were initiated in commercial wild blueberry fields to examine the potential impact of harvesting equipment on weed seed dispersal within and between blueberry fields. Seed loads were examined on harvesting equipment between fields and results suggest that harvesting equipment is a major vector of seed dispersal. Seed loads were 397,000 in 2006 and 194,000 in 2007. Of all seeds located on the harvester, 66 to 79% were located on the belts or affiliated components. In 2006, a second experiment was established to examine within-field seed dispersal. A sampling grid was established over multiple distinct poverty oatgrass patches with seed heads at 44% of all sampling points. Following harvest, seeds were located at 67% of all sampling points. In 2006 and 2007, short-distance secondary dispersal of poverty oatgrass by harvesting equipment was measured. The relationship between distance from patch perimeter and seeds per unit area on the side approached by harvesting equipment and the far side of the patch was adequately modeled with an exponential decay model. Secondary dispersal within blueberry fields by harvesting equipment is inevitable. Dispersal may be reduced by avoiding dense weed patches, or altering harvest timing. Periodic cleaning of harvesting equipment between fields will help prevent the spread of weed seed.

POST weed harrowing and other cultivation methods to control weeds in early crop growth stages may result in crop damage due to low selectivity between crop and weeds. Crop tolerance to cultivation plays an important role but it has not been clearly defined and analyzed. We introduce a procedure for analyzing crop tolerance on the basis of digital image analysis. Crop tolerance is defined as the ability of the crop to avoid yield loss from cultivation in the absence of weeds, and it has two components: resistance and recovery. Resistance is the ability of the crop to resist soil covering and recovery is the ability to recover from it. Soil covering is the percentage of the crop that has been buried because of cultivation. We analyzed data from six field experiments, four experiments with species of small grains, barley, oat, wheat, and triticale, and two experiments with barley cultivars with different abilities to suppress weeds. The order of species' tolerance to weed harrowing was triticale > wheat > barley > oat and the differences were mainly caused by different abilities to recover from soil covering. At 25% soil covering, grain yield loss in triticale was 0.5%, in wheat 2.5%, in barley 3.7%, and in oat 6.5%. Tolerance, resistance, and recovery, however, were influenced by year, especially for oat and barley. There was no evidence of differences between barley cultivars in terms of tolerance indicating that differences among species are more important than differences among cultivars. Selectivity analysis made it possible to calculate the crop yield loss due to crop damage associated with a certain percentage of weed control. In triticale, 80% weed control was associated with 22% crop soil cover on average, which reduced grain yield 0.4% on average in the absence of weeds. Corresponding values for wheat, barley, and oat were 23, 21, and 20% crop soil cover and 2.3, 3.6, and 5.1% grain yield loss.

Microbial metabolites have been identified as a promising class of natural herbicides due to their effective control against weeds and a relatively low environmental impact. Here we report on the potency and crop safety of a natural compound with herbicidal properties, the metabolite SPRI-70014 from Streptomyces griseolus CGMCC 1370. The compound showed excellent herbicidal activities on various broadleaf and gramineous weeds in both greenhouse and field trials. In germination inhibition experiments, SPRI-70014 inhibited the emergence of both root and shoot at 1 mg L−1. At a dose of 31.3 g ai ha−1, SPRI-70014 provided effective control over most broadleaf weeds in greenhouse trials. Observations on absorption and translocation using a cucumber plant model system indicated that SPRI-70014 could be absorbed by the root but only partly by the stem. Field trials showed that SPRI-70014 provided effective control over most weed species tested at a dose of 1,000 g ai ha−1. Crop safety experiments showed that the compound had no harmful effect on peanut or wheat plants at doses up to 2,000 g ai ha−1. These results indicated that this compound could be developed as a potential POST herbicide for control of broadleaf weeds in peanut and wheat fields.

Benghal dayflower (formerly known as tropical spiderwort) is one of the most troublesome weeds in Georgia cotton. Field studies were conducted from 2003 to 2005 to evaluate the relationship between the duration of Benghal dayflower interference and cotton yield to establish optimum weed-control timing. To determine the critical period of weed control (CPWC), Benghal dayflower interference with cotton was allowed or prohibited in 2-wk intervals between 0 to 12 wk after crop planting. Maximum yield loss from Benghal dayflower in May-planted cotton was 21 to 30% in 2004 and 2005, whereas cotton planting delayed until June resulted in maximum yield losses of 40 to 60%. June-planted cotton had a CPWC of 190 to 800 growing degree days (GDD) in 2004 (52-d interval beginning at 16 d after planting [DAP]) and 190 to 910 GDD in 2005 (59-d interval beginning at 18 DAP). In contrast, May-planted cotton in 2005 had a narrower CPWC interval of 396 to 587 GDD (18 d) that occurred 3 wk later in the growing season (initiated at 39 DAP). May-planted cotton in 2004 did not have a critical range of weed-free conditions. Instead, a single weed removal at 490 GDD (44 DAP) averted a yield loss greater than 5%. It is recommended that fields infested with Benghal dayflower be planted with cotton early in the growing season to minimize weed interference with the crop.

Field studies were conducted to examine both density and duration of glyphosate-resistant (GR) horseweed interference in cotton. Two studies, one examining the effect of horseweed density and a second the duration of horseweed interference, were conducted on a site with a natural population of horseweed that were treated with glyphosate at 0.84 kg ae ha−1 prior to planting and at the 2nd and 4th cotton node growth stages. GR horseweed density effect on cotton height, maturity, and lint yield was determined at horseweed densities of 0, 5, 10, 15, 20, and 25 plants m−2. Duration of horseweed interference was evaluated when 20 horseweed m−2 were allowed to interfere with cotton from emergence to 2nd node, 6th node, 10th node, 12th node, and 1st bloom stage of cotton. The maximum cotton lint yield loss (46%) occurred when horseweed was allowed to compete with cotton from emergence to maturity at the two highest densities (20 and 25 horseweed m−2). When the data were fit to the Cousens model the estimated a (maximum yield loss) and i (yield loss per unit density as density approaches zero) were 53 ± 7.3 and 2.8 ± 0.6 SE, respectively. In both years of the study, horseweed interference from emergence to the 2nd cotton node did not reduce cotton lint yields. In 2006, cotton lint yield loss was 28% compared to 39% in 2005 when horseweed interfered with cotton from emergence until the 6th cotton node. Cotton lint yield loss was 37 and 44% when horseweed competed to the 8th cotton node in 2005 and 2006, respectively. Maximum horseweed seed production was 134,000 to 148,000 seeds m−2.

A fungal pathogen, Helminthosporium gramineum Rabehn f.sp. echinochloae (HGE), has been developed as a mycoherbicidal agent for the control of barnyardgrass in China. Under greenhouse conditions, the effect of the pathogen on disease incidence, mortality, and dry weight reduction of barnyardgrass was tested to determine the potential of this mycoherbicide. Field experiments during 2007 and 2008 showed that the conidia of HGE displayed excellent activity on barnyardgrass and good activity on a few other weed species. The HGE treatment increased the rice yield when compared with the untreated control and had no negative impact on the rice plant. In addition, the progression of HGE infection and the alteration of cellular ultrastructure in infected barnyardgrass were observed by using scanning and transmission electron microscopes. After infection, cell membranes of barnyardgrass leaves were found dramatically changed, and the ultrastructure of cells was severely deformed. This study clearly shows the scope of HGE as a potential mycoherbicide for control of barnyardgrass in agricultural cropping systems and has laid the groundwork for further studies on the mode of infection and the nosogenesis of HGE.

A weed emergence prediction model, WeedCast, was used as a decision aid to schedule potato cultivation with and without herbicides at Wooster, OH, USA; Charlottetown, PE, Canada; and Fargo, ND, USA, from 2001 to 2003. Studies were laid out in a split-plot design with herbicides (±) forming the main plots and cultivation timing as subplots. Cultivation was done at 15, 30, or 60% of predicted weed emergence. Subplots were either left unsprayed or treated with metolachlor + metribuzin at 1.68 + 0.5 kg ai ha−1 and only cultivated at predetermined timing. Cultivation timing was based on predicted emergence of common lambsquarters at Wooster and Charlottetown, whereas eastern black nightshade was the indicator weed at Fargo. Weed control for the different cultivation timings varied among sites and years and was consistently better in plots where herbicides were followed by cultivation. Cultivation alone resulted in poor weed control and significantly reduced potato tuber yield compared with those in plots where weed control also included herbicides. Use of herbicides followed by cultivation and hilling increased tuber yield by 4.6, 4.3, and 8.7 t ha−1, when cultivations were done at 15, 30, and 60% of predicted weed emergence, respectively, and 12.2 t ha−1 for hilled-only plots. The average potato yield increase at Charlottetown was 9.7, 5.9, 6.9, and 7.4 t ha−1 for hilled-only plots and for hilled after cultivations at 15, 30, and 60% of predicted weed emergence with herbicides, respectively. There was no apparent pattern for treatment effects at Fargo, and the potato tuber yields were greatly reduced mainly because of excessive precipitation during potato establishment. Use of WeedCast as a decision-aid tool could be an asset in determining when to do the first and subsequent cultivations. It may work best for growers who use cultivations in potato to remove weeds that were not controlled by herbicides.

Field and laboratory studies were conducted to examine herbicide dissipation when applied to low density polyethylene (LDPE) mulch for dry scenarios vs. irrigation. Analytical chemical analysis was used for quantification. In field studies, halosulfuron, paraquat, carfentrazone, glyphosate, and flumioxazin were surface applied to black 32-μm-thick (1.25 mil) LDPE mulch. LDPE mulch harvest began 1 h after treatment (HAT) then continued every 24 h for five consecutive rain-free days after treatment (DAT) to determine the level of herbicide dissipation from the LDPE mulch surface. In a related study, treated LDPE mulch was harvested 1 HAT, then sprinkler irrigation was applied, followed by a sampling five HAT, then the same irrigation and sampling procedure was repeated every 24 h for five consecutive DAT. The order for half-life, as defined as time for 50% dissipation (DT50), varied by herbicide and method of dissipation for dry and irrigated studies. Data indicated that glyphosate and paraquat dissipation was rapid following irrigation. Glyphosate and paraquat DT50 were both 1 h in the irrigated study, but 84 and 32 h for the dry scenario, respectively. This indicated that glyphosate and paraquat could be removed from LDPE mulch with rainfall or irrigation, primarily due to their high water solubility. Halosulfuron and flumioxazin DT50 were 3 and 6 h in the irrigated study, and 18 and 57 h for the dry study, respectively. Carfentrazone DT50 was similar at 28 and 30 h for the irrigated and dry studies, respectively. This indicated that carfentrazone was adsorbed to the LDPE mulch, and irrigation water did not remove it from the LDPE mulch. Results from 14C-herbicide laboratory studies were similar to those from field studies for halosulfuron, glyphosate, paraquat, and flumioxazin.

Cultivated rice yield losses due to red rice infestation vary by cultivar, red rice density, and duration of interference. The competition effects of red rice could be influenced further by emergence characteristics, red rice biotype, and planting time of cultivated rice. We aimed to characterize the emergence of red rice biotypes at different planting dates and evaluate the effect of red rice biotype, rice cultivar, and planting date on cultivated rice yield loss. Field experiments were conducted at the Southeast Research and Extension Center, Rohwer, AR, and at the Arkansas Rice Research and Extension Center, Stuttgart, AR, in the summer of 2005 and 2006. The experimental design was a split-split plot with three or four replications. Planting time, ClearfieldTM (CL) rice cultivar, and red rice biotype were the main plot, subplot, and sub-subplot factors, respectively. There were three planting times from mid-April to mid-May at 2-wk intervals. CL rice cultivars, CL161 and hybrid CLXL8, and 12 red rice biotypes were planted. The emergence rate and coefficient of uniformity of germination differed among some red rice biotypes within a planting time. Planting date affected the emergence characteristics of red rice biotypes. The mean emergence rate of red rice was 0.043 d−1 in the mid-April planting and 0.058 d−1 in the late April planting. For the mid-April planting, 50% of red rice biotypes emerged in 20 ± 2 d compared with 15 ± 2 d for CL rice cultivars. Yield losses due to red rice biotypes generally increased in later planting dates, up to 49%. Yield losses due to interference from red rice biotypes ranged from 14 to 45% and 6 to 35% in CL161 and CLXL8, respectively. Cultivated rice became less competitive with red rice in later plantings, resulting in higher yield losses.

The need for reducing costs and making grape production more sustainable has prompted the search for alternative weed control practices that optimize production while maintaining profits. For this reason, it is imperative to understand how different weed management practices modify vine–weed interactions. In the present study, we evaluated the effect on weed growth and Zinfandel grapevine growth and production of five weed control practices: (1) flumioxazin, (2) simazine, (3) cultivation, (4) cover crop, and (5) untreated control. The herbicide treatments had the lowest weed biomass, followed by the cultivation, being approximately 10 and 2 times lower than the weed biomass of either the cover crop or untreated control treatments, respectively. However, the differences in grape yield were not as evident. In 2006, a rainy year, the herbicides and cultivation treatments did not differ in grape yield, but the cover crop and untreated control had a reduction of approximately 20% compared with the other treatments. In 2007, a dry year, in comparison to the herbicide treatments, the grape yield reductions of cultivation were around 22%, and those of the cover crop and untreated control were around 48%. Although the cover crop reduced grape yield, it suppressed weed species considered important, such as horseweed, panicle willowherb, scarlet pimpernel, and sowthistle. Also, it was concluded that vines can tolerate a certain amount of weed competition, and that properly timed postemergence control actions (e.g., cultivation or POST herbicides) could provide the necessary level of control to obtain the desired yields. However, under limited soil moisture conditions, the use of PRE herbicides could prove important to maintain vine yield and vigor.

New and improved glyphosate-resistant (GR) crops continue to be rapidly developed. These crops confer greater crop safety to multiple glyphosate applications, higher rates, and wider application timings. Many of these crops will also have glyphosate resistance stacked with traits that confer resistance to herbicides with other modes of actions to expand the utility of existing herbicides and to increase the number of mixture options that can delay the evolution of GR weeds. Some breeding stacks of herbicide resistance traits are currently available, but the trend in the future will be to combine resistance genes in molecular stacks. The first example of such a molecular stack has a new metabolically based mechanism to inactivate glyphosate combined with an active site-based resistance for herbicides that inhibit acetolactate synthase (ALS). This stack confers resistance to glyphosate and all five classes of ALS-inhibiting herbicides. Other molecular stacks will include glyphosate resistance with resistance to auxin herbicides and herbicides that inhibit acetyl coenzyme A carboxylase (ACCase) and 4-hydroxyphenyl pyruvate dioxygenase (HPPD). Scientists are also studying a number of other herbicide resistance transgenes. Some of these new transgenes will be used to make new multiple herbicide-resistant crops that offer growers more herbicide options to meet their changing weed management needs and to help sustain the efficacy of glyphosate.

The continuous use of glyphosate has resulted in the selection of glyphosate-resistant (GR) biotypes in 13 weed species. Decreased translocation of glyphosate to the meristematic tissue is the primary mechanism of resistance in horseweed, hairy fleabane, rigid ryegrass, and Italian ryegrass, and the resistance is inherited as a single, semidominant nuclear trait. The question is: What role does decreased translocation play in glyphosate resistance, and what is the actual mechanism(s)? The enzyme 5-enol-pyruvylshikimate-3-phosphate synthase (EPSPS), the target site of glyphosate, preferentially accumulates in the active meristems of plants. Inhibition of EPSPS results in the accumulation of shikimate. Leaf disc assays across a number of species show that the maximum accumulation of shikimate occurs in young, rapidly expanding tissue. Gene expression studies have also shown that the gene encoding EPSPS is maximally expressed in meristems. Thus, glyphosate needs to translocate to the growing points of plants to be effective. In some GR weed biotypes, glyphosate moves in the treated leaf via the transpiration stream; but instead of being loaded into the phloem, it is trapped in the distal portion of the leaf. These results suggest that there is some type of inhibition of glyphosate-loading into the phloem in GR plants. However, this mechanism may involve uptake of glyphosate at the cellular level. Shikimate accumulation in isolated leaf discs occurs at high glyphosate concentrations in both susceptible and GR biotypes of horseweed and Italian ryegrass; but at low concentrations, shikimate accumulation occurs only in susceptible biotypes. Decreased cellular uptake of glyphosate might occur by one of four mechanisms: (1) the active uptake system no longer recognizes glyphosate, (2) an active efflux system pumps glyphosate out of the cell into the apoplast, (3) an active efflux system pumps glyphosate out of the chloroplast into the cytoplasm, or (4) glyphosate is pumped into the vacuole and sequestered in the cell.

Development of genetically modified (GM) wheat has raised concerns about the movement and persistence of transgenes in agroecosystems and the ability of growers to segregate GM from conventional wheat. Wheat as a crop has been studied extensively but the population biology of volunteer wheat is not well characterized. Artificial seed bank studies were conducted in western Canada to provide baseline data on volunteer wheat seed persistence. Seed from two cultivars of Canadian western red spring wheat, ‘AC Splendor’ and ‘AC Superb’, were buried in mesh bags at three depths (0, 2, and 15 cm) in two different environments in the fall of 2003 and 2004. In addition, in 2004, ‘AC Superb’ seed were separated into small and large seed lots and buried with a medium seed lot to examine the influence of seed size on seed bank persistence. Seeds were withdrawn at intervals to assess seed germination and viability and regression analysis conducted on the viable seed at each sample period, after burial. Seed viability was variable within years and sites, and declined exponentially over time. In the spring, approximately 6 mo after initiation, viable seed ranged from 1 to 43%. With the exception of a single site and year, seeds on the soil surface persisted significantly longer than buried seeds and increasing burial depth accelerated loss of viability. The maximum viability of wheat seeds at 0, 2, and 15 cm depth in the spring following planting was 43, 7, and 2%, respectively. The extinction of viability for 99% (EX99) of the seed was estimated from regression analysis. The EX99 values of seeds buried at 0, 2, and 15 cm ranged from 493 to 1,114, 319 to 654, and 175 to 352 d after planting (DAP), respectively, with the exception of one site in 2003 where burial depths were not different and all had an EX99 value of 456 DAP. Seed size and cultivar did not significantly affect persistence, with the exception of one site in 2003 where the difference in EX99 values was 20 DAP. The rapid loss of seed viability limits temporal gene flow via volunteers in years following a wheat crop. Results provide data on spring wheat biology to aid in Canadian environmental biosafety assessments of GM wheat and will be incorporated into a mechanistic model to predict wheat gene flow on the Canadian prairies.