The need for sustainable agricultural-production systems has generated demand for effective, nonsynthetic, alternative weed-control strategies. For some vegetable crops there are few herbicide options available, and there is little prospect of new herbicides being registered for vegetable crops. Brassicaceae seed meal, a residue product of the seed oil extraction process, can provide a resource for supplemental nutrients, disease control, and weed suppression. The objective of this study was to evaluate the effect of different Brassicaceae seed meals and application rates on the emergence of wild oat, Italian ryegrass, prickly lettuce, and redroot pigweed, which are some of the major weeds in vegetable production systems. White mustard seed, Indian mustard seed, and rapeseed meals were used with (intact) or without a functional myrosinase enzyme (denatured). Intact white mustard seed meals applied at a rate of 2000 kg ha−1 significantly reduced weed seedling emergence and weed dry biomass compared with intact rapeseed-meal–amended treatments. Indian mustard showed significantly better herbicidal efficacy on the grassy weeds than did white mustard, which was most effective in controlling broadleaf weeds. In all instances, a 1000 kg ha−1 application rate of either Indian mustard or white mustard exhibited greater herbicidal effect than did the 2000 kg ha−1 application rate of rapeseed meal. These results demonstrate that all glucosinolates are not equal in herbicidal effects. The herbicidal effects of the mustard seed meal could offer vegetable growers a new option for weed control, particularly in organic production systems. In practice, it would seem feasible to treat soils with a blend of Indian mustard and white mustard seed meals so that both grass and broadleaf weeds could be effectively controlled.

The sharp decline in the area of lupin grown in Australia is partly attributed to the failure to control herbicide-resistant weeds in narrow-leaf lupin crops grown with the conventional 25-cm-wide row spacing. Growing lupin with wider row spacing allows for interrow weed control by nonselective herbicides using a sprayshield or physical methods. During 2003 to 2006, two experiments conducted at five sites evaluated the efficacy of interrow weed control techniques in narrow-leaf lupin crops grown in 55- to 65-cm-wide rows within the Western Australia wheatbelt. Interrow herbicides were applied POST using sprayshields, intrarow herbicides were banded on lupin rows at seeding, and interrow weeds were mowed using a garden mower. The main weed species at each site was rigid ryegrass, blue lupin, or wild radish. Paraquat plus diquat applied on the interrow of the lupin crop with sprayshields controlled up to 100% of weeds between rows, leading to increases in lupin grain yield in most of the sites. Glyphosate alone, a mixture of glyphosate plus metribuzin, and glyphosate followed by paraquat plus diquat also controlled interrow weeds, but did not increase lupin grain yield at any site. Thus, paraquat plus diquat is a better choice for interrow weed control in wide row lupin than glyphosate. Mowing did not improve weed control, but mowing followed by paraquat plus diquat increased lupin grain yield at one site. Regression models predicted that there was a strong relationship between weed biomass and lupin grain yield.

We studied the emergence phenology of large and smooth crabgrass in lawn and bare soil environments and identified ornamental plants as phenological indicators that predict the progress of emergence. From 2002 to 2004, we monitored emergence of large and smooth crabgrass in field plots to estimate the dates of first emergence, and 25, 50 and 80% emergence. Each year, we monitored 74 taxa of ornamental plants to determine dates of first and full bloom. We compiled dates of weed emergence and ornamental blooming to create a biological calendar of phenological events for each year, ordered by average cumulative degree days (DD) (January 1 start date, 10 C base temperature). Ornamental plant flowering events that occurred in a regular sequence before crabgrass emergence events were identified as the phenological indicators. We also evaluated DD and rule-based models for predicting crabgrass emergence and optimum time of PRE herbicide application. In general, smooth crabgrass reached each emergence stage earlier than large crabgrass. Differences in emergence between environments were not consistent over years for the two species. There was no consistent pattern in parameters for DD models predicting emergence events for either crabgrass species or environment. For published DD models, the deviation between observed and predicted emergence events ranged from 0 to > 60 d. Published rule-based predictions, though accurate in some cases, were sometimes difficult to implement. The order of ornamental plant blooming and crabgrass emergence events was generally consistent over years (R2 = 0.977). The biological calendar provided useful crabgrass emergence predictions using real-time field-based indicators of sequential biological events that can help managers plan and optimize management strategies.

Common cocklebur is a new weed in irrigated maize grown for forage in the hot, dry region of northwest Pakistan. We conducted experiments in the Khyber Pakhtunkhwa Province, Peshawar, Pakistan, during 2006 and 2007 to evaluate the interaction of common cocklebur density and maize density on biomass, leaf area index (LAI), and plant height of forage maize. Seven common cocklebur densities (0, 2, 4, 6, 8, 10, and 12 plants m−2) in maize planted at four densities (5, 7.5, 10, and 12.5 plants m−2) were evaluated. An ANOVA for both years revealed significant main effects and interactions for all variables. Regression of measured variables against common cocklebur density showed that maize biomass declined linearly as common cocklebur density increased from 0 to 12 plants m−2, with an increasing rate of decline for high maize densities and low maize densities. Combined data for all maize densities revealed that the relationship between maize biomass and common cocklebur biomass fit a linear function, with 1.28 to 1.35 kg ha−1 loss in maize biomass for each kilogram per hectare increase in common cocklebur biomass from about 1,500 to 3,200 kg ha−1. Above 8 to 10 common cocklebur plants m−2, weed biomass declined, presumably due to intraspecific competition. An increase in common cocklebur density decreased maize LAI about 0.15 to 0.3 units for each additional common cocklebur plant per square meter in 2006, and 0.11 to 0.24 units in 2007. Common cocklebur LAI increased in a linear fashion as density of the weed increased. Results suggest that the effect of common cocklebur interference on maize biomass was associated with a change in allocation of resources, resulting in increased crop height growth at the expense of a reduction in LAI and presumably potential light interception by the crop as common cocklebur density increased.

With increasing incidence of glyphosate-resistant weeds worldwide, greater farmer awareness of the importance of glyphosate stewardship and proactive glyphosate-resistance management is needed. A Web-based decision-support tool (http://www.weedtool.com) comprising 10 questions has been developed primarily for farmers in western Canada to assess the relative risk of selection for glyphosate-resistant weeds on a field-by-field basis. We describe the rationale for the questions and how a response to a particular question influences the risk rating. Practices with the greatest risk weighting in western Canadian cropping systems are lack of crop-rotation diversity (growing mainly oilseeds) and a high frequency of glyphosate-resistant crops in the rotation. Three case scenarios are outlined—low, moderate, and high risk of glyphosate-resistance evolution. Based on the overall risk rating, three best-management practices are recommended to reduce the risk of glyphosate resistance in weeds.

The replication of experiments over multiple environments such as locations and years is a common practice in field research. A major reason for the practice is to estimate the effects of treatments over a variety of environments. Environments are frequently classed as random effects in the model for statistical analysis, while treatments are almost always classed as fixed effects. Where environments are random and treatments are fixed, it is not always necessary to include all possible interactions between treatments and environments as random effects in the model. The rationale for decisions about the inclusion or exclusion of fixed by random effects in a mixed model is presented. Where the effects of treatments over broad populations of environments are to be estimated, it is often most appropriate to include only those fixed by random effects that reference experimental units.

A survey of 109 fields was conducted across western Canada in spring 2007 to determine the extent of ALS-inhibitor and dicamba (synthetic auxin) resistance in kochia. Weed seedlings were collected from fields in three provinces of western Canada and transplanted into the greenhouse. Seeds were harvested from selfed plants, and the F1 progeny were screened for resistance to the ALS-inhibitor mixture thifensulfuron–tribenuron or dicamba. All kochia populations were susceptible to dicamba. ALS inhibitor–resistant kochia was found in 85% of the fields surveyed in western Canada: 80 of 95 fields in Alberta, six of seven fields in Saskatchewan, and all seven fields in Manitoba. For the 93 ALS inhibitor–resistant populations, the mean frequency (±SE) of parental plants classified as resistant was 61 ± 3%. Most of the resistant populations (87%) were heterogeneous and contained both resistant and susceptible individuals. ALS sequence data (Pro197 and Asp376 mutations) and genotyping data (Trp574 mutation) obtained for 87 kochia parental (i.e., field-collected) plants confirmed the presence of all three target-site mutations as well as two mutational combinations (Pro197 + Trp574, Asp376 + Trp574) in resistant individuals.