No-till systems and crop residue management have changed cropping systems in the Great Plains. Previously, winter wheat-fallow was the prevalent rotation; now producers grow warm-season crops along with winter wheat and fallow. With this diversity of crops, producers have developed an ecological approach to weed management where cultural tactics disrupt weed population growth. Producers using this approach are managing weeds with 50% less cost compared with the winter wheat-fallow rotation. Two key components of the multitactic approach are devising rotations comprised of two cool-season crops followed by two warm-season crops with the use of no-till practices. Fallow, if used, serves in either seasonal category. The cycle-of-four rotation also minimizes severity of plant diseases, thereby increasing crop yield potential. Net returns are increased with crop diversity and no-till compared with winter wheat-fallow and tillage. Reduced cost of weed management is a major factor of improved net returns, as well as increased land productivity.

The objective of this study was to determine if the presence of two acetolactate synthase (ALS)-inhibiting herbicide residues in different Saskatchewan soils would result in additive, synergistic, or antagonistic interactions. This was determined through field trials where herbicides were applied sequentially over the course of 2 yr. The herbicides examined in these experiments were imazamethabenz, flucarbazone, sulfosulfuron, and florasulam, each in combination with imazamox and imazethapyr. The phytotoxicity and persistence of the herbicides in soil was assessed using an oriental mustard root inhibition bioassay. The determination of herbicide interaction was made through the comparison of the experimentally observed values to theoretically expected values derived from a mathematical equation. On the basis of the bioassay analysis, it was found that the herbicide residue combinations resulting from sequentially applied ALS-inhibiting herbicides in the three soils produced additive injury effects rather than synergistic or antagonistic interactions.

Purple deadnettle is an obligate winter annual weed and an alternate host of soybean cyst nematode (SCN). Field experiments were conducted using microplots to determine (1) the effect of purple deadnettle planting date and (2) the effect of purple deadnettle removal time on SCN egg population density in continuous no-tillage soybean. A population change factor (PCF) to assess treatment effects on SCN population densities was calculated by dividing the SCN population density at each sampling time (Pf) by the initial population density before treatments were applied (Pi). In the planting date experiment, purple deadnettle seeded on October 3, 11, and 18 resulted in PCF values ranging from 7.28 to 11.41, which were three- to fivefold higher than the PCF values for the weed-free control or purple deadnettle seeded on September 6, 20, and 27. Self-thinning of purple deadnettle seeded in September may have resulted in higher levels of SCN mortality compared to later seeding dates. In the removal time experiment, purple deadnettle removal at 2 and 4 wk after emergence (WAE) resulted in PCF values of 1.19 and 1.54, respectively, which were similar to the PCF for the weed-free control. In contrast, PCF values for purple deadnettle removal times of 6 WAE or later ranged from 2.46 to 5.44. Field and greenhouse experiments provided evidence that completion of the SCN life cycle on purple deadnettle was prevented if the weed was removed before the accumulation of 380 soil degree days within the 5 to 30 C range. Results from the removal study also suggested that completion of the first SCN generation on purple deadnettle in the fall was the primary factor causing increases in egg population density, since PCF values did not continue to increase significantly beyond the 6 WAE removal time.

Empirical models of crop–weed competition are integral components of bioeconomic models, which depend on predictions of the impact of weeds on crop yields to make cost-effective weed management recommendations. Selection of the best empirical model for a specific crop–weed system is not straightforward, however. We used information–theoretic criteria to identify the model that best describes barley yield based on data from barley–wild oat competition experiments conducted at three locations in Montana over 2 yr. Each experiment consisted of a complete addition series arranged as a randomized complete block design with three replications. Barley was planted at 0, 0.5, 1, and 2 times the locally recommended seeding rate. Wild oat was planted at target infestation densities of 0, 10, 40, 160, and 400 plants m−2. Twenty-five candidate yield models were used to describe the data from each location and year using maximum likelihood estimation. Based on Akaike's Information Criterion (AIC), a second-order small-sample version of AIC (AICc), and the Bayesian Information Criterion (BIC), most data sets supported yield models with crop density (Dc), weed density (Dw), and the relative time of emergence of the two species (T) as variables, indicating that all variables affected barley yield in most locations. AIC, AICc, and BIC selected identical best models for all but one data set. In contrast, the Information Complexity criterion, ICOMP, generally selected simpler best models with fewer parameters. For data pooled over years and locations, AIC, AICc, and BIC strongly supported a single best model with variables Dc, Dw, T, and a functional form specifying both intraspecific and interspecific competition. ICOMP selected a simpler model with Dc and Dw only, and a functional form specifying interspecific, but no intraspecific, competition. The information–theoretic approach offers a rigorous, objective method for choosing crop yield and yield loss equations for bioeconomic models.

Herbicides are very effective tools to control weeds but there has been an overreliance on their use at the expense of other useful methods of weed management. Farmers are interested in alternative methods of weed management but are concerned about the risk of adopting such practices with current small profit margins. Research on the Canadian Prairies has found that cropping systems that utilize zero tillage, diverse crop rotations, competitive cultivars, higher crop seed rates, specific fertilizer management, and cover crops can effectively manage weed populations, especially when used in conjunction with targeted but limited use of herbicides. Farmers are gaining confidence in the merits of such agronomic practices in terms of sustainable weed management and are gradually adopting these integrated cropping systems on their farms. Further research and extension efforts are required to ensure that these integrated weed management systems are biologically and economically robust to facilitate greater adoption at the farm level.

Weed management strategies can influence insect infestations in field crops, yet no attempts have been made previously to manipulate weed populations in canola for integrated weed and insect management. Field studies were conducted during 2003 to 2005 at Lacombe and Beaverlodge, Alberta, Canada to manipulate weed and root maggot, Delia spp. (Diptera: Anthomyiidae), interactions in canola. Densities of monocot weeds were varied by altering herbicide applications, with rates ranging from 0 to 100% of the rate recommended. Weed populations declined, and yields were variable with increased herbicide rates. Root maggot damage decreased with increases in monocot weed dry weight for both canola species at both study sites. Results support the hypothesis that heterogenous environments, arising from mixed populations of monocot weeds with canola, minimize opportunities for females of Delia spp. to complete the behavioral sequence required for oviposition, leading to reduced infestation levels in weedy systems. However, effects of dicot weeds on root maggot infestations varied between sites as a result of site-related differences in weed species complexes. When wild mustard was common, crop damage increased, because this weed can serve as an alternate host for root maggots. The study emphasizes the importance of adopting crop management practices that are compatible for both weed and root maggot control.

Hairy nightshade is a common weed in potato rotations in the western United States. As a close relative of potato, hairy nightshade can host numerous potato nematodes, diseases, and insect pests. Hairy nightshade hosts three common parasitic nematodes of potato, Columbia and northern root-knot nematodes, and stubby root nematode. Tubers of a potato breeding line with roots that are resistant to Columbia root-knot nematode—race 1, were damaged when grown in the presence of hairy nightshade. The weed provided an alternate host for the nematode, which then allowed the nematode to infect susceptible tubers. Stubby root nematodes transmit tobacco rattle virus (TRV), the causal agent for corky ringspot disease (CRS) of potato. CRS disease was maintained in soil when hairy nightshade was present in rotation crops of alfalfa or Scotch spearmint that otherwise eliminated the disease. Hairy nightshade also is a host of potato leaf roll virus (PLRV), which is transmitted by green peach aphids (GPA). GPA preferentially land and readily reproduce on hairy nightshade. Aphid transmission of PLRV from hairy nightshade to potato was four times greater than the virus transmission rate from potato to potato. Integrated management of these potato nematodes, diseases, and insect pests also should include strategies to control hairy nightshade in potato and rotation crops.

An integrated pest management (IPM) program is a systems approach that requires an understanding of the overall agroecosystem. The interaction between different pest categories (weeds, insects, pathogens, nematodes), as well as their management practices, should be examined, understood, and taken into consideration in the design of IPM systems. Several studies have shown that plant pathogens are affected by other pests and their management practices. Herbicide application has often been cited as an example of a management practice that affects plant pathogens and disease development in various cropping systems. The activity of herbicides can extend beyond their target organisms and inhibit spore germination or mycelial growth, alter the level of phytoalexins, or interfere with other physiological processes in plants. This paper summarizes the published reports on direct effects of herbicides on plant disease and provides insights for future research on this aspect. Examples are drawn from some common agricultural herbicides and adjuvants. The discussion on various findings on herbicide and crop diseases re-emphasizes the fact that pest management in agriculture requires a systems approach. Although it is difficult to come to a common consensus on the effect of these chemicals on crop diseases or pathogens, this paper provides an overview of several interactions between herbicides and crop diseases and pathogens in various cropping systems. Knowledge of such interactions can help in the design of IPM systems.

The concept of integrated pest management (IPM) was first introduced in the 1960s. Since then many definitions of IPM have appeared in the literature. According to the 1988 U.S. National IPM Coordinating Committee, the primary goals of IPM programs are to reduce pesticide use and the subsequent environmental impact and to rely more on alternative strategies to control pests. Integrated weed management (IWM) comes under the umbrella of IPM with similar objectives of using multiple management tactics and incorporating the knowledge of weed biology and crop physiology into the weed management system. The goals of IWM range from maximizing profit margins to safeguarding natural resources and minimizing the negative impact of weed control practices on the environment. The acceptance of IWM by farmers will depend on their perceived risk to management, individual management capability, and environmental interactions that will influence the economic viability of the cropping system. We have been in this process of developing, integrating, and adopting potential IWM practices for the last 25 to 30 yr. However, strategic directions for research in the future must continue to discover opportunities for enhanced profitability and sustainability.

The fundamental role of integrated weed management (IWM) is to provide a source of scientifically based knowledge from which growers can make informed weed-management decisions. The objectives of this article include (1) highlighting the essential knowledge base required for the success of an IWM cropping system, (2) identifying the barriers to acceptance of IWM, and (3) discussing the future research opportunities for IWM. The minimum knowledge base consists of four key components: the effect of tillage on weed population dynamics, the time of weed emergence relative to the crop, the critical period for weed control, and the concept of a harvest window. There are substantial barriers, however, that reduce the willingness of growers to adopt the components of an IWM cropping system. IWM systems can be perceived as unreliable resulting in increased risk to management. No direct economic benefit can be defined clearly nor has there been sustained support for the adoption of IWM. In the future, IWM must change from a descriptive to a predictive science. As new markets evolve for agricultural products, new quality issues will arise that may influence weed management. Environmental auditing of IWM systems in terms of ISO 14000 accreditation, total carbon credits, or energy use will provide an important template from which comparisons of alternative weed-control strategies can be assessed. IWM strategies must be developed to reduce the risk to management and to gain broader support from the crop-protection industry, growers, and government.

Invasive plants impose threats to both natural and managed ecosystems. Downy brome is among the most aggressive invasive weeds that has infested the shrub-steppe ecoregion of eastern Washington. Hyperspectral remote sensing has potential for early detection and for monitoring the spread of downy brome—information that is essential for developing effective management strategies. Two airborne hyperspectral Advanced Visible Infrared Imaging Spectrometer (AVIRIS) images (electromagnetic spectrum ranging from 400 to 2,500 nm) were acquired at a nominal 4-m ground resolution over a study area in south-central Washington on July 27, 2000 and May 5, 2003. We used a mixture-tuned matched filtering (MTMF) algorithm to classify downy brome and predict its percent cover in each dataset plus a merged multiseasonal dataset using the transformed bands from a minimum noise fraction (MNF) output. The correlation coefficient was 0.79, calculated for the multidate MTMF predicted downy brome abundance, compared to 0.41 and 0.51 derived from the July 2000 and May 2003 data, respectively. Although this study used high spatial resolution (∼3 to 4 m) hyperspectral imagery, this result shows that data acquired in different seasons is more effective for detection of downy brome invasion, compared to single-date datasets. These results support expanded use of multitemporal data for weed mapping to capitalize on spectral differences between seasons for weeds, in this case downy brome, and the surrounding environment.