The adoption of conservation tillage systems has been challenged by concerns potential weed species shifts. A 9-yr study from 1988 to 1996 was conducted Delhi, Ontario, on a loamy sand soil to evaluate the effect of tillage systems (conventional [CT] and no-till [NT]), cover crop Secale cereale, and nitrogen (N) rate (0, 50, 100, 125, 150, and 200 kg N ha−1) on monocrop Zea mays L. (corn) yield and changes in the composition of the weed flora. CT consisted of spring moldboard plowing followed by cultivation with a tooth cultivator. Weed counts were taken in the last 3 yr of the study (1994, 1995, and 1996) prior to postemergence herbicide application and then again 2 to 3 wk after herbicide treatment. Composition or the weed flora was analyzed by canonical discriminant analysis (CDA). The relationship between weed density and tillage system was not consistent. Weed species composition differed between CT and NT systems. Chenopodium album and Amaranthus retroflexus were associated with CT and Digitaria sanguinalis with NT. N rate and cover crop did not affect weed density or species composition. Proper management of weeds with herbicides appeared to minimize any long-term effect on the weed flora resulting from varying N rates. Zea mays yields did not differ between CT and NT systems but were greater in both systems with a cover crop at the higher N rates. Disturbance caused by tillage was more important than N rate and cover crop as a mechanism influencing composition of the weed flora.

Greenhouse and laboratory experiments were conducted to determine the physiological basis for differential tolerance of four Zea mays L. hybrids to RPA 201772. Differences in Zea mays tolerance were quantified by determining the herbicide rate required to injure and reduce Z. mays height 50% (GR50). GR50 values indicated that the Z. mays hybrids ‘Pioneer 3751’ and ‘Pioneer 3737’ were less tolerant to RPA 201772 than the hybrids ‘Pioneer 3394’ and ‘Pioneer 3963.’ Experiments using 14C-RPA 201772 were conducted to determine if hybrid sensitivity was due to differential uptake, translocation, or metabolism of the herbicide. Differences in hybrid tolerance were primarily due to differential herbicide metabolism rates. The time required for 50% inactivation (T½) of RPA 201772 was 42 and 52 h for the more tolerant hybrids and 66 and 93 h for the more sensitive hybrids. Increased uptake of RPA 201772 was also a contributing factor to the sensitivity of one of the hybrids.

The antidotes dichlormid, MON-4660, CGA-154281, R-29148, and MON-13900 were tested in the greenhouse to protect Zea mays L. (corn) against RPA 201772 injury. High rates of RPA 201772 injured four Z. mays hybrids > 30%. R-29148 and MON-13900 were the most effective of the five antidotes evaluated. R-29148 applied at rates ⩾ 45 g ha−1 provided excellent protection against RPA 201772 injury and also prevented injury to Z. mays from diketonitrile, the active metabolite of RPA 201772. In laboratory studies, R-29148 did not alter absorption of 14C-RPA 201772 from soil; however, R-29148 significantly enhanced the rate of RPA 201772 metabolism and inactivation in Z. mays. The mixed function oxidase inhibitor piperonyl butoxide (PBO) increased RPA 201772 injury on all hybrids. These results demonstrate that Z. mays tolerance to RPA 201772 can be enhanced with the use of antidotes such as R-29148 and MON-13900, that R-29148 protects Z. mays from RPA 201772 and diketonitrile by the enhancement of metabolism, and that oxidative reactions may be involved in the metabolism of RPA 201772 in Z. mays.

Bioeconomic weed management models help growers achieve appropriate weed management with less herbicide by matching management to the weed population in a field. Growers, however, will not use bioeconomic models unless cost-effective methods to sample their weed populations are identified. Counting and identifying seeds and seedlings is the most time-consuming and costly part of sampling weed populations. The time required for this process was investigated and modeled as a first step in developing sampling plans for growers using WEEDCAM, a bioeconomic model for weed management in Zea mays L. in Colorado. The time required to count and identify seeds or seedlings was recorded for 9,405 soil cores (5 cm in diameter and 10 cm deep) and 9,726 quadrats (18-cm band over 1.52 m of crop row) collected or examined in eight corn fields in eastern Colorado. The time required to count and identify seeds was best described using a log-linear regression with time increasing with the number of seeds and species and the amount of sand in the core. The average cost of determining there are no seeds in a core is $1.07 for a core from a field with 37% sand and $4.32 if the field has 88% sand. The average cost of counting and identifying 36 seeds of four species is $2.70 and $10.88 for cores with 37 and 88% sand, respectively. The time required to count and identify seedlings was best described using a log-linear regression with time increasing with the number of seedlings and species. Classifying seedlings as grass or broadleaf did not improve the model. The average cost of determining that a quadrat is weed-free is $0.02. The average cost of counting and identifying 37 seedlings is $0.05, $0.07, $0.19, and $0.26 per quadrat for 1, 2, 4, and 6 species, respectively. The cost of identifying seeds and seedlings in eastern Colorado Z. mays fields to use WEEDCAM is estimated as $2.71 per core for the seed bank and $0.08 per quadrat for seedlings.

A field study was established in southern Iowa in 1994 to study seasonal and long-term weed population dynamics on land being brought back into production after 8 yr as part of the conservation reserve program (CRP). The study was a split-plot design with four replications; two tillage regimes, two crop rotations, and three herbicide application methods were used. Even though the tillage regime did not influence individual weed population density throughout the study, the no-till (NT) regime had more weeds compared to conventional tillage (CT). However, when weeds were grouped into categories, tillage influenced broadleaf weeds in 1994 and 1996 and total weeds in 1995. Plots under the NT regime had an average of 46 broadleaf weeds m−2 compared to 27 in CT in 1994, with Amaranthus rudis Sauer (common waterhemp) being the most prevalent. NT had a total of 186 weeds m−2 compared to 125 m−2 weeds in CT in 1995; however, in 1996, CT plots had 184 weeds m−2 compared to 121 m−2 in the NT regime. Except for broadleaf weeds in 1994, crop rotation did not influence the number of weeds, and herbicide application methods had the greatest effect on weed populations. Overall, weed populations were greater in 1997, 1996, and 1995 than in 1994 for all herbicide application methods. The no-herbicide treatment had the highest number of weeds throughout the study. The total number of weeds in band and broadcast treatments averaged 41 and 26 m−2 in 1994; 96 and 24 m−2 in 1995; 96 and 12 m−2 in 1996; and 109 and 95 m−2 in 1997. The use of broadcast herbicides in NT should be recommended for land coming out of CRP. Regardless of the herbicide application method or crop rotation, CT plots had better yields for both Zea mays L. (corn) and Glycine max L. (soybean). Glycine max had a better stand compared to Z. mays in the first year, indicating that a rotation starting with G. max might be preferred in the land coming out of CRP.

Site-specific weed management recommendations require knowledge of weed species, density, and location in the field. This study compared several sampling techniques to estimate weed density and distribution in two 65-ha no-till Zea mays–Glycine max rotation fields in eastern South Dakota. The most common weeds (Setaria viridis, Setaria glauca, Cirsium arvense, Ambrosia artemisiifolia, and Polygonum pensylvanicum) were counted by species in 0.1-m2 areas on a 15- by 30-m (1,352 points in each field) or 30- by 30-m (676 points in each field) grid pattern, and points were georeferenced and data spatially analyzed. Using different sampling approaches, weed populations were estimated by resampling the original data set. The average density for each technique was calculated and compared with the average field density calculated from the all-point data. All weeds had skewed population distributions with more than 60% of sampling points lacking the specific weed, but very high densities (i.e., > 100 plants m−2) were also observed. More than 300 random samples were required to estimate densities within 20% of the all-point means about 60% of the time. Sampling requirement increased as average density decreased. The W pattern produced average species densities that often were similar to the field averages, but information on patch location was absent. Weed counts taken on the 15- by 30-m grid were dependent spatially and weed contour maps were developed. Kriged maps presented both density and location of weed patches and could be used to establish management zones. However, grid-sampling production fields on a small enough scale to obtain spatially dependent data may have limited usefulness because of time, cost, and labor constraints.

Crop rotation is thought to reduce weed density and maintain species diversity, thus preventing the domination of a few problem weeds. Because cropping sequence dictates other agricultural management practices, variations in weed populations between cropping systems may be the direct result of crop rotation, the result of different weed management practices associated with crop rotation, or both. Studies that fail to separate the effects of crop rotation from weed management may generate misleading results. A 10-yr crop rotation study was undertaken to study the dynamics of the standing weed vegetation in Zea mays L., Glycine max L., and Triticum aestivum L. The present paper compared total weed density and diversity between monocultures and rotations under three levels of weed management. Weed management accounted for 37.9% of the variation in total weed density, whereas crop rotation accounted for only 5.5%. Weed density varied between monocultures and rotations in plots where herbicides were applied. The effectiveness of rotations in reducing weed density was dependent upon the crop. Margalef's species richness index (DMG), a measure of diversity, varied among weed management strategies, with 38.4% of the variance attributed to this factor. In the 10th year, when all plots were sown with Z. mays, few cumulative effects of crop rotation were apparent, with two exceptions. In weedy and herbicide-treated plots, weed density was higher on plots cropped with Z. mays the previous year. Also, under these weed management treatments, including a cereal in the crop rotation reduced weed density. Crop rotation, when used in combination with herbicides, provides additional weed control and is therefore an effective tool in integrated weed management.

Field studies were conducted in 1996 and 1997 to determine the effects of RP-201772 and RP-201772 tank mixtures applied to emerged Zea mays. RP-201772 at 105 g ha−1 and tank-mixed metolachlor/benoxacor or atrazine were applied preemergence and to spike, 2-leaf, and 4-leaf Z. mays. Herbicide treatments over the four application timings provided greater than 90% Chenopodium album, Ambrosia artemisiifolia, Amaranthus retroflexus, and Abutilon theophrasti control. However, Setaria faberi control varied among years and application timings. Severe Z. mays injury, 70% and 40%, was observed when RP-201772 tank-mixed with metolachlor/benoxacor was applied to 2-leaf and 4-leaf Z. mays, respectively. Greenhouse studies confirmed Z. mays sensitivity from delayed applications of RP-201772 tank-mixed with metolachlor/benoxacor. Similarly, increased Z. mays injury was observed from postemergence applications of RP-201772 tank-mixed with acetochlor/MON-13900. Herbicide absorption, translocation, metabolism, and retention studies were conducted to determine the physiological basis for the observed Z. mays injury from delayed applications of the RP-201772 tank mixture with metolachlor/benoxacor. Metolachlor/benoxacor increased radiolabeled RP-201772 absorption when applied to spike, 2-leaf, and 4-leaf Z. mays. RP-201772 translocation and metabolism did not explain enhanced Z. mays injury. However, RP-201772 retention increased fivefold when metolachlor/benoxacor was present in the spray solution and applied to 2-leaf and 4-leaf Z. mays. Increased RP-201772 absorption and retention appeared to be the basis for Z. mays injury when tank-mixed with metolachlor/benoxacor and applied to emerged Z. mays.

Site properties and weed species abundance are known to vary spatially across fields. The extent to which they covary is not well understood. The objective of this research was to assess how canonical correlation analysis could be used to identify associations among site properties and weed species abundance within an agricultural field. A farmer-managed field rotated between Zea mays and Glycine max in Boone County, IA, was grid-sampled for site properties in 1992 and for weed species abundance between 1994 and 1997. Twelve site properties were considered in relation to five weed species that were identified and counted after all weed control operations were completed. Site properties such as total nitrogen, Bray-1 P, percent organic carbon, and texture were spatially variable. Weed species abundance was also spatially variable such that most weeds were found in patches and much of the field was weed-free. Canonical correlation analysis identified one to four significant correlations between linear combinations of site properties and weed species abundance. The first and second pairs of linear combinations explained the majority of variation in the data and were used to identify associations among site properties and weed species abundance. In years with Z. mays, the first pair of linear combinations described an association between herbicide activity and weed presence, and the second described topography and soil texture associations with weed presence. In years with G. max, the single observed association described a link between soil texture and presence of Setaria species and Polygonum coccineum. Several consistent associations were identified across years, indicating that site properties can influence weed abundance. However, annual variation in the associations may be attributed to differences in agronomic and weed management practices for each crop, as well as temporal weather variation influencing weed abundance from year to year. This multivariate technique is an important tool to identify associations between site properties and weed abundance that could help explain observed patchy patterns of weed abundance. These associations are an important first step in the generation of hypotheses to be tested at the whole field scale.

The floristic diversity and the vertical distribution of the weed seedbank were studied in ridge tillage (RT) and conventional tillage (CT) systems in clay and clay loam soils. Viable seedbank populations were monitored during 3 yr using germination in a greenhouse. Ridge-tilled fields had a larger soil seedbank (2,992 seeds m−2) than moldboard-plowed fields (1,481 seeds m−2) in the top 15 cm. This result can be explained by the larger perennial seedbank of RT fields at both the 0- to 5-cm and 5- to 15-cm depths. Annual dicot seeds were more abundant in clay soils than in clay loams at the two soil depths. Annual grass seeds were more abundant under CT than under RT in clay soils at the two sampled depths. In clay loams, the density of annual grass seeds in RT fields was six times greater than in CT fields in the top 5 cm of soil and two times greater at the 5- to 15-cm depth. The vertical distribution of total seeds in soil did not differ between tillage systems. The top 5 cm of the 15-cm soil core contained 35 and 46% of all weed seed in CT and RT systems, respectively. However, the CT system had the highest concentration of annual dicot seeds 5 to 15 cm deep, whereas in the RT system, the same depth contained the highest concentration of perennial seeds. These results confirm that tillage systems and soil types can regulate seedbanks. Weed management programs must take this information into account.

At the end of the cropping season in November 1994, Striga hermonthica seed populations were collected in northern Bénin (in the Atacora and Borgou departments). Host crops included Zea mays L. (corn), Pennisetum americanum (pearl millet), and Sorghum bicolor (L.) Moench (sorghum). The seed populations were kept dry in the laboratory, and germination was tested regularly after 2 wk conditioning in the laboratory. The seeds passed through a state of primary dormancy, which was not the same for seed populations collected from Z. mays and S. bicolor fields and those collected from P. americanum fields. The length of the primary dormancy was approximately 6 mo. After passing through primary dormancy (after-ripening), the seeds later went through annual, recurrent states of secondary dormancy. Primary dormancy coincided with the dry season directly after maturity (i.e., between December 1994 and April 1995), and secondary dormancy coincided more or less with the subsequent 1995/1996 and 1996/1997 dry seasons. It is concluded that the secondary dormancy pattern was endogenous. Germination percentages during the period that coincided with the first rainy season after collection were generally higher than during the period that coincided with the second rainy season.

Mulches on the soil surface are known to suppress weed emergence, but the quantitative relationships between emergence and mulch properties have not been clearly defined. A theoretical framework for describing the relationships among mulch mass, area index, height, cover, light extinction, and weed emergence is introduced. This theory is applied to data from experiments on emergence of four annual weed species through mulches of selected materials applied at six rates. Mulch materials, in order from lowest to highest surface-area-to-mass ratio, were bark chips, Zea mays stalks, Secale cereale, Trifolium incarnatum, Vicia villosa, Quercus leaves, and landscape fabric strips. The order of weed species' sensitivity to mulches was Amaranthus retroflexus > Chenopodium album > Setaria faberi > Abutilon theophrasti, regardless of mulch material. The success of emergence through mulches was related to the capacity of seedlings to grow around obstructing mulch elements under limiting light conditions. Mulch area index was a pivotal property for quantitatively defining mulch properties and understanding weed emergence through mulches. A two-parameter model of emergence as a function of mulch area index and fraction of mulch volume that was solid reasonably predicted emergence across the range of mulches investigated.

Identification of associations between site properties and weed species abundance led to the generation of hypotheses as to why weed populations occur where they do, or do not, in agricultural fields. The objective of this research was to use a multivariate statistical technique, canonical correlation analysis, to identify the associations. Two continuous Zea mays production fields under center-pivot irrigation in the central Platte River Valley of Nebraska were grid-sampled between 1994 and 1997 for nine site properties and six to seven weed species. Weed species were identified and counted just prior to postemergence weed control in two adjacent quadrats (1 by 0.38 m) at each grid sampling point. These quadrats represented untreated weed populations emerging between crop rows and treated populations that survived preemergence herbicide banded within the crop row. Canonical correlation analysis identified one to five significant correlations between linear combinations of site properties and weed species abundance depending on field site, years, and between- vs. on-crop row weed populations. The first pair of linear combinations consistently described an association that separated weed species across a gradient of topography and soil type. The second pair of linear combinations described associations between weed species and soil fertility. In all cases, it was hypothesized that management practices strongly interacted with site properties to create the observed associations with weed populations. Other hypothesized mechanisms for weed patchiness include patchiness in available soil moisture that would influence weed seed germination, emergence, and seedling growth. Additional variation in plant-available preemergence herbicide concentration across the field site would vary weed control efficacy. Another mechanism would be variation in soil fertility that affects the growth, reproduction, and competitive ability of both the crop and the weed.

Rhizobacteria isolated from the rhizospheres of dominant weed species in six representative cropping systems and one native prairie ecosystem in mid-Missouri were screened for phytotoxicity on Lactuca sativa seedlings and their host plants in the laboratory. The proportions of deleterious rhizobacteria (DRB) were compared among different cropping systems to determine possible effects of crop management practices on the occurrence of DRB. Phytotoxicity screening on L. sativa seedlings revealed that an integrated crop management system with a Zea mays–Glycine max–Triticum aestivum cover crop rotation under no-tillage had the highest proportion of DRB at 25.3%, followed by an organic farming system with continuous Fragaria virginiana (strawberry) and organic amendments under minimum tillage at 22.9%. A continuous cool-season grass–legume meadow with no agrochemical inputs had the lowest proportion of DRB at 13%. Crop management practices that maintained high soil organic matter had higher proportions of DRB compared to cropping systems with lower organic matter. Phytotoxicity screening on host plants greatly reduced the proportion of rhizobacteria characterized as DRB, likely because of the high sensitivity of L. sativa seedlings to phytotoxins. Although screening on L. sativa is an effective method to detect phytotoxic rhizobacteria, our research indicates that it is essential to test selected cultures on their host weed species for accurate assessment of their occurrence in the field. Using this approach, we found that crop management practices influence the occurrence of DRB naturally associated with weed seedlings. Results suggest that crop production systems can be developed to favor soil microorganisms such as DRB that affect weed growth and thereby become important considerations in overall weed management.