Three empirical crop yield loss models were used to describe the interference of redroot pigweed and Powell amaranth populations with soybean. Data were obtained from field experiments conducted in 1992 and 1993. Pigweed densities of 0 to eight plants m−1 were established within the soybean row. Pigweed sowing dates were selected so that weed seedling emergence coincided with VE, VC, and V2 soybean growth stages within the time frame of the critical weed-free period. The model incorporating pigweed density and time of emergence gave the best description of soybean yield loss in comparison to the two relative leaf area models. This model was fit to a combined data set of percent yield loss because parameter estimates did not differ among locations and years. Estimated soybean yield losses decreased from 16.4 to 0.5% with delayed pigweed emergence from 0 to 20 degree days. Leaf area of pigweed relative to soybean encompassed pigweed density and time of emergence. Relationship between relative leaf area and soybean yield loss was best described by the one-parameter model estimating a relative damage coefficient ‘q’ than the two-parameter model that also estimated maximum expected yield loss. The relative damage coefficient ‘q’ decreased with later times of leaf area assessment but could be predicted with one leaf area observation. Empirical models that incorporate time of weed emergence represent a step toward improving predictions of yield loss. This is important for the selection of cost-effective weed control strategies.

Economic decision rules for postemergence herbicide control of barnyardgrass in corn were developed. Damage and control functions that formed the basis of an economic model were estimated. Barnyardgrass density and time of emergence relative to the crop were fundamental to calculate the damage function. The control function described barnyardgrass dry weight response to variable doses of two herbicides. Both the biologist's and economist's weed control decision rules, derived from the economic model, were influenced by time of weed emergence relative to the crop, corn yield, and price. Inclusion of time of weed emergence relative to the crop improved our interpretative ability of derived decision rules. The biologist's threshold weed density was more sensitive to changes in parameter values than the economist's optimal herbicide dose strategy. Herbicide use with recommended label dose was greater than either the economically optimal or the biologically effective doses. Use of the biologically effective dose for postemergence weed control decisions was cost efficient and could be of practical significance to corn growers.

Jointed goatgrass is a serious weed in winter wheat, and presently no herbicides are available for its selective control. This study examined the effect of time of emergence and removal on jointed goatgrass interference in winter wheat, as well as its rate of development and soil water extraction. The goal of this study was to suggest cultural practices that minimize jointed goatgrass interference in winter wheat. Jointed goatgrass development was identical to ‘Vona’ winter wheat in two crop seasons, even though precipitation differed drastically between seasons. Depth of soil water extraction of both species was also similar. Jointed goatgrass at 18 plants m−2 reduced grain yield 27 and 17% when emerging 0 and 42 d after Vona, respectively. The relationship between time of jointed goatgrass emergence after winter wheat and grain yield loss was Y = 30.6–0.29X (X = days, r = 0.72), indicating that plants emerging in late fall still caused yield loss. Removing jointed goatgrass by early March prevented winter wheat grain yield loss. The interference data suggests that producers assess infestation levels and plan control measures in early March.

Barnyardgrass is a serious weed problem in cornfields in Ontario. Field experiments were conducted at two locations in 1994 and 1995 to determine the influence of emergence time and barnyardgrass density on corn yield loss, leaf area at 50% silking, and barnyardgrass seed production. Selected barnyardgrass densities up to 200 plants m−1 were established within 12.5 cm on either side of the corn row. Barnyardgrass seeds were planted concurrently with corn and at the 3- to 5- or 1- to 2-leaf stage of corn growth in 1994 and 1995, respectively. Barnyardgrass density and seedling emergence relative to corn influenced the magnitude of corn yield loss. Maximum corn grain yield loss ranged from 26 to 35% for early emerging barnyardgrass, and less than 6% yield loss occurred from barnyardgrass seedlings emerging later than the 4-leaf stage of corn growth. Changes in corn leaf area index at 50% silking reflected the level of barnyardgrass competition in corn. Maximum leaf area reduction ranged from 21 to 23%. Barnyardgrass seed production varied with time of seedling emergence and density. Ten barnyardgrass plants emerging up to the 3-leaf stage of corn growth produced 14,400 to 34,600 seeds m−2 compared to only 1,200 to 2,800 seeds m−2 from plants emerging after the 4-leaf corn stage. The results of this study are essential in the development of an integrated weed management strategy for corn.

Field experiments were conducted to determine the influence of time of emergence and density of single and multispecies populations of pigweed and barnyardgrass on soybean yield and competitive abilities of pigweed and barnyardgrass. Pigweed and barnyardgrass were established at selected densities within 12.5 cm on either side of the soybean row. Pigweed and barnyardgrass seeds were sown concurrently with soybean and at the cotyledon stage of soybean growth. Time and density of pigweed and barnyardgrass seedling emergence relative to soybean influenced the magnitude of soybean yield loss. Maximum soybean yield loss ranged from 32 to 99%, depending upon time of emergence relative to soybean. Pigweed was more competitive than barnyardgrass across all locations, years, and time of weed emergence. When pigweed was assigned a competitive index of 1 on a scale from 0 to 1, the competitive ability of barnyardgrass ranged from 0.075 to 0.40 of pigweed, depending upon location and time of emergence. This is the first multiple weed species study to include time of weed emergence relative to the crop. Competitive index values for multiple weed species must be calculated from field experiments in which weeds are grown with the crop under differing environmental conditions.

Weed control decision rules were derived for the application of postemergence herbicides to control pigweed species in soybean. Field experiments were conducted at two locations in 1992 and 1993 to evaluate soybean-pigweed interference. A damage function was determined that related yield loss to time of pigweed emergence, density, and soybean weed-free yield. A control function described pigweed species response to variable doses of imazethapyr and thifensulfuron. The integration of these two functions formed the basis of an economic model used to derive two weed control decision rules, the biologist's “threshold weed density” and the economist's “optimal dose.” Time of weed emergence had a more significant role than weed density in the economic model. Later-emerging pigweed caused less yield loss and therefore, decision rules lead to overuse of herbicides if emergence time is not considered. The selected herbicide dose influenced the outcome of the control function. Depending on the desired level of weed control, a herbicide could be chosen to either eradicate the escaped weed species (label or biologically-effective doses) or reduce the growth of the weed species and thereby offset interference (optimal dose). The development of a biologically-effective dose by weed species matrix was recommended. Decision rules should not be utilized as an exclusive weed management strategy but rather as a component of an integrated weed management program.

Understanding weed–crop interactions is critical in predicting crop yield loss, but it is also important to understand how these interactions affect weed productivity. Therefore, research was conducted to characterize the weed relative leaf area and weed relative volume of several giant foxtail cohorts in soybean, and to assess weed density and cohort emergence time, weed relative leaf area, and weed relative volume as predictors of giant foxtail shoot biomass and fecundity. Giant foxtail cohorts emerged at VE (emergence), VC (cotyledon), V1 (first node), and V3 (third node) soybean growth stages and were thinned to densities of 0, 4, 16, 36, and 64 plants m−2. Based on weed density and cohort emergence time, the maximum shoot biomass per square meter or the maximum fecundity per square meter differed between years. In contrast, shoot biomass or fecundity per plant, as weed density approached zero, and the rate at which shoot biomass or fecundity decreased exponentially, as time increased, were similar between years. Based on the weed relative leaf area, the cohort effect on giant foxtail shoot biomass differed between years, whereas the cohort effect on giant foxtail fecundity was similar between years. Maximum giant foxtail shoot biomass per square meter or fecundity per square meter differed between years when estimated from weed relative leaf area. Based on the weed relative volume, the cohort effect on giant foxtail shoot biomass per square meter or fecundity per square meter was similar between years, as was the maximum giant foxtail shoot biomass per square meter or fecundity per square meter. The temporal stability of weed relative volume, used to describe giant foxtail shoot biomass or fecundity, may aid in improving bioeconomic weed management models.

Tropical signalgrass is one of the dominant weeds in the Florida turfgrass industry and is potentially troublesome for the southeastern turfgrass industry. Tropical signalgrass is especially problematic for St. Augustinegrass sod producers because of lack of control options. The objectives of our research were to determine the effect of light, pH, temperature, water potential, and planting depth on tropical signalgrass germination and emergence. Tropical signalgrass germination does not require light and is optimum at pH 5 to 6, temperature 25 C, and water potentials greater than − 0.4 MPa. Tropical signalgrass shoots emerged from depths of 0 to 7 cm, with maximum germination when placed on the soil surface. Tropical signalgrass seedlings emerged in the field during the second week of March in Ft. Lonesome, FL. Weekly mean soil and ambient air temperatures at the time of emergence were 20 C. Tropical signalgrass emergence was first observed at 118 and 73 growing degree-days (GDD) (13 C base temperature), with a peak emergence period at 222 and 156 GDD for 2001 and 2002, respectively.

Wild oat is a serious weed in cultivated oat because there are no herbicides to selectively control it. Considering the effect of time of emergence on weed–crop interference is critical for the development of accurate crop yield loss models and weed density thresholds. Therefore, field experiments were conducted at two locations in Saskatchewan, Canada, in 2002 and 2003 to determine the effect of wild oat density and time of emergence on cultivated oat yield and quality. Wild oat was planted at 50 growing degree day (GDD) intervals ranging from 100 GDD before to 100 GDD after crop planting. Wild oat density ranged from 0 to 320 plants m−2. High densities of early emerging wild oat greatly reduced cultivated oat yield and increased wild oat contamination, with observed oat yield losses as great as 70% and wild oat contamination levels of 15%. Wild oat that emerged before cultivated oat caused considerably more yield and quality loss and had higher reproductive output than wild oat that emerged after cultivated oat. The yield loss caused by individual wild oat plants at low densities (parameter I) ranged from 0.40 to 0.49%. The effect of relative time of wild oat emergence (parameter C) always varied significantly between site-years. However, little variation in absolute values within site-years was observed for cultivated oat yield loss, wild oat seed production, and wild oat contamination, suggesting that relative time of wild oat emergence influences all similarly. The results of this study emphasize both the need to control early emerging wild oat, as well as the importance of time of emergence in the prediction of crop yield loss. Furthermore, our approach of conducting an emergence study based on thermal time is novel and demonstrates a robust, mechanistic method of estimating crop yield losses due to relative time of emergence.

Large crabgrass, redroot pigweed, and hairy galinsoga are three important weed species in bell pepper and other crops in the northeastern United States. Field experiments were conducted in 1998 and 1999 to determine the influence of density and relative emergence time of the three weed species on bell pepper fruit yield. Densities of 0, 1, 2, 4, 8, 16, and 32 plants m−1 row were established for each weed species from naturally occurring weed populations. The effects of relative emergence time were studied by investigating the different yield responses to weeds emerging at two different times: 3 d or 2 wk after transplanting of pepper. Both weed density and relative emergence time affected pepper yield loss. The relative competitive ability of weed species varied between years. Large crabgrass was the most competitive species in 1998 and the measure of yield loss at low weed densities, I, was estimated to be 34% on the basis of the nonlinear hyperbolic equation. Redroot pigweed was most competitive in 1999 with an estimate of 88% for I. Hairy galinsoga was the least competitive weed in both years. Maximum yield loss under 32 plants m−1 row ranged from 19% with late-emerging hairy galinsoga in 1998 to 99% with early-emerging redroot pigweed in 1999. A new equation was proposed to characterize the relation between yield loss and weed pressure by expanding the nonlinear hyperbolic equation to include a parameter to account for the change of maximum yield loss with emergence time. The expanded equation generally provided a more accurate prediction of yield loss. In addition, several models are introduced to describe both the effects of density and relative emergence time of multiple weed species on crop yield. Generally these models provided an adequate fit of the data and a good description of the competitive ability of the mixed population.