Field experiments were conducted in Louisiana over 2 yr to evaluate the influence of full-season interference from johnsongrass, common cocklebur, or hemp sesbania at densities of 2.5, 0.5, and 2.0 plants m–1 of row, respectively, and simulated insect defoliation of soybean on weed and soybean growth. Defoliation at R2 (full bloom) and R5 (beginning seed development) soybean growth stages was accomplished by removal of zero, one, or two leaflets per soybean trifoliate, which approximated 0, 33, and 66% defoliation, respectively. Height and dry weight of all weeds were not affected by soybean defoliation level or defoliation stage. Soybean height 3 wk after defoliation at R5 was not influenced by weed interference, soybean defoliation level, or defoliation stage in either year. Averaged across soybean defoliation levels and stages in 1994, johnsongrass, common cocklebur, and hemp sesbania reduced soybean yields 30, 15, and 14%, respectively. In 1995, johnsongrass reduced soybean yield 35%. As soybean defoliation level increased, a linear decrease in soybean yield was observed. Averaged across weeds and soybean defoliation stages, 33 and 66% defoliation reduced soybean yield 6 and 20% in 1994 and 12 and 33% in 1995, respectively. Defoliation at R5 resulted in 10% lower yield than defoliation at R2 in one of two years. Yield reduction due to combinations of weeds and soybean defoliation was additive.

Research was conducted to determine the suitability of the Fermi-Dirac distribution function for modeling the seedling emergence of downy brome, johnsongrass, and round-leaved mallow, as influenced by burial depth. Six sets of previously published emergence data were used to formulate the model and test its adequacy. Two independent johnsongrass emergence data sets were used to validate the model. Constant temperature growth chamber studies were conducted to evaluate the effects of temperature and moisture on the model parameters. The Fermi-Dirac distribution function was found to adequately describe the seedling emergence of downy brome, johnsongrass, and round-leaved mallow as indicated by a good visual data fit, narrow confidence intervals for the model parameters, and regression analysis of observed vs. modeled data. Although this function is a model used in physical science, its parameters can be related to abiotic factors such as soil texture, temperature, and moisture.

Research was conducted to formulate a seedling johnsongrass emergence model as influenced by temperature and burial depth using the poikilotherm rate equation. A series of constant-temperature growth chamber experiments with johnsongrass seed buried at various depths in fritted clay was conducted to develop a temperature/burial emergence database. The poikilotherm rate equation was fit to the emergence data from burial depths of 0 to 2.5 cm at constant temperatures between 20 and 44 C. These data were then combined to formulate a single poikilotherm rate equation to model the emergence of seedling johnsongrass from 0 and 2.5 cm deep and 20 to 44 C. This combined model was validated against two independent emergence data sets with good results.

Greenhouse and laboratory studies were conducted to determine the physiological basis for selectivity of nicosulfuron and primisulfuron in 5 plant species. Differential sensitivity of the species was quantified by determining GR50 values (herbicide rate required to reduce plant growth 50%) for each species/herbicide combination. GR50 data indicated the following levels of sensitivity: corn—tolerant to both herbicides; seedling johnsongrass—sensitive to both herbicides; barnyardgrass—sensitive to nicosulfuron and tolerant to primisulfuron; giant foxtail—sensitive to nicosulfuron and tolerant to primisulfuron; and eastern black nightshade—tolerant to nicosulfuron and sensitive to primisulfuron. Studies using 14C-radiolabeled herbicides were conducted to determine whether differential herbicide absorption, translocation, or metabolism contributed to whole plant responses. Nicosulfuron and primisulfuron selectivity in corn, johnsongrass, barnyardgrass, and giant foxtail was primarily due to differential herbicide metabolism rate. Tolerant species metabolized the herbicide more rapidly and extensively than sensitive species. Differential herbicide absorption, translocation, or metabolism did not explain differential sensitivity of eastern black nightshade to the herbicides. Further studies indicated that the tolerance of eastern black nightshade to nicosulfuron and its sensitivity to primisulfuron was directly related to lower sensitivity of the acetolactate synthase (ALS) to nicosulfuron than to primisulfuron. Eastern black nightshade translocated very little (3%) of the nicosulfuron applied. The ALS sensitivity of johnsongrass and eastern black nightshade was similar in the presence of nicosulfuron. A combination of a higher ALS level and less herbicide translocation contributes to tolerance of eastern black nightshade and to sensitivity of johnsongrass to nicosulfuron.

Laboratory studies were conducted to determine the effect of SAN 582 on the absorption, translocation, and metabolism of sethoxydim in johnsongrass and soybean. 14C-sethoxydim absorption in johnsongrass and soybean was enhanced 4 h after application when tank mixed with SAN 582. Absorption in johnsongrass increased from 18% with 14C-sethoxydim applied alone to 65% when applied with SAN 582. Absorption in soybean increased from 30% with 14C-sethoxydim applied alone to 83% when applied with SAN 582. The addition of crop oil concentrate also enhanced foliar absorption of 14C-sethoxydim. Eight hours after application, foliar absorption in johnsongrass increased from 22% with 14C-sethoxydim applied alone to 61% when 14C-sethoxydim was applied with crop oil concentrate. Foliar absorption in soybean increased from 38% with 14C-sethoxydim applied alone to 59% when 14C-sethoxydim was applied with crop oil concentrate. When 14C-sethoxydim was applied in combination with crop oil concentrate and SAN 582, foliar absorption was 84% or more in both johnsongrass and soybean 4 h after application and did not increase over time. Minor differences in translocation were observed, but these differences were not sufficient to account for the increase in foliar activity observed when SAN 582 is tank mixed with sethoxydim. SAN 582 did not affect metabolism of sethoxydim in either species. Based on these data, it appears that SAN 582 increases the efficacy of sethoxydim by enhancing foliar absorption.

The objective of this research was to explore the influence that weed decision threshold (DT; expressed as plants m−2), weed spatial distribution patterns, and spatial resolution of sampling have on potential reduction in herbicide use under site-specific weed management. As a case study, a small plot located in a typical corn field in central Spain was used, constructing very precise distribution maps of the major weeds present. These initial maps were used to generate herbicide prescription maps for each weed species based on different DTs and sampling resolutions. The simulation of herbicide prescription maps consisted of on/off spraying decisions based on information from two different approaches for weed detection: ground-based vs. aerial sensors. In general, simulations based on ground sensors resulted in higher herbicide savings than those based on aerial sensors. The extent of herbicide reductions derived from patch spraying was directly related to the density and the spatial distribution of each weed species. Herbicide savings were potentially high (up to 66%) with relatively sparse patchy weed species (e.g., johnsongrass) but were only moderate (10 to 20%) with abundant and regularly distributed weed species (e.g., velvetleaf). However, DT has proven to be a key factor, with higher DTs resulting in reductions in herbicide use for all the weed species and all sampling procedures and resolutions. Moreover, increasing DT from 6 to 12 plants m−2 resulted in additional herbicide savings of up to 50% in the simulations for johnsongrass and up to 28% savings in the simulations for common cocklebur. Nonetheless, since DT determines the accuracy of patch spraying, the consequences of using higher DTs could be leaving areas unsprayed, which could adversely affect crop yields and future weed infestations, including herbicide-resistant weeds. Considering that the relationship between DT and accuracy of herbicide application depends on weed spatial pattern, this work has demonstrated the possibility of using higher DT values in weeds with a clear patchy distribution compared with weeds distributed regularly.

Dormancy is a critical factor for the survival and persistence of weedy species. Contemporary approaches can be used to identify genes that regulate dormancy directly or indirectly to elucidate key mechanisms, signals, and pathways. Several domesticated plant species have been used as model systems to mark quantitative trait loci (QTL) that affect dormancy in seeds and vegetative propagules directly. A few weedy species have also been used to mark QTL and to determine dormancy genes using microarray analysis. Given the number of serious weeds worldwide and the role that dormancy plays in their persistence, developing fundamental knowledge on dormancy is an important step toward developing new strategies for weed management. This paper describes current research and outlines some weeds that might be candidates for dormancy investigations using molecular genetic and genomics approaches. An underlying theme in the selection of weeds for dormancy investigations is their relation to crop species and the ability to adapt existing resources to investigate dormancy in weedy plants.

Field experiments were conducted in 1999 and 2000 in northern Greece to study interference between johnsongrass from seed or rhizomes and three corn hybrids (‘Dunia’, ‘Papea’, and ‘Costanza’). Fresh weight of each corn hybrid was lower with greater duration of johnsongrass interference, and it was lower for corn grown with johnsongrass from rhizomes than from seed. Corn-silage yield and corn-grain yield were 10 to 14% less than weed-free corn yield when grown with johnsongrass plants from rhizomes 4 wk after sowing (WAS) or from seed 6 WAS. Regression analysis indicated that a corn-grain yield loss of 10% was associated with an interference period of 2.6 to 2.7 WAS for johnsongrass from rhizomes and 4.3 to 5.1 WAS for johnsongrass from seed compared with weed-free corn. Corn-silage yield with season-long interference by johnsongrass from rhizomes or from seed was 83 and 62% lower, respectively, than was weed-free corn yield. Similarly, corn-grain yield with season-long interference by johnsongrass from rhizomes or from seed was 88 and 57% lower, respectively, than was the yield from weed-free corn. Corn-ear length of each hybrid was more affected by johnsongrass interference than was 1,000-seed weight. Johnsongrass plants from rhizomes emerged earlier, grew faster, and produced greater fresh weight than did plants from seed. However, fresh weight and stem number of johnsongrass plants from either seed or rhizomes were not affected by corn hybrids.

Four field experiments were conducted in Louisiana and Mississippi in 2009 and 2010 to evaluate POST herbicides treatments with tembotrione applied alone or as a prepackaged mixture with thiencarbazone for weed control in corn. Treatments included tembotrione at 92 g ai ha−1, thiencarbazone : tembotrione at 15 : 76 g ai ha−1, atrazine at 2,240 g ai ha−1, glufosinate at 450 g ai ha−1, glyphosate at 860 g ae ha−1, and coapplications of tembotrione or thiencarbazone : tembotrione with atrazine, glufosinate, or glyphosate. All treatments were applied to 26-cm corn in the V4 growth stage. Treatments containing thiencarbazone : tembotrione and those with tembotrione controlled barnyardgrass, browntop millet, entireleaf morningglory, hophornbeam copperleaf, johnsongrass, Palmer amaranth, and velvetleaf 85 to 96% and 43 to 97% 28 d after treatment and at corn harvest, respectively. Corn yield ranged from 9,200 to 10,420 kg ha−1 and was greater than the nontreated control following all herbicide treatments, except atrazine alone. Results indicated that thiencarbazone : tembotrione or tembotrione POST is an option for weed management in corn, and applications of thiencarbazone : tembotrione would be strongly encouraged where rhizomatous johnsongrass is problematic.

Natural dissemination of johnsongrass seeds as well as the effect of combine harvesting on this process were studied in corn fields. The estimation of natural dispersal was carried out by two different methods, collecting seeds throughout the season using seed traps and sampling soil–surface seed abundance before harvest using a vacuum device. Both methods showed the same dispersal pattern. A minimum of 84.6% was dispersed in the first 2 m from the focus and a maximum of 1.6% was dispersed beyond the first 5 m. An average of 76.3% of these dispersed seeds were lost or buried after shedding but before harvest. Seed dispersal by the combine harvester was estimated from the difference between soil–surface seed abundance in the same sites pre and postharvest. Although the quantity of seeds dispersed by the combine was similar to those dispersed by natural factors, dispersal distances were significantly higher. Around 90% of the dispersed seeds were found in the first 5 m forward and backward of the combine direction from the infestation source, and 1.6% of the seeds were found beyond 22 m forward and 10 m backward of the combine direction from the infestation source. A large proportion of the seeds dispersed were dormant or not viable. It is concluded that the major role of sexual reproduction in johnsongrass population dynamics may be to spread the risks, promoting dispersal in time and space.

Acetyl-coenzyme A carboxylase (ACCase) assays and absorption, translocation, and metabolism experiments were conducted to investigate the mechanism(s) responsible for resistance in a johnsongrass biotype that exhibited low levels of resistance to the cyclohexanedione (CHD) herbicide sethoxydim and the aryloxyphenoxypropionate (APP) herbicides quizalofop-P and fluazifop-P. The rate of [14C]quizalofop-ethyl absorption was significantly higher in the resistant compared to the susceptible biotype 8, 24, and 48 h after treatment (HAT), but by 72 HAT, there was no significant difference in the amount of [14C]quizalofop-ethyl detected in either biotype. Additionally, little or no differences in the translocation of [14C]quizalofop-ethyl were observed in the resistant and susceptible biotypes at any time interval after application. In [14C]quizalofop-ethyl metabolism experiments, similar levels of quizalofop-ethyl and quizalofop metabolites were observed in the resistant and susceptible biotypes 8, 24, 48, and 72 HAT, but slightly higher levels of quizalofop acid were detected in the resistant biotype 48 and 72 HAT. In ACCase assays, the concentrations of quizalofop-P, clethodim, and sethoxydim that inhibited ACCase activity by 50% (I50) were statistically similar in the two biotypes, indicating that the resistant johnsongrass biotype contains an ACCase that is sensitive to the APP and CHD herbicides. In the absence of APP or CHD herbicides, however, the specific activity of ACCase in the resistant biotype was two to three times greater than that of the susceptible biotype. The specific activity of ACCase in the resistant biotype was also significantly greater than that of the susceptible biotype in the presence of all concentrations of quizalofop-P and sethoxydim and in the presence of 0.1, 1, and 10 µM clethodim. These results suggest that resistance to quizalofop-P and sethoxydim is conferred by an overproduction of ACCase in the resistant johnsongrass biotype.

A high proportion of viable pollen grains must germinate to study the physiology of pollen growth to reduce the confounding effects of environmental influences on pollen germination. The objectives of this study were to evaluate the nuclear state and develop a suitable medium and culture method for in vitro germination of johnsongrass pollen. Johnsongrass pollen was trinucleate, and in vitro tests for pollen viability using Alexander's stain and a fluorochromatic reaction method (FCR) indicated johnsongrass pollen was viable (92.6 to 98.4%). A factorial treatment arrangement of four concentrations of sucrose, two concentrations of boric acid, and two concentrations of calcium nitrate were used to determine the optimum pollen-germination medium composition in suspension culture, agar culture, and cellophane membrane culture. Germination was highest in a suspension culture with a medium containing 0.3 M sucrose, 2.4 mM boric acid, and 3 mM calcium nitrate. Pollen germination using this medium was 78.9% when anthers were harvested just before anthesis.

Field and greenhouse studies were conducted to investigate the compatibility of MSMA in a tank mixture with glyphosate or glufosinate for broadleaf and grass weed control. Glyphosate, glufosinate, and MSMA were evaluated at 0.5×, 1×, and 2× rates, with 1× rates of 0.84 kgae/ha, 0.5 kgai/ha, and 2.2 kgai/ha, respectively. Glyphosate and glufosinate provided similar levels of control for most weed species and were often more efficacious than MSMA alone. Glyphosate controlled Palmer amaranth better than glufosinate. Glufosinate controlled hemp sesbania, pitted morningglory, and ivyleaf morningglory better than glyphosate at one location. Weed control was not improved with the addition of MSMA to glyphosate or glufosinate when compared with either herbicide alone. MSMA antagonized glyphosate efficacy on barnyardgrass, browntop millet, hemp sesbania, Palmer amaranth, and redroot pigweed. MSMA antagonized glufosinate efficacy on browntop millet, hemp sesbania, ivyleaf morningglory, johnsongrass, Palmer amaranth, pitted morningglory, prickly sida, redroot pigweed, and velvetleaf. Antagonism of glyphosate or glufosinate by MSMA was often overcome by applying the 2× rate of either herbicide alone. MSMA is not a compatible tank-mixture partner with glyphosate or glufosinate for weed control in cotton.

Twenty-one grass weeds have evolved resistance to herbicides in Latin America, particularly in rice, soybean, wheat, and orchards. Junglerice, the most widespread and economically important rice weed, evolved resistance to propanil, acetyl-coenzyme A carboxylase (ACCase)-inhibitor herbicides, quinclorac, and imazapyr in Central America, Colombia, and Venezuela. Some junglerice populations are resistant to at least three herbicide modes of action. Other herbicide-resistant (HR) rice weeds are barnyardgrass and gulf cockspur to quinclorac in Brazil, and saramollagrass to ACCase-inhibitor herbicides in Colombia and bispyribac in Venezuela. Populations of weedy rice resistant to imidazolinones are now emerging, most likely originated from gene flow from imidazolinone-resistant rice. Saramollagrass also became resistant to nicosulfuron in corn in Venezuela. Eight species associated with soybean are resistant to ACCase-inhibitor herbicides in Brazil (alexandergrass, goosegrass, and southern crabgrass) and Bolivia (Louisiana cupgrass, itchgrass, sudangrass, and two common wild sorghum species). Four more ACCase-inhibitor–resistant species (hedgehog dogtailgrass, wild oat, rigid ryegrass, and Italian ryegrass) are found in Chile infesting canola and wheat. ACCase-inhibitor–resistant hood canarygrass, littleseed canarygrass, and wild oat are important in wheat in Mexico. Resistance to acetolactate synthase (ALS)-inhibitor herbicides has been reported in itchgrass, goosegrass, and Mexican grass. Italian ryegrass populations resistant to glyphosate have been found in Chile and Brazil. Glyphosate resistance has also evolved in goosegrass in Bolivia and johnsongrass in Argentina. In general, little is done to prevent resistance evolution. An exception is the stewardship programs aiming to prevent gene flow from imidazolinone-resistant rice to weedy rice. Once resistance evolves, HR populations are mostly managed by shifting to herbicides with different modes of action and, in some cases, by slightly modifying agronomic practices. Propanil formulations containing a synergist are used to manage propanil-resistant junglerice. Increased no-till agriculture and planting of glyphosate-resistant crops are likely to select more glyphosate-resistant weeds.

Field studies were conducted in Louisiana and Mississippi in 2009 and 2010 to evaluate PRE herbicide treatments containing isoxaflutole or a prepackaged mixture of thiencarbazone-methyl : isoxaflutole (TCM : isoxaflutole) for weed control in corn. PRE treatments included the premix of TCM : isoxaflutole alone (30 : 80 g ai ha−1) and with atrazine (1,120 g ai ha−1), isoxaflutole alone (90 g ai ha−1) and with atrazine (1,120 g ai ha−1), and the premix of atrazine plus S-metolachlor (1,820 plus 1,410 g ai ha−1). POST treatments included glufosinate (450 g ai ha−1) or glyphosate (870 g ae ha−1) applied to 30-cm corn along with a no POST treatment. All PRE treatments controlled barnyardgrass, entireleaf morningglory, rhizomatous johnsongrass, Palmer amaranth, and velvetleaf 87 to 95% 4 wk after planting (WAP) and browntop millet and hophornbeam copperleaf were controlled 86 to 95% 8 WAP. Weed control was improved 8 and 20 WAP when either POST treatment was applied. TCM : isoxaflutole plus atrazine controlled barnyardgrass, entireleaf morningglory, Palmer amaranth, and velvetleaf at least 90% 20 WAP regardless of POST treatment. TCM : isoxaflutole plus atrazine provided greater control of browntop millet (90%) than isoxaflutole alone or with atrazine and atrazine plus S-metolachlor where control was 86% 20 WAP. Pooled across POST treatments, all PRE treatments containing isoxaflutole or TCM : isoxaflutole controlled rhizomatous johnsongrass better (74 to 76%) than atrazine plus S-metolachlor (67%). Corn yield following herbicide treatments ranged from 9,280 to 11,040 kg ha−1 compared with 9,110 kg ha−1 for the nontreated. Results indicate that TCM : isoxaflutole or isoxaflutole PRE is an option for use in a corn weed management program and may prolong the use of atrazine where weed resistance may be an issue. Where rhizomatous johnsongrass is a problem, TCM : isoxaflutole or isoxaflutole PRE can provide better control than atrazine plus S-metolachlor PRE. Without PRE treatments, glufosinate or glyphosate was needed for season-long weed control.

Field studies were conducted 2004 and 2005 to evaluate weed control following POST applications of glyphosate in combination with either S-metolachlor (premix formulation), pyrithiobac, or trifloxysulfuron in conjunction with glyphosate in second-generation glyphosate-resistant cotton (Roundup Ready Flex). These herbicides were applied in combination with glyphosate in a two-application program at the 2-leaf (LF) (followed by glyphosate alone at the 10-LF growth stage), 6-LF (following glyphosate alone at the 2-LF growth stage), or 10-LF (following glyphosate alone at the 2-LF growth stage) cotton growth stages. No differences in weed control between residual herbicide were observed for goosegrass, hemp sesbania, Johnsongrass, Palmer amaranth, redroot pigweed, sicklepod, or smellmelon. Optimum control of barnyardgrass and browntop millet was achieved with glyphosate plus S-metolachlor. No differences were observed among application timings for control of goosegrass, hemp sesbania, Johnsongrass, pitted morningglory, and smellmelon. Control of barnyardgrass, browntop millet, Palmer amaranth, redroot pigweed, and sicklepod was optimized with residual herbicide application at the 2- or 10-LF timing. No yield differences were observed between residual herbicides, and seed cotton yield averaged 2,800 kg/ha. Yield was maximized when residual herbicide was applied at the 2- or 10-LF growth stage (2,960 to 2,730 kg/ha). Analysis based on numerical yield at particular residual-herbicide application timings and calculated yield for each timing based on the percentage of a standard three-application glyphosate program indicated the most consistent residual-herbicide timing for optimizing yield in a reduced-input Roundup Ready Flex weed-control program occurred at the two-leaf growth stage. All reduced-input programs, however, resulted in cotton yield of at least 93% of that obtained with the standard program.

The feasibility of visual detection of weeds for map-based patch spraying systems needs to be assessed for use in large-scale cropping systems. The main objective of this research was to evaluate the reliability and profitability of using maps of Johnsongrass patches constructed at harvest to predict spatial distribution of weeds during the next cropping season. Johnsongrass patches visually were assessed from the cabin of a combine harvester in three corn fields and were compared with maps obtained in the subsequent year prior to postemergence herbicide application. There was a good correlation (71% on average) between the position of Johnsongrass patches on the two maps (fall vs. spring). The highest correlation (82%) was obtained with relatively large infestations, whereas the lowest (58%) was obtained when the infested area was smaller. Although the relative positions of the patches remained almost unchanged from 1 yr to the next, the infested area increased in all fields during the 4-yr experimental period. According to our estimates, using a strategy based on spraying full rates of herbicides to patches recorded in the map generated in the previous fall resulted in higher net returns than spraying the whole field, either at full or half rate. This site-specific strategy resulted in an average 65% reduction in the volume of herbicide applied to control this weed.

Field studies were conducted during the 2000 and 2001 growing seasons to evaluate imazapic plus 2,4-D for weed control and bermudagrass tolerance. Imazapic at 140 g ai/ha plus 2,4-D at 280 g ai/ha or greater controlled dallisgrass at least 82% and provided at least 90% control of field sandbur, johnsongrass, and field mint. A mixed stand of Texas panicum and large crabgrass was controlled less than 75% and bahiagrass less than 25% with all rates of imazapic plus 2,4-D. Coastal bermudagrass injury was greater than 24% at three of four locations and Tifton 85 injury was greater than 50% at 3 wk after treatment with rates of imazapic plus 2,4-D as low as 70 plus 140 g/ha. Coastal bermudagrass yield was reduced at the first cutting with imazapic plus 2,4-D at 140 plus 210 g/ha and 240 plus 420 g/ha. Imazapic plus 2,4-D at 200 plus 350 g/ha reduced Tifton 85 forage production at the first two cuttings.

Research was conducted to formulate a temperature-dependent population-level model to predict rhizome johnsongrass development to the four-leaf stage. A nonlinear poikilotherm rate equation was used to describe development rates as a function of temperature. Development rate was highest at 36 C and declined at higher temperatures. A temperature-independent Weibull function adequately distributed development times for the population. Coupling the poikilotherm rate equation and the Weibull distribution function yielded a model suitable for characterizing rhizome johnsongrass development to the four-leaf growth stage. The model was tested and validated against independent data sets. Model predictions of 80% of rhizome johnsongrass population at the four-leaf stage were used as the central point of a 4-d application window for using reduced rates of herbicides in johnsongrass management programs. This application window included an average interval of 85 to 99% of johnsongrass population at the desired growth stage in field validation experiments.

Perennial weeds constitute a serious problem in Greek cotton-growing areas, as they strongly competing against the crop and downgrade the final product. Monitoring weeds at a regional scale and relating their occurrence with abiotic factors will assist in the control of these species. Purple nutsedge, field bindweed, bermudagrass, and johnsongrass were studied in cotton crops for three consecutive growing seasons (2007 through 2009) in a large area of central Greece. Weed densities and uniformities per sampling site were assessed in relation to soil and climatic data. Abundance index (AI), which is highly dependent on abiotic factors, was also estimated, and revealed purple nutsedge to the most persistent and damaging species among the recorded weeds. Field bindweed showed the highest correlation with soil properties and especially with clay content. Furthermore, correlation analysis was used over the sampling years in order to assess the stability of weed occurrence in the sampling sites. Purple nutsedge, field bindweed, and bermudagrass proved to be stable in location and intensity. The weed density spatial distribution was evaluated by using local indicators of spatial autocorrelation (LISA) statistics, and was mapped by ordinary kriging and co-kriging interpolation methods. Only 1 to 3 spatial outliers were identified in each 1 of the 3 yr. Between the two interpolation methods co-kriging delivered better results for field bindweed and purple nutsedge, indicating that soil data could improve the estimation of weed occurrence. These co-kriging interpolated weed maps would be a very useful tool for decision makers in taking appropriate weed control measures.