Methiozolin is applied five or more times per year to control annual bluegrass (Poa annua L.) in cool, temperate areas, but high market demand in the southern United States and recent registration in Australia has expanded the product’s use in variable climates. To better design weed control programs for variable turf types, more information is needed to characterize methiozolin dissipation in different turf systems. Methiozolin was applied biweekly three times to a Kentucky bluegrass (Poa pratensis L.) lawn and adjacent bare soil in New Jersey and on 12 hybrid bermudagrass [Cynodon dactylon (L.) Pers. × Cynodon transvaalensis Burtt Davy] putting greens in Virginia. Soil samples were collected immediately following each application and biweekly for 12 additional weeks. Methiozolin was extracted from each soil sample and analyzed using liquid chromatography with tandem mass spectrometry. Methiozolin was detected only within the top 2 cm of the soil (including verdure), but not below 2 cm, demonstrating its limited vertical mobility. Dissipation was significantly faster in turf-covered soil compared with bare soil. The time required for 50% methiozolin dissipation was 13 and 3.5 d in bare soil and turf-covered soil, respectively. In Virginia, methiozolin dissipation in the 1-m span of three sequential applications differed between years. Methiozolin concentration immediately following the third biweekly application to C. dactylon ×transvaalensis greens was approximately 105% and 180% of the concentration immediately following the initial application, in 2021 and 2022, respectively. This difference in methiozolin accumulation following three applications was attributed to differential C. dactylon ×transvaalensis green up during methiozolin treatments each year. Despite differences in posttreatment methiozolin concentration between years, the temporal dissipation rate later into the summer was consistent. Following the final application on C. dactylon ×transvaalensis greens, methiozolin dissipated 50% and 90% in 14 and 46 d, respectively. These data suggest that methiozolin dissipates more rapidly in turfgrass systems than in bare soil.

The Conyza genus includes nearly 150 species, comprising closely related weedy species. Proper identification of Conyza spp. is essential to develop effective strategies for their management. The overlap of traits, species varieties, and the putative occurrence of hybridization hampers the identification of Conyza spp. and its management in agricultural and natural environments. Herein, we assessed five DNA barcodes and 32 morphological traits to classify Conyza spp. and survey their dispersion in soybean fields [Glycine max (L.) Merr.] in Brazil in 2019, 2020, and 2021. The Conyza accessions included two species, hairy fleabane [Conyza bonariensis (L.) Cronquist) and Sumatran fleabane [Conyza sumatrensis (Retz.) E. Walker], and each species comprised two varieties. The ITS and rps16-trnQ gene regions showed the ability to distinguish between the two Conyza species, while the matK, rbcL, and trnF-trnF gene regions were not polymorphic. Out of 32 morphological traits, phyllary color, involucre shape, capitulescence type, and inflorescence type were the most polymorphic and even reliable for taxonomic purposes. The combination of ITS or ITS+rps16-trnQ regions and the four morphological markers was able to discriminate 91% of the plants, except those of C. bonariensis var. angustifolia. These results support the taxonomic resolution between C. bonariensis and C. sumatrensis and are useful for other Conyza spp. and other closely related weedy species worldwide. Conyza sumatrensis was detected in 94% of soybean fields across macroregions and seasons in Brazil, while C. bonariensis was sparsely dispersed, mainly in the southern macroregion (MRS 1).

Russian thistle (Salsola tragus L.) is among the most troublesome weeds in cropland and ruderal semiarid areas of the Pacific Northwest (PNW). Predicting S. tragus emergence timing plays a critical role in scheduling weed management measures. The objective of this research was to develop and validate a predictive model of the seedling emergence pattern of S. tragus under field conditions in the PNW to increase the efficacy of control measures targeting this species. The relationship between cumulative seedling emergence and cumulative hydrothermal time under field conditions was modeled using the Weibull function. This model is the first to use hydrothermal time units (HTT) to predict S. tragus emergence and showed a very good fit to the experimental data. According to this model, seedling emergence starts at 5 HTT, and 50% and 90% emergence is completed at 56 HTT and 177 HTT, respectively. For model validation, independent field experiments were carried out. Cumulative seedling emergence was accurately predicted by the model, supporting the idea that this model is robust enough to be used as a predictive tool for S. tragus seedling emergence. Our model can serve as the basis for the development of decision support systems, helping farmers make the best decisions to control S. tragus populations in no-till fallow and spring wheat systems.

Furrow-irrigated rice (Oryza sativa L.) has become a popular option for rice production in Arkansas. Highly troublesome weeds like barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.] are a major problem for producers in all rice production systems. Cultural tactics should become a priority to enhance crop growth and competitiveness. This research aimed to determine the effects of bed width (irrigation furrow spacing) and crop row spacing manipulation on E. crus-galli emergence and seed production in a furrow-irrigated rice system. Three bed widths (76, 97, and 152 cm) (whole-plot factor) were used, and plots were drill seeded in four crop row spacings (13, 19, 25, and 38 cm) (subplot factor). The widest width of 152 cm had a slight increase in E. crus-galli density in the early rice life cycle but, by the end of the season, did not differ from the narrower bed widths. Conversely, a decrease in E. crus-galli seed production was observed as the bed width increased. Similar rice canopy coverage and yields occurred among all three bed widths. As for crop row spacing, as the width increased, E. crus-galli density also increased. The 13-cm crop row spacing had the lowest preflood E. crus-galli density, preharvest panicle count, and seed production. No effect of crop row spacing was observed on rice canopy coverage; however, the 13-cm crop row spacing produced the greatest rice yield. The 13-cm crop row spacing paired with the 152-cm bed width may be the optimum combination of ecological strategies in furrow-irrigated rice to reduce E. crus-galli seed production while maintaining rice growth and yield.

Nitrogen availability has an important influence on agricultural weed growth, because many weeds in annual cropping systems are more competitive in high-nitrogen soils. A potential method to control nitrogen availability is through soil carbon amendments, which stimulate soil microbial growth and immobilize nitrogen. Additionally, carbon amendments may alter soil microbial community composition, increase soil biological functioning, and improve soil health. In a 2-yr field experiment in corn (Zea mays L.) and soybean [Glycine max (L.) Merr.], we implemented five amendment treatments to test their ability to alter weed and crop growth through soil nitrogen availability and soil biological functioning. The treatments included: an untreated control, an unamended weed-free control, rye hay adding 3,560 kg C ha−1 and 3,350 kg C ha−1 in 2020 and 2021, respectively, sawdust adding 5,030 kg C ha−1 and 4,350 kg C ha−1 in 2020 and 2021, respectively, and a rye hay and sawdust combined treatment adding 8,590 kg C ha−1 and 7,700 kg C ha−1 in 2020 and 2021, respectively. Each treatment was replicated five times in corn and six times in soybean. Each season, we explored correlations between crop and weed biomass and weed community composition and nitrogen immobilization measured through soil respiration and nitrogen availability. We also explored changes to the soil microbial community composition and soil health as a secondary result of the carbon amendment treatments. Nitrogen availability was lowest in plots treated with the highest C:N amendment. Increasing carbon improved soil health metrics, but the microbial community composition was most affected by the rye hay treatment. Amendments with high C:N reduced weed growth in both soybean and corn plots but only selected for specific weed communities in soybean, leading to improved soybean competitiveness against weeds. In corn, crop growth and weed community composition remained consistent across amendment treatments. Targeted nitrogen immobilization may improve leguminous crop competition in some weed communities as part of an integrated weed management program.

The herbicide dicamba has injured millions of hectares of sensitive plant species in the United States since 2017. This injury has coincided with the commercialization of dicamba-resistant soybean [Glycine max (L.) Merr.] and cotton (Gossypium hirsutum L.). We quantified atmospheric deposition and mass flux of dicamba in 12 soybean production regions of Missouri. Dicamba was routinely detected in weekly deposition samples collected during agriculturally intensive spray periods. Observed concentrations were indicative of both local (<1 km) and long-distance transport (>1 km) of airborne dicamba. High-deposition events (>100 µg m−2) occurred annually in southeast Missouri, and peak dicamba deposited at these sites (12.5 to 84.0 µg m−2) was sufficient to injure non–dicamba resistant soybean. Adoption rate of dicamba-resistant crops and atmospheric stability explained much of the variance, and it is difficult for a herbicide product label to address these variables. Overall, these results demonstrated that dicamba was commonly deposited from the atmosphere during the growing season, and observed concentrations and fluxes were strongly related to the timing and magnitude of rainfall events and the amount of dicamba usage near collection sites.