Yield losses due to weeds are a major threat to wheat production and economic well-being of farmers in the United States and Canada. The objective of this Weed Science Society of America (WSSA) Weed Loss Committee report is to provide estimates of wheat yield and economic losses due to weeds. Weed scientists provided both weedy (best management practices but no weed control practices) and weed-free (best management practices providing >90% weed control) average yield from replicated research trials in both winter and spring wheat from 2007 to 2017. Winter wheat yield loss estimates ranged from 2.9% to 34.4%, with a weighted average (by production) of 25.6% for the United States, 2.9% for Canada, and 23.4% combined. Based on these yield loss estimates and total production, the potential winter wheat loss due to weeds is 10.5, 0.09, and 10.5 billion kg with a potential loss in value of US$2.19, US$0.19, and US$2.19 billion for the United States, Canada, and combined, respectively. Spring wheat yield loss estimates ranged from 7.9% to 47.0%, with a weighted average (by production) of 33.2% for the United States, 8.0% for Canada, and 19.5% combined. Based on this yield loss estimate and total production, the potential spring wheat loss is 4.8, 1.6, and 6.6 billion kg with a potential loss in value of US$1.14, US$0.37, and US$1.39 billion for the United States, Canada, and combined, respectively. Yield loss in this analysis is greater than some previous estimates, likely indicating an increasing threat from weeds. Climate is affecting yield loss in winter wheat in the Pacific Northwest, with percent yield loss being highest in wheat-fallow systems that receive less than 30 cm of annual precipitation. Continued investment in weed science research for wheat is critical for continued yield protection.

Potential effectiveness of harvest weed seed control (HWSC) systems depends upon seed shatter of the target weed species at crop maturity, enabling its collection and processing at crop harvest. However, seed retention likely is influenced by agroecological and environmental factors. In 2016 and 2017, we assessed seed-shatter phenology in 13 economically important broadleaf weed species in soybean [Glycine max (L.) Merr.] from crop physiological maturity to 4 wk after physiological maturity at multiple sites spread across 14 states in the southern, northern, and mid-Atlantic United States. Greater proportions of seeds were retained by weeds in southern latitudes and shatter rate increased at northern latitudes. Amaranthus spp. seed shatter was low (0% to 2%), whereas shatter varied widely in common ragweed (Ambrosia artemisiifolia L.) (2% to 90%) over the weeks following soybean physiological maturity. Overall, the broadleaf species studied shattered less than 10% of their seeds by soybean harvest. Our results suggest that some of the broadleaf species with greater seed retention rates in the weeks following soybean physiological maturity may be good candidates for HWSC.

The effect of plant phenology and canopy structure of four crops and four weed species on reflectance spectra were evaluated in 2016 and 2017 using in situ spectroscopy. Leaf-level and canopy-level reflectance were collected at multiple phenologic time points in each growing season. Reflectance values at 2 wk after planting (WAP) in both years indicated strong spectral differences between species across the visible (VIS; 350–700 nm), near-infrared (NIR; 701–1,300 nm), shortwave-infrared I (SWIR1; 1,301–1,900 nm), and shortwave-infrared II (SWIR2; 1,901–2,500 nm) regions. Results from this study indicate that plant spectral reflectance changes with plant phenology and is influenced by plant biophysical characteristics. Canopy-level differences were detected in both years across all dates except for 1 WAP in 2017. Species with similar canopy types (e.g., broadleaf prostrate, broadleaf erect, or grass/sedge) were more readily discriminated from species with different canopy types. Asynchronous phenology between species also resulted in spectral differences between species. SWIR1 and SWIR2 wavelengths are often not included in multispectral sensors but should be considered for species differentiation. Results from this research indicate that wavelengths in SWIR1 and SWIR2 in conjunction with VIS and NIR reflectance can provide differentiation across plant phenologies and, therefore should be considered for use in future sensor technologies for species differentiation.

Greenhouse studies were conducted to evaluate absorption, translocation, and metabolism of¹⁴C-glufosinate in glufosinate-resistant cotton, nontransgenic cotton, Palmer amaranth, and pitted morningglory. Cotton plants were treated at the four-leaf stage, whereas Palmer amaranth and pitted morningglory were treated at 7.5 and 10 cm, respectively. All plants were harvested at 1, 6, 24, 48, and 72 h after treatment (HAT). Absorption of¹⁴C-glufosinate was greater than 85% 24 h after treatment in Palmer amaranth. Absorption was less than 30% at all harvest intervals for glufosinate-resistant cotton, nontransgenic cotton, and pitted morningglory. At 24 HAT, 49 and 12% of radioactivity was translocated to regions above and below the treated leaf, respectively, in Palmer amaranth. Metabolites of¹⁴C-glufosinate were detected in all crop and weed species. Metabolism of¹⁴C-glufosinate was 16% or lower in nontransgenic cotton and pitted morningglory; however, metabolism rates were greater than 70% in glufosinate-resistant cotton 72 HAT. Intermediate metabolism was observed for Palmer amaranth, with metabolites comprising 20 to 30% of detectable radioactivity between 6 and 72 HAT.

Field studies were conducted in 2016 and 2017 at Clinton, NC, to quantify the effects of season-long interference of large crabgrass [Digitaria sanguinalis (L.) Scop.] and Palmer amaranth (Amaranthus palmeri S. Watson) on ‘AG6536’ soybean [Glycine max (L.) Merr.]. Weed density treatments consisted of 0, 1, 2, 4, and 8 plants m⁻² for A. palmeri and 0, 1, 2, 4, and 16 plants m⁻² for D. sanguinalis with (interspecific interference) and without (intraspecific interference) soybean to determine the impacts on weed biomass, soybean biomass, and seed yield. Biomass per square meter increased with increasing weed density for both weed species with and without soybean present. Biomass per square meter of D. sanguinalis was 617% and 37% greater when grown without soybean than with soybean, for 1 and 16 plants m⁻² respectively. Biomass per square meter of A. palmeri was 272% and 115% greater when grown without soybean than with soybean for 1 and 8 plants m⁻², respectively. Biomass per plant for D. sanguinalis and A. palmeri grown without soybean was greatest at the 1 plant m⁻² density. Biomass per plant of D. sanguinalis plants across measured densities was 33% to 83% greater when grown without soybean compared with biomass per plant when soybean was present for 1 and 16 plants m⁻², respectively. Similarly, biomass per plant for A. palmeri was 56% to 74% greater when grown without soybean for 1 and 8 plants m⁻², respectively. Biomass per plant of either weed species was not affected by weed density when grown with soybean due to interspecific competition with soybean. Yield loss for soybean grown with A. palmeri ranged from 14% to 37% for densities of 1 to 8 plants m⁻², respectively, with a maximum yield loss estimate of 49%. Similarly, predicted loss for soybean grown with D. sanguinalis was 0 % to 37% for densities of 1 to 16 m⁻² with a maximum yield loss estimate of 50%. Soybean biomass was not affected by weed species or density. Results from these studies indicate that A. palmeri is more competitive than D. sanguinalis at lower densities, but that similar yield loss can occur when densities greater than 4 plants m⁻² of either weed are present.

Investigating the effects of soil properties on herbicide persistence can aid in evaluating the carryover potential of herbicides in soil and the consequent injury risk to rotational crops. Laboratory incubation experiments were conducted to quantify the persistence of atrazine, mesosulfuron‐methyl, and topramezone in five regional soils under aerobic conditions at 23 °C. Additionally, mesosulfuron‐methyl persistence was tested at 7 °C, which is representative of regional average winter soil temperature. Herbicide half‐life was calculated with the logarithmic form of first‐order rate of degradation using linear regression and was correlated with soil properties. Half‐lives of atrazine (37–73 d) and topramezone (15–19 d) varied among soil types at 23 °C. Mesosulfuron‐methyl half‐life varied among soils at 7 °C (8.8–9.8 d) and 23 °C (5.4–5.8 d) and between temperatures. Atrazine and topramezone half‐lives were shortest in Candor sand (4% clay, 1.8% organic matter [OM], pH 5.1) and longest in Portsmouth sandy loam (13% clay, 5.3% OM, pH 4.3). Mesosulfuron‐methyl half‐life was longer at lower soil temperature. Half‐lives of atrazine, mesosulfuron‐methyl, and topramezone were correlated with soil OM content (r = .83, −.53, and .63, respectively) and pH (r = −.86, .55, and −.57). Additionally, atrazine and topramezone half‐lives were positively correlated with soil clay content (r = .83 and .71), and mesosulfuron‐methyl half‐life was negatively correlated with temperature (r = −.97). Correlations between soil OM content, clay content, and pH among soil types may have influenced herbicide persistence.