J. Anita Dille

Soil microbial and nematode communities as affected by glyphosate and tillage practices in a glyphosate-resistant cropping system

Abstract Field experiments were conducted at Ashland Bottoms in northeastern Kansas and at Hays in western Kansas in 2001, 2002, and 2003 to determine the response of soil microbial and nematode communities to different herbicides and tillage practices under a glyphosate-resistant cropping system. Conventional herbicide treatments were a tank mixture of cloransulam plus S-metolachlor plus sulfentrazone for soybean and a commercially available mixture of acetochlor and atrazine for corn. Glyphosate was applied at 1.12 kg ai ha−1 when weeds were 10 or 20 cm tall in both corn and soybean. Soil samples were collected monthly at Ashland Bottoms during the growing period for soil microbial biomass (SMB) carbon determination. In addition, substrate-induced respiration (SIR) and BIOLOG substrate utilization were determined at the end of the growing season each year at Ashland Bottoms, and nematode populations were determined at the beginning and the end of the growing season at both sites. Direct effects of glyphosate rates on soil microbial and nematode communities were also studied in a controlled environment. Values for SMB carbon, SIR, and BIOLOG substrate utilization were not altered by glyphosate. Nematode community response to the glyphosate treatment was similar under both conventional tillage and no-till environments. Total nematode densities were similar with the glyphosate and conventional herbicide treatments. SMB carbon and BIOLOG substrate utilization did not differ between tillage treatments. Nematode densities were greater under conventional tillage than in the no-till system. This study showed that soil health when glyphosate was applied in a glyphosate-resistant cropping system was similar to that of cropping systems that used conventional herbicides. Nomenclature: Glyphosate; corn, Zea mays L. ‘Asgrow RX718RR’, ‘DeKalb 520RRYG’, ‘DeKalb 53-34’; soybean, Glycine max (L.) Merr. ‘Asgrow 3003RR’, ‘Asgrow 3302RR’.

WeedSOFT®: a weed management decision support system

Abstract WeedSOFT® is a decision support system that was developed to help farmers and consultants in Nebraska with the selection of optimal weed management strategies. WeedSOFT® evolved from HERB, a bioeconomic model for soybean that was developed in North Carolina. The program is composed of four independent modules, namely, ADVISOR, EnviroFX, MapVIEW, and WeedVIEW. ADVISOR helps the user select a treatment based on maximum yield or maximum net gain. EnviroFX and MapVIEW provide environmentally relevant herbicide information and county soil maps that indicate vulnerability to groundwater contamination. WeedVIEW is a visual library of color images and line drawings of 46 common weed species. Over 500 farmers and consultants in Nebraska and adjacent states use WeedSOFT®. As a result of the current regionalization effort, the user base is expected to increase rapidly during the next 2 or 3 yr. This article explains the algorithms implemented in the current version of WeedSOFT®. Nomenclature: Soybean, Glycine max (L.) Merr.

How good is your weed map? A comparison of spatial interpolators

Abstract Recent interest in describing the spatial distribution of weeds and studying their association with site properties has increased the use of interpolation to estimate weed seedling density from spatially referenced data. In addition, farmers and consultants adopting elements of site-specific farming practices are using interpolation methods for mapping weed densities as well as soil properties. This study was conducted to compare the performance of four interpolation methods, namely inverse-distance weighting (IDW), ordinary point kriging (OPK), minimum surface curvature (MC), and multiquadric radial basis function (MUL), with respect to their ability to map weed-seedling densities. These methods were evaluated on data from four weed species, velvetleaf, hemp dogbane, common sunflower, and foxtail species, of contrasting biology and infestation levels in corn and soybean production fields in Nebraska. Mean absolute difference (MAD) and root mean square (RMS) between the observed point sample data and the estimated weed seedling density surfaces were used to evaluate the performance of the interpolation methods. Four neighborhood search types were compared within each interpolation method, and Search3 (12 to 16 neighboring locations) generated an interpolated surface with the smallest MAD and RMS indicating the highest precision. IDW with a power coefficient of p = 4 gave the smallest MAD and RMS, as did a test with an elliptical search and no anisotropy. The level of precision of all four interpolation methods was very poor for weed species with low infestation levels (> 75% of field weed-free; MAD ranged from 100 to 187% of the observed mean density), whereas precision was improved for weed species with high infestation levels (< 25% of field weed-free; MAD ranged from 45 to 85%). No single interpolator appears to be more precise than another. Implications of this study indicate that grid sample spacing and quadrat size are more important than the specific interpolation method chosen. Nomenclature: Common sunflower, Helianthus annuus L. HELAN; foxtail species, Setaria spp. SETSS; hemp dogbane, Apocynum cannabinum L. APCCA; velvetleaf, Abutilon theophrasti Medicus ABUTH; corn, Zea mays L.; soybean, Glycine max (L.) Merr.

Mechanism of Antagonism of Mesotrione on Sulfonylurea Herbicides

Abstract Studies were conducted to determine if altered absorption, translocation, or metabolism were the basis for the reduction in sulfonylurea herbicide efficacy on foxtail species when mesotrione was mixed with a sulfonylurea herbicide. Green foxtail and yellow foxtail plants were grown in the greenhouse and treated at the four-leaf stage with 14C-labeled nicosulfuron or rimsulfuron, applied alone or with mesotrione or mesotrione + atrazine. Absorption of nicosulfuron was greater in green foxtail and yellow foxtail 7 d after treatment (DAT) when applied alone, compared with absorption when mixing the herbicide with mesotrione or mesotrione + atrazine. When nicosulfuron was applied alone, 9% more of the nicosulfuron in green foxtail was translocated at 7 DAT, as compared with when nicosulfuron was applied in combination with mesotrione or mesotrione + atrazine. Translocation of nicosulfuron in yellow foxtail, however, was similar when nicosulfuron was applied alone or in combination with mesotrione or mesotrione + atrazine. The addition of mixing rimsulfuron with mesotrione did not reduce the absorption of rimsulfuron in green foxtail 7 DAT, but the addition of mesotrione + atrazine resulted in a 20% decrease in rimsulfuron absorption 7 DAT compared with absorption of rimsulfuron applied alone. Yellow foxtail absorption of rimsulfuron at 7 DAT was decreased by 11 or 20% when mixed with mesotrione or mesotrione + atrazine, respectively. Application of rimsulfuron alone resulted in 6% more herbicide being translocated to the treated tiller in green foxtail at 7 DAT, compared with an application of mesotrione + atrazine and rimsulfuron. Translocation of rimsulfuron in yellow foxtail was similar when applied alone or in combination with mesotrione or mesotrione + atrazine. Nicosulfuron and rimsulfuron metabolism in foxtail species was similar when applied alone or in combination with mesotrione or mesotrione + atrazine. Nomenclature: Atrazine; mesotrione; nicosulfuron; rimsulfuron; green foxtail; Setaria viridis (L.) Beauv. SETVI; yellow foxtail; Setaria glauca (L.) Beauv. SETLU

Common sunflower (Helianthus annuus) and shattercane (Sorghum bicolor) interference in corn

Abstract Multiple weed species in the field combine to cause yield losses and can be described using one of several empirical models. Field studies were conducted to compare observed corn yield loss caused by common sunflower and shattercane populations with predicted yield losses modeled using a multiple species rectangular hyperbola model, an additive model, or the yield loss model in the decision support system, WeedSOFT, and to derive competitive indices for common sunflower and shattercane. Common sunflower and shattercane emerged with corn and selected densities established in field experiments at Scandia and Rossville, KS, between 2000 and 2002. The multiple species rectangular hyperbola model fit pooled data from three of five location–years with a predicted maximum corn yield loss of 60%. Initial slope parameter estimate for common sunflower was 49.2 and 4.2% for shattercane. A ratio of these estimates indicated that common sunflower was 11 times more competitive than shattercane. When common sunflower was assigned a competitive index (CI) value of 10, shattercane CI was 0.9. Predicted yield losses modeled for separate common sunflower or shattercane populations were additive when compared with observed yield losses caused by low-density mixed populations of common sunflower (0 to 0.5 plants m−2) and shattercane (0 to 4 plants m−2). However, a ratio of estimates of these models indicated that common sunflower was only four times as competitive as shattercane, with a CI of 2.5 for shattercane. The yield loss model in WeedSOFT underpredicted the same corn losses by 7.5%. Clearly, both the CI for shattercane and the yield loss model in WeedSOFT need to be reevaluated, and the multiple species rectangular hyperbola model is proposed. Nomenclature: Common sunflower, Helianthus annuus L. HELAN; shattercane, Sorghum bicolor (L.) Moench SORVU; corn, Zea mays L. ‘Asgrow 770RR’, ‘Asgrow RX740RR’, ‘Garst 8349RR’, ‘Midland 7B05RR’.

Efficacy of Sulfonylurea Herbicides when Tank Mixed with Mesotrione

Experiments were conducted in the greenhouse and the field to evaluate the efficacy of various sulfonylurea herbicides applied with mesotrione or mesotrione + atrazine. The addition of mesotrione or mesotrione + atrazine to sulfonylurea herbicides had no adverse effects on the control of large crabgrass or velvetleaf in a controlled environment. Tank mixing mesotrione or mesotrione + atrazine with nicosulfuron or foramsulfuron, however, antagonized nicosulfuron and foramsulfuron control of green foxtail and shattercane. Field experiments conducted in 2004 and 2005 also indicated that addition of mesotrione + atrazine to a sulfonylurea herbicide decreased herbicidal efficacy on green foxtail, yellow foxtail, and shattercane, compared with the sulfonylurea herbicide applied alone. In addition, increasing mesotrione application from 53 to 105 g/ha decreased efficacy of sulfonylurea herbicide in the tank mix on selected grass species. This research showed that the addition of mesotrione to sulfonylurea herbicides resulted in decreased efficacy of sulfonylurea herbicides on green foxtail, yellow foxtail, and shattercane. The addition of atrazine to the tank mix or an increased mesotrione rate will further decrease herbicide efficacy of sulfonylurea herbicides on shattercane and foxtail species. Nomenclature: Atrazine, foramsulfuron, mesotrione, nicosulfuron. rimsulfuron. green foxtail, Setaria viridis (L.) Beauv. SETVI, large crabgrass, Digitaria sanguinalis (L.) Scop. DIGSA, shattercane, Sorghum bicolor (L.) Moench ssp. bicolor SORVU, velvetleaf, Abutilon theophrasti Medicus ABUTH, yellow foxtail, Setaria pumila (Poir.) Roemer & J.A. Schultes SETLU

Soil pH and Cation Exchange Capacity Affects Sunflower Tolerance to Sulfentrazone

Effects of soil pH and cation exchange capacity (CEC) on sunflower tolerance to sulfentrazone were investigated in a greenhouse study. Variables were soil pH (7.0, 7.3, 7.5, and 7.8), soil CEC (8.2, 13.7, 18.4, and 23.3 cmol/kg), and sulfentrazone rate (0, 105, 158, and 184 g ai/ha). Sulfentrazone-induced leaf chlorosis was affected by soil pH at 12 d after planting (DAP), but plants recovered, and earlier differences were not visible 9 d later. At 12 DAP, leaf chlorosis was 3 or 4% more severe in soils with pH 7.3 or higher compared with soils with pH 7.0 when averaged over both sulfentrazone rate and soil CEC. Leaf chlorosis resulting from sulfentrazone rates of 105, 158, and 184 g/ha was 17, 25, and 35% less at 23 cmol/kg than at 8.2 cmol/kg, respectively. Differences in chlorosis among sulfentrazone rates were greatest in soil with low CEC and lessened as soil CEC increased. Plants regained normal color over time, and newly emerging leaves were not affected. However, plant dry weights were reduced when sulfentrazone rate was ≥158 g/ha. Averaged over sulfentrazone rate and soil pH, sunflower dry weights were less when soil CEC was 8.2 compared with a CEC of 13.7 cmol/kg or higher, indicating a greater response at low CEC. Sunflower plant dry matter was not different in sulfentrazone-treated soil with a CEC above 13.7 cmol/kg. At the ranges tested, soil CEC had a considerably greater effect than did pH on sunflower tolerance to sulfentrazone. Nomenclature: Sulfentrazone; sunflower, Helianthus annuus L. ‘Triumph 562’. Additional index words: Bioactivity, chlorosis, crop injury, soil factors. Abbreviations: CEC, cation exchange capacity; DAP, days after planting; OM, organic matter.

Local conditions, not regional gradients, drive demographic variation of giant ragweed (Ambrosia trifida) and common sunflower (Helianthus annuus) across northern U.S. maize belt.

Abstract Knowledge of environmental factors influencing demography of weed species will improve understanding of current and future weed invasions. The objective of this study was to quantify regional-scale variation in vital rates of giant ragweed and common sunflower . To accomplish this objective, a common field experiment was conducted across seven sites between 2006 and 2008 throughout the north central U.S. maize belt. Demographic parameters of both weed species were measured in intra- and interspecific competitive environments, and environmental data were collected within site-years. Site was the strongest predictor of belowground vital rates (summer and winter seed survival and seedling recruitment), indicating sensitivity to local abiotic conditions. However, biotic factors influenced aboveground vital rates (seedling survival and fecundity). Partial least squares regression (PLSR) indicated that demography of both species was most strongly influenced by thermal time and precipitation. The first PLSR components, both characterized by thermal time, explained 63.2% and 77.0% of variation in the demography of giant ragweed and common sunflower, respectively; the second PLSR components, both characterized by precipitation, explained 18.3% and 8.5% of variation, respectively. The influence of temperature and precipitation is important in understanding the population dynamics and potential distribution of these species in response to climate change. Nomenclature: Giant ragweed, Ambrosia trifida L. AMBTR; common sunflower, Helianthus annuus L. HELAN; maize, Zea mays L.; soybean, Glycine max (L.) Merr.

Potential Corn Yield Losses from Weeds in North America

Crop losses from weed interference have a significant effect on net returns for producers. Herein, potential corn yield loss because of weed interference across the primary corn-producing regions of the United States and Canada are documented. Yield-loss estimates were determined from comparative, quantitative observations of corn yields between nontreated and treatments providing greater than 95% weed control in studies conducted from 2007 to 2013. Researchers from each state and province provided data from replicated, small-plot studies from at least 3 and up to 10 individual comparisons per year, which were then averaged within a year, and then averaged over the seven years. The resulting percent yield-loss values were used to determine potential total corn yield loss in t ha−1 and bu acre−1 based on average corn yield for each state or province, as well as corn commodity price for each year as summarized by USDA-NASS (2014) and Statistics Canada (2015). Averaged across the seven years, weed interference in corn in the United States and Canada caused an average of 50% yield loss, which equates to a loss of 148 million tonnes of corn valued at over U.S.

Annual weed competitiveness as affected by preemergence herbicide in corn

26.7 billion annually. Nomenclature: Corn, Zea mays L.