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The influence of winter annual grass litter on herbicide availability

Published online by Cambridge University Press:  23 August 2019

Shannon L. Clark*
Affiliation:
Graduate Research Assistant, Bioagricultural Sciences and Pest Management Department, Colorado State University, Fort Collins, CO, USA
Paulo V. da Silva
Affiliation:
Graduate Student, Department of Plant Production, University of São Paulo, School of Agriculture“Luiz de Queiroz,” Piracicaba, SP, Brazil
Franck E. Dayan
Affiliation:
Professor, Bioagricultural Sciences and Pest Management Department, Colorado State University, Fort Collins, CO, USA
Scott J. Nissen
Affiliation:
Professor, Bioagricultural Sciences and Pest Management Department, Colorado State University, Fort Collins, CO, USA
Derek J. Sebastian
Affiliation:
Area Sales Manager, Bayer Vegetation Management, Bayer U.S., Cary, NC, USA
*
Author for correspondence: Shannon L. Clark, Bioagricultural Sciences and Pest Management Department, Colorado State University, Fort Collins, CO 80523-1177. Email: shannon.clark@colostate.edu
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Abstract

Invasive winter annual grass infestations on rangeland accumulate large quantities of litter on the soil surface, as plants senesce yearly and decompose slowly. It has been speculated that winter annual grass litter can adsorb soil-active herbicides and reduce overall performance. Three experiments were conducted from 2017 to 2018 at the Colorado State University Weed Research Laboratory to evaluate interception and subsequent desorption of herbicides applied to litter from three invasive winter annual grass species with simulated rainfall. Imazapic, rimsulfuron, and indaziflam were applied to medusahead [Taeniatherum caput-medusae (L.) Nevski], ventenata [Ventenata dubia (Leers) Coss.], and downy brome (Bromus tectorum L.) litter at two amounts (equivalent to 1,300 and 2,600 kg ha−1). Rainfall was simulated at 3, 6, 12, and 24 mm at 0, 1, and 7 d after herbicide application. Herbicide concentration from the collected rainfall was measured using liquid chromatography–tandem mass spectrometry. At 2,600 kg ha−1, B. tectorum herbicide interception was 84.3%, while V. dubia and T. caput-medusae averaged 76% herbicide interception. There were no differences in desorption among the three litter types. Simulated rainfall at 0 d after application recovered 100% of the intercepted rimsulfuron and imazapic from B. tectorum litter, while recovery decreased to 65% with rainfall at 1 or 7 d after application. Only 54% of indaziflam could be recovered at 0 d, and recovery decreased to 33% when rainfall was applied at 1 or 7 d after application. Applying soil-active herbicides before forecasted rain or tank mixing with a POST herbicide to provide initial control could potentially increase the amount of herbicide reaching the soil and provide more consistent invasive winter annual grass control.

Information

Type
Research Article
Copyright
© Weed Science Society of America, 2019 
Figure 0

Table 1. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) conditions for rimsulfuron, imazapic, and indaziflam.

Figure 1

Table 2. Amount of herbicide intercepted by Bromus tectorum, Taeniatherum caput-medusae, and Ventenata dubia litter, as a percentage of total herbicide applied, at two litter amounts (1,300 kg ha−1 and 2,600 kg ha−1).a

Figure 2

Table 3. Parameter estimates describing desorption of rimsulfuron, imazapic, and indaziflam from Bromus tectorum, Taeniatherum caput-medusae, and Ventenata dubia litter after 0, 1, and 7 d with a maximum of 24 mm of simulated rainfall by applying an asymptotic regression model.

Figure 3

Figure 1. Rimsulfuron desorption from Bromus tectorum litter as a function of the amount of simulated rainfall after 0, 1, and 7 d expressed as a percentage of total herbicide intercepted. Data points are the means of replications with bars indicating the standard error of the mean (n = 6): 0 d: $y = 103.45X\left\{ {1 - \exp \left[ {\left( {{\rm{log}}0.1} \right)X\left( {{{24} \over {8.35}}} \right)} \right]} \right\}$; 1 d: $y = 64.58X\left\{ {1 - \exp \left[ {\left( {{\rm{log}}0.1} \right)X\left( {{{24} \over {10.87}}} \right)} \right]} \right\}$; 7d: $y = 72.31X\left\{ {1 - \exp \left[ {\left( {{\rm{log}}0.1} \right)X\left( {{{24} \over {13.06}}} \right)} \right]} \right\}$.

Figure 4

Figure 2. Imazapic desorption from Bromus tectorum litter as a function of the amount of simulated rainfall after 0, 1, and 7 d expressed as a percentage of total herbicide intercepted. Data points are the means of replications with bars indicating the standard error of the mean (n = 6): 0 d: $y = 101.19X\left\{ {1 - \exp \left[ {\left( {{\rm{log}}0.1} \right)X\left( {{{24} \over {6.39}}} \right)} \right]} \right\}$; 1 d: $y = 69.53X\left\{ {1 - \exp \left[ {\left( {{\rm{log}}0.1} \right)X\left( {{{24} \over {8.54}}} \right)} \right]} \right\}$; 7d: $y = 66.22X\left\{ {1 - \exp \left[ {\left( {{\rm{log}}0.1} \right)X\left( {{{24} \over {7.69}}} \right)} \right]} \right\}$.

Figure 5

Figure 3. Indaziflam desorption from Bromus tectorum litter as a function of the amount of simulated rainfall after 0, 1, and 7 d expressed as a percentage of total herbicide intercepted. Data points are the means of replications with bars indicating the standard error of the mean (n = 6): 0 d: y = 2.27x, R2 = 0.94; 1 d: $y = 37.72X\left\{ {1 - \exp \left[ {\left( {{\rm{log}}0.1} \right)X\left( {{{24} \over {19.29}}} \right)} \right]} \right\}$; 7d: $y = 40.89X\left\{ {1 - \exp \left[ {\left( {{\rm{log}}0.1} \right)X\left( {{{24} \over {23.99}}} \right)} \right]} \right\}$.

Supplementary material: File

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