Published online by Cambridge University Press: 09 July 2020
Rush skeletonweed is an aggressive perennial weed that establishes itself on land in the Conservation Reserve Program (CRP), and persists during cropping following contract expiration. It depletes critical soil moisture required for yield potential of winter wheat. In a winter wheat/fallow cropping system, weed control is maintained with glyphosate and tillage during conventional fallow, and with herbicides only in no-till fallow. Research was conducted for control of rush skeletonweed at two sites in eastern Washington, Lacrosse and Hay, to compare the effectiveness of a weed-sensing sprayer and broadcast applications of four herbicides (aminopyralid, chlorsulfuron + metsulfuron, clopyralid, and glyphosate). Experimental design was a split-plot with herbicide and application type as main and subplot factors, respectively. Herbicides were applied in the fall at either broadcast or spot-spraying rates depending on sprayer type. Rush skeletonweed density in May was reduced with use of aminopyralid (1.1 plants m−2), glyphosate (1.4 plants m−2), clopyralid (1.7 plants m−2), and chlorsulfuron + metsulfuron (1.8 plants m−2) compared with the nontreated check (2.6 plants m−2). No treatment differences were observed after May 2019. There was no interaction between herbicide and application system. Area covered using the weed-sensing sprayer was, on average, 52% (P < 0.001) less than the broadcast application at the Lacrosse location but only 20% (P = 0.01) at the Hay location. Spray reduction is dependent on foliar cover in relation to weed density and size. At Lacrosse, the weed-sensing sprayer reduced costs for all herbicide treatments except aminopyralid, with savings up to US$6.80 per hectare. At Hay, the weed-sensing sprayer resulted in economic loss for all products because of higher rush skeletonweed density. The weed-sensing sprayer is a viable fallow weed control tool when weed densities are low or patchy.
Associate Editor: Prashant Jha, Iowa State University