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Background Annual bluegrass is a troublesome weed in managed turf systems. A survey was conducted to evaluate the prevalence of herbicide resistance in golf course populations of annual bluegrass in eastern Texas. Screenings were conducted for two photosystem II (PS II)-inhibitor herbicides [simazine preemergence (PRE), amicarbazone postemergence (POST)], two acetolactate synthase (ALS) inhibitors (foramsulfuron POST, trifloxysulfuron POST) and one microtubule assembly inhibitor (pronamide PRE/POST). Results Ninety percent of the populations were found to be resistant to at least one of the tested herbicides. The TX15-14 population was >490-, 178-, 10-, 26-, 4.3- and 3.8-fold, and the TX15-27 population was >490-, 16-, 28-, 84-, 5.2- and 4.1-fold less sensitive to simazine, amicarbazone, foramsulfuron, trifloxysulfuron, pronamide POST and pronamide PRE, respectively, compared to the susceptible standard TX15-SUS. Populations resistant to pronamide POST were completely controlled by pronamide PRE at the label recommended rate. The ALS and psbA gene sequence analysis indicated the presence of target site mutations (Ser-264-Gly in the psbA gene of TX15-14 and Trp-574-Leu in the ALS gene of TX15-27). However, given the absence of any target-site mutation in the ALS gene of TX15-14, the psbA gene of TX15-27 and α-tubulin of both populations, nontarget site mechanisms of resistance are suspected. Conclusion This is the first case of multiple herbicide resistance in annual bluegrass populations to three herbicide modes of action. Results show the widespread occurrence of multiple herbicide resistance in golf course annual bluegrass populations in eastern Texas and emphasize the need for the development and implementation of effective resistance management practices. © 2020 Society of Chemical Industry.

More than 70 years after modern agriculture declared a 'war on weeds', they continue to thrive and suppress crop yields. Viewing weeds as an enemy that can be defeated if only a powerful enough technology can be deployed is a losing proposition. The latest evidence for the inadequacy of this approach, rampant evolution of multiple herbicide-resistant weed genotypes and dwindling options for chemical control in many production systems, should be seen as an urgent message to all those concerned with the science and practice of weed management: we need another way of thinking about the weed resistance issue. Fortunately, the theoretical and practical foundation of this alternative approach, ecological weed management, has been in development for decades. Here, we use Barry Commoner's laws of ecology as a conceptual frame for a review of some of the fundamental concepts of ecological weed management. © 2018 Society of Chemical Industry.

BACKGROUND Dynamic optimization models are normative; they solve for what growers 'ought to do' to maximize some objective, such as long-run profits. While valuable for research, such models are difficult to solve computationally, limiting their applicability to grower resistance management education. While discussing properties of normative models in general, this study presents results of a specific positive model of herbicide resistance management, applied to Palmer amaranth control on a representative cotton farm. This positive model compares a proactive resistance management strategy to a reactive strategy with lower short-run costs, but greater risk of herbicide resistance developing. RESULTS The proactive strategy can pay for itself within 1-4 years, with a yield advantage of 4% or less if the yield advantage begins within 1-2 years of adoption. Whether the proactive strategy is preferable is sensitive to resistance onset and yield losses, but less sensitive to cotton prices or baseline yields. Industry rebates to encourage residual herbicide use (to delay resistance to post-emergence treatments) may be too small to alter grower behavior or they may be paid to growers who would have used residuals anyway. Rebates change grower behavior over a relatively narrow range of model parameters. The size of rebates needed to induce a grower to adopt the proactive strategy declines significantly if growers extend their planning horizon from 1 year to 3-4 years. CONCLUSIONS Whether proactive resistance management is more profitable than a reactive strategy is more sensitive to biological parameters than economic ones. Simulation results suggest growers with longer time horizons (perhaps younger ones) would be more responsive to rebate programs. More empirical work is needed to determine how much rebates increase residual use above what would occur without them. © 2017 Society of Chemical Industry.