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Italian ryegrass (Lolium multiflorum L.) is a highly competitive weed widely disseminated worldwide that affects both summer and winter crops. The development of predictive emergence models can contribute to optimizing weed management. The aim of this study was to develop and validate an empirical emergence model of Italian ryegrass based on soil thermal time. For model development, cumulative emergence in two locations was obtained, and the model was validated with data collected in an experiment conducted independently. Three commonly used emergence models were compared (Gompertz, Logistic, and Weibull). The relationship between emergence and soil thermal time was described best by the Gompertz model. The Gompertz model predicted Italian ryegrass emergence start at 300 thermal time (TT), reaching 50% emergence at 444 TT, and 90% at 590 TT. Model validation performed well in predicting Italian ryegrass emergence and proved to be efficient at describing its emergence. This is a potential predictive tool for assisting farmers with Italian ryegrass management., The authors are grateful to the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Universidade Tecnologica Federal do Paraná (UTFPR), Instituto de Agricultura Sostenible Consejo Superior de Investigaciones Científicas (IAS-CSIC) and HRAC-BR (Associação Brasileira de Ação a Resistência de Plantas Daninhas aos Herbicida) for the infrastructure and financial support.

Italian ryegrass (Lolium multiflorum L.) is an annual grass widely distributed in cultivated crops around the world. This weed causes significant yield reduction in many crops and has developed herbicide resistance. The aim of this study was to develop a cohort-based stochastic population dynamics model that integrates both emergence (thermal time) and dynamic population models as a tool to simulate the population dynamics of susceptible and resistant populations of L. multiflorum under the effects of climate change. The current climate scenario and the increase in the average air temperature by 2.5 &deg, C were considered. Chemical and cultural management strategies commonly used in the South Region of Brazil during the winter and summer seasons were incorporated into the model. In the absence of control and under the current climate conditions, the seed bank population grew until reaching an equilibrium density of 19,121 &plusmn, 371 seeds m&minus, 2 for the susceptible and 20463 &plusmn, 363 seeds m&minus, 2 for the resistant populations. Considering the second climate scenario, the seed bank reaches an equilibrium density of 24,182 &plusmn, 253 seeds m&minus, 2 (+26% in relation to the current scenario) for the susceptible population and 24,299 &plusmn, 254 seeds m&minus, 2 (+18% in relation to the current scenario) for the resistant one. The results showed that the effect of the rise in temperature implies an increase in population in all the management strategies in relation to the current climate scenario. In both climate scenarios, the strategies based on herbicides application controlling cohorts 1 and 2 were the most efficient, and cropping systems including winter oat-soybeans rotation had a smaller impact on the L. multiflorum seed bank than crop rotations including winter wheat or summer corn. Crop rotations including wheat and corn for L. multiflorum management as an adaptive strategy under the future climate change are suggested.