Abstract Introduction A. hybridus interference in soybeans varies with population size and may be quantified by mathematical models that allow establishing the threshold levels. Objective Determine the interference of A. hybridus escaped from an herbicide program and with multiple resistance to EPSPs and ALS-inhibiting herbicides on soybean yield and its economic threshold (ET). Methods Two experiments were conducted in a randomized block design. The treatments consisted of populations of A. hybridus ranging from 0 to 41 plants m-2 (2018/19) and 0 to 32 plants m-2 (2019/20). The yield components and yield plant-1 of soybean were evaluated. The rectangular hyperbola model was fitted to the soybean yield loss. ET was calculated according to yield potential, price paid for grains, control cost and weed control efficiency Results The increase in populations of A. hybridus has decreased in the number of pods and grains-1 of soybean in both periods. The parameter i was 4.47 and 8.32%, and the ET ranged from 0.16 to 1.21 plants m-2 in 2018/19 and from 0.09 to 0.65 plants m-2 in 2019/20. Conclusions One A. hybridus m-2 may reduce 6.4% in the grain yield of soybean. ET occurs within the range of 0.09 to 1.21 plants m-2.

Abstract Mixing herbicides is a common practice in agriculture, to optimize farm management practices, widen the weed control spectrum, enhance application efficiency, and manage herbicide resistance. Interactions between herbicides can occur within the spray tank, on the leaf surface, and/or inside the plant, resulting in physicochemical and physiological interactions. Additive, synergistic, or antagonistic effects can result from these interactions. Given the range in plant response and the potential for negative and positive outcomes for weed management, predicting herbicide interactions before using mixtures would be of great value. Therefore, the physiological responses in the literature can help to ensure efficient weed control and avoid unwanted effects in the field. This review compiles information on physiological and physicochemical interactions between herbicides, addressing the most known cases of synergism, antagonism, and additivity, as well as their physiological bases, and the methods for evaluating herbicide interactions. Reference models for herbicide interactions have been reported and they usually interfere interpretation of the mixture effect. Antagonistic interactions can increase the evolution of weed resistance by favoring the survival of individuals exposed to the herbicide. Physicochemical incompatibility in the spray tank usually causes herbicide antagonism, whereas both synergism and antagonism can result from increased or decreased uptake/translocation and from physiological changes in the plant. agriculture practices spectrum efficiency surface andor Additive synergistic value Therefore field additivity bases effect uptaketranslocation uptake translocation