The development of models that can provide early estimates of crop grain yield losses caused by weed infestation involves identifying explicative variables and mathematical models suited to characterize such losses. The aim of this research was to adjust mathematical models including relative leaf variables, by integrating alternative parameters to quantify losses in soybean grain yield due to the interference of beggarticks (Bidens spp.) and arrowleaf sida (Sida rhombifolia) infestation. Field experiments were carried out using soybean seeding times after plant cover desiccation and beggarticks and arrowleaf densities as main factors as well as bioassays using soybean in monoculture and in association with beggarticks or arrowleaf. Field trials evaluated crop and weed relative leaf area and soil coverage 20 days after soybean emergence (DAE). The bioassays evaluated soybean dry matter 60 DAE. Inclusion of a second parameter (m) in the rectangular hyperbolic model, which limits yield maximum loss, improves model fitting when relative leaf area or soil coverage are used as explicative variables. Bioassay parameter estimates can be integrated with field data, improving prediction of soybean grain yield losses due to weed infestations.
relative leaf area; soil coverage; Bidens spp.; Sida rhombifolia; interference
