AlertInf: emergence predictive model for weed control in maize in Veneto

Weed control is one of the most important management practices in maize production. Weed time of emergence influences the weed-crop competition, determining the level of damage that the infestation may cause to crop yield. The ability to predict weed emergences can help to optimize control timing, increasing the efficacy of both chemical and mechanical methods and consequently reducing herbicide use. The Department of Environmental Agronomy and Crop Science of the University of Padova has developed the AlertInf model, which provides the percentage of emergence reached by a given weed species in real time using meteorological data, such as soil temperature and rainfall. The Agrobiometeorology Unit of ARPA Veneto has organized an interactive support service using the AlertInf model on their webpage www.arpa.veneto.it/upload_teolo/agrometeo/infestanti.htm to help farmers in planning weed control.