Modeling weed emergence of Polygonum lapathifolium L. and Solanum nigrum L. in maize

The agronomic importance of knowing weed emergence patterns has been recognized for many years and several studies have been conducted on weed emergence dynamics with various approaches. Predictive weed emergence models can estimate, in a given moment, the percentage of weeds that have already emerged and the successive seedling emergence dynamics. Therefore they may be useful to achieve well-timed and efficient weed control, both chemical and mechanical. There is no universal best approach to create an accurate model, since it depends on many factors, such as climatic characteristics of the area, cultivation practices, etc. A commonly used approach is the hydrothermal time concept, based on the idea that seeds need a certain amount of hydrothermal time to germinate. The aim of the this research was to model weed emergence of Polygonum lapathifolium L. and Solanum nigrum L. to enrich and improve the information provided by the predictive emergence model AlertInf. Base temperature required for the hydrothermal time calculation of these weed species was calculated with an innovative method using alternating temperatures. Base water potential was empirically derived from field data using an iterative process. Emergence dynamics were modelled using data of seedling emergence collected from 2005 to 2012 in maize fields at two sites located in northeastern Italy. Simulating emergence dynamics based on hydrothermal time of species which germinate only with alternating temperature is fundamental to increase number of species predicted by AlertInf and consequently the richness of information provided by the model for more effectively timed weed management.