Predictive weed emergence models and bioeconomic models as a tool for integrated weed management.

In Integrated Weed Management herbicide use is justified only when the economic damage caused by the weed population is greater than the cost of the treatment which is known as economic threshold. The competitiveness of the weeds must be known beforehand in order to be able to forecast the potential damage. Economic optimum threshold models give more precise indication because they predict the long–term effects (seed bank) of weed competition and management techniques on population dynamics and annualized net return. Because of the multispecies nature of the weed population and completely different biology and ecology of weed species regarding pests and pathogens, adoption of this threshold approach to weed management has been much slower. In recent years many decision models have been developed to assist growers in weed control decision–making for several crops. The most used one are decision support system (DSS) models and predictive weed emergence models. DSS models integrate biology of weed with economy of crops and give to producers information “if” and “how” to treat. Information “when” to treat is possible while using predictive weed emergence models because they calculate the percentage of weeds that have already emerged out of the total number of plants that may potentially emerge during the season. This information is useful for optimizing application time.