Predicting field weed emergence with empirical models and soft computing techniques
- Gonzalez Andujar, J. L.
- Chantre Balacca, Guillermo Ruben
- Morvillo, C.
- Blanco, Anibal Manuel
- Forcella, F.
DOIAbstract
Seedling emergence is one of the most important phenological processes that influence the success of weed species. Therefore, predicting weed emergence timing plays a critical role in scheduling weed management measures. Important efforts have been made in the attempt to develop models to predict seedling emergence patterns for weed species under field conditions. Empirical emergence models have been the most common tools used for this purpose. They are based mainly on the use of temperature, soil moisture and light. In this review, we present the more popular empirical models, highlight some statistical and biological limitations that could affect their predictive accuracy and, finally, we present a new generation of modelling approaches t...
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