Predicting field weed emergence with empirical models and soft computing techniques

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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 se...

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Detalles Bibliográficos
Otros Autores: González Andújar, José L., Chantre, Guillermo Rubén, Morvillo, Claudia Mariela, Blanco, A. M., Forcella, Frank
Formato: Artículo
Lenguaje:Inglés
Materias:
ARTIFICIAL NEURAL NETWORKS
GENETIC ALGORITHMS
PREDICTIVE MODELLING
NONLINEAR REGRESSION
WEED CONTROL
DAY DEGREES
Acceso en línea:http://ri.agro.uba.ar/files/intranet/articulo/2016gonzalezandujar.pdf
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Biblioteca Central (FAUBA) de Universidad de Buenos Aires
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