A flexible and practical approach for real-time weed emergence prediction based on Artificial Neural Networks

Most popular emergence prediction models require species-specific population-based parameters to modulate thermal/hydrothermal accumulation. Such parameters are frequently unknown and difficult to estimate. Moreover, such models also rely on hardly available and difficult to estimate soil site-speci...

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Bibliographic Details

Main Authors:	Chantre Balacca, Guillermo Ruben, Vigna, Mario Raul, Renzi Pugni, Juan Pablo, Blanco, Anibal Manuel
Format:	Artículo
Language:	Inglés
Published:	2018
Subjects:	Malezas Emergencia Modelos Inteligencia Artificial Weeds Emergence Models Artificial Intelligence Redes Neuronales Artificiales Modelos de Predicción
Online Access:	https://www.sciencedirect.com/science/article/pii/S1537511017306335 http://hdl.handle.net/20.500.12123/2333 https://doi.org/10.1016/j.biosystemseng.2018.03.014