Abstract
Crop models are frequently used in agronomy for simulating crop variables at a discrete time step. This paper describes the application of an artificial neural network in developing a model for yield forecasts in durum wheat, using back-propagation algorithms based on the mechanistic model AFRCWHEAT2 (Porter, 1993; Porter et al., 1993). Given the relevant number of inputs (16) required to operate AFRCWHEAT2, we have tried to develop a simpler model based on a neural network, in order to match AFRCWHEAT2 performance while substantially reducing the need of inputs.
Lingua originale | English |
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Titolo della pubblicazione ospite | Book of abstracts ESA XIIIth Congress |
Pagine | 257-258 |
Numero di pagine | 2 |
Stato di pubblicazione | Pubblicato - 2014 |
Evento | ESA XIIIth Congress - Debrecen Durata: 25 ago 2014 → 29 ago 2014 |
Convegno
Convegno | ESA XIIIth Congress |
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Città | Debrecen |
Periodo | 25/8/14 → 29/8/14 |
Keywords
- AFRCWHEAT2
- Modelling
- durum wheat
- mechanistic model