Developing a neural network to simplify durum wheat yield prediction in Italy

Simone Bianchi, Lorenzo Barbanti, Tiziano Bettati, Vittorio Rossi, Franco Miglietta, Roberto Ranieri, Giuseppe Piacentino, Piero Toscano

Risultato della ricerca: Contributo in libroContributo a convegno


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 originaleEnglish
Titolo della pubblicazione ospiteBook of abstracts ESA XIIIth Congress
Numero di pagine2
Stato di pubblicazionePubblicato - 2014
EventoESA XIIIth Congress - Debrecen
Durata: 25 ago 201429 ago 2014


ConvegnoESA XIIIth Congress


  • Modelling
  • durum wheat
  • mechanistic model


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