Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloNeural network for the estimation of leaf wetness duration: application to a Plasmopara viticola infections forecasting
Anno di pubblicazione2005
FormatoElettronico
Autore/iDALLA MARTA A., DE VINCENZI M., DIETRICH S., ORLANDINI S.
Affiliazioni autoriDepartment of Agronomy and Land Management, University of Florence, Institute of Biometeorology, National Research Council - Agroecosystem Monitoring Laboratory, Sassari, Italy Institute of Atmospheric Sciences and Climate, National Research Council, Roma, Italy Department of Agronomy and Land Management, University of Florence,
Autori CNR e affiliazioni
  • STEFANO DIETRICH
  • MATTEO DE VINCENZI
Lingua/e
  • inglese
AbstractLeaf wetness duration (LWD) is one of the most important variables responsible for the outbreak of plant diseases but, in spite of its importance, the technology for measurement is not rather reliable. For this reason the modelling appears to be a valid support for LWD assessment. In this work a technique for LWD estimation that was applied in some agro-environmental studies from few years was used: artificial neural network (ANN). The ANN output then was used as input for an epidemiological model to predict Plasmopara viticola infections. The aim of this work was to carry out an ANN capable to find out the relationships between the agrometeorological input and LWD and to evaluate the impact of this estimated LWD when integrated in epidemiological simulations.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da91
Pagine a96
Pagine totali-
RivistaPhysics and chemistry of the earth. Parts A/B/C (Online)
Attiva dal 2002
Editore: Elsevier Science - [New York]
Paese di pubblicazione: Paesi Bassi
Lingua: inglese
ISSN: 1873-5193
Titolo chiave: Physics and chemistry of the earth. Parts A/B/C (Online)
Titolo proprio: Physics and chemistry of the earth. (Online)
Numero volume della rivista30
Fascicolo della rivista-
DOI10.1016/j.pce.2004.08.016
Verificato da refereeSì: Internazionale
Stato della pubblicazione-
Indicizzazione (in banche dati controllate)
  • ISI Web of Science (WOS) (Codice:000227113000011)
  • Scopus (Codice:2-s2.0-13144301660)
Parole chiaveagrometeorology, simulation modelling, grapevine; downy mildew, plasmo
Link (URL, URI)http://www.sciencedirect.com/science/article/pii/S1474706504002001
Titolo parallelo-
Licenza-
Scadenza embargo-
Data di accettazione-
Note/Altre informazioni-
Strutture CNR
  • IBIMET — Istituto di biometeorologia
Moduli/Attività/Sottoprogetti CNR
  • AG.P04.033.001 : Sviluppo di competenze
Progetti Europei-
Allegati
Articolo pubblicato
Tipo documento: application/pdf

Dati storici
I dati storici non sono modificabili, sono stati ereditati da altri sistemi (es. Gestione Istituti, PUMA, ...) e hanno solo valore storico.
Rivista ISIPHYSICS AND CHEMISTRY OF THE EARTH [13835J0]