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An artificial neural network approach to the estimation of stem water potential from frequency domain reflectometry soil moisture measurements and meteorological data

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An artificial neural network approach to the estimation of stem water potential from frequency domain reflectometry soil moisture measurements and meteorological data

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Martí Pérez, PC.; Gasque Albalate, M.; González Altozano, P. (2013). An artificial neural network approach to the estimation of stem water potential from frequency domain reflectometry soil moisture measurements and meteorological data. Computers and Electronics in Agriculture. 91:75-86. doi:10.1016/j.compag.2012.12.001

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Título: An artificial neural network approach to the estimation of stem water potential from frequency domain reflectometry soil moisture measurements and meteorological data
Autor:
Entidad UPV: Universitat Politècnica de València. Departamento de Física Aplicada - Departament de Física Aplicada
Universitat Politècnica de València. Departamento de Ingeniería Rural y Agroalimentaria - Departament d'Enginyeria Rural i Agroalimentària
Fecha difusión:
Resumen:
Stem water potential seems to be a sensitive measure of plant water status. Nonetheless, it is a labour-intensive measurement and is not suited for automatic irrigation scheduling or control. This study describes the ...[+]
Palabras clave: Frequency domain reflectometry , Irrigation scheduling , Principal component analysis , Artificial neural networks
Derechos de uso: Reserva de todos los derechos
Fuente:
Computers and Electronics in Agriculture. (issn: 0168-1699 )
DOI: 10.1016/j.compag.2012.12.001
Editorial:
Elsevier
Versión del editor: http://dx.doi.org/10.1016/j.compag.2012.12.001
Agradecimientos:
The authors are grateful to TECVASA, which obtained a subsidy from the Conselleria de Agricultura, Pesca y Alimentacion de la Generalitat Valenciana (DOCV 5493, 19 April 2007, no. exp.: 2007TAHAVAL00018), and to the Valencian ...[+]
Tipo: Artículo

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