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dc.contributorEscuela Superior y Tecnica de Ingenieros de Minases_ES
dc.contributor.authorOrdóñez, Celestino
dc.contributor.authorOviedo de la Fuente, Manuel
dc.contributor.authorRoca-Pardiñas, Javier
dc.contributor.authorRodríguez Pérez, José Ramón 
dc.contributor.otherIngeniería Cartografica, Geodesica y Fotogrametriaes_ES
dc.date2018-01-16
dc.date.accessioned2018-01-12T13:20:20Z
dc.date.available2018-01-12T13:20:20Z
dc.date.issued2018-01-12
dc.identifier.citationChemometrics and Intelligent Laboratory Systems, 2018, n. 172es_ES
dc.identifier.urihttp://hdl.handle.net/10612/7087
dc.descriptionP. 1-10es_ES
dc.description.abstractThis paper proposes a method to estimate leaf water content from reflectance in four commercial vineyard varieties by estimating the local maxima of a distance correlation function. First, it applies four different functional regression models to the data and compares the models to test the viability of estimating water content from reflectance. It then applies our methodology to select a small number of wavelengths (optimum wavelengths) from the continuous spectrum, which simplifies the regression problem. Finally, it compares the results to those obtained by means of two different methods: a nonparametric kernel smoothing for variable selection in functional data and a wavelet-based weighted LASSO functional linear regression. Our approach proved to have some advantages over these two testing approaches, mainly in terms of the computing time and the lack of assumption of an underlying model. Finally the paper concludes that estimating water content from a few wavelengths is almost equivalent to doing so using larger wavelength intervalses_ES
dc.languageenges_ES
dc.publisherElsevieres_ES
dc.subjectIngeniería agrícolaes_ES
dc.subject.otherVineyardes_ES
dc.subject.otherWater contentes_ES
dc.subject.otherDistance correlationes_ES
dc.subject.otherFunctional analysises_ES
dc.subject.otherDesign pointses_ES
dc.titleDetermining optimum wavelengths for leaf water content estimation from re ectance: a distance correlation approaches_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.description.peerreviewedSIes_ES


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