RT info:eu-repo/semantics/article T1 Determining optimum wavelengths for leaf water content estimation from re ectance: a distance correlation approach A1 Ordóñez, Celestino A1 Oviedo de la Fuente, Manuel A1 Roca-Pardiñas, Javier A1 Rodríguez Pérez, José Ramón A2 Ingeniería CartograficaGeodesica y Fotogrametria K1 Ingeniería agrícola K1 Vineyard K1 Water content K1 Distance correlation K1 Functional analysis K1 Design points AB This paper proposes a method to estimate leaf water content from reflectance in four commercial vineyard varietiesby estimating the local maxima of a distance correlation function. First, it applies four different functionalregression models to the data and compares the models to test the viability of estimating water content fromreflectance. 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 thoseobtained by means of two different methods: a nonparametric kernel smoothing for variable selection in functionaldata and a wavelet-based weighted LASSO functional linear regression. Our approach proved to have someadvantages over these two testing approaches, mainly in terms of the computing time and the lack of assumptionof an underlying model. Finally the paper concludes that estimating water content from a few wavelengths isalmost equivalent to doing so using larger wavelength intervals PB Elsevier YR 2018 FD 2018-01-12 LK http://hdl.handle.net/10612/7087 UL http://hdl.handle.net/10612/7087 NO Chemometrics and Intelligent Laboratory Systems, 2018, n. 172 NO P. 1-10 DS BULERIA. Repositorio Institucional de la Universidad de León RD 28-mar-2024