2024-03-29T07:40:29Zhttp://buleria.unileon.es/oai/requestoai:buleria.unileon.es:10612/70872020-12-10T09:02:47Zcom_10612_17col_10612_18
Determining optimum wavelengths for leaf water content estimation from re ectance: a distance correlation approach
Ordóñez, Celestino
Oviedo de la Fuente, Manuel
Roca-Pardiñas, Javier
Rodríguez Pérez, José Ramón, 1968-
Ingeniería Cartografica, Geodesica y Fotogrametria
Escuela Superior y Tecnica de Ingenieros de Minas
Ingeniería agrícola
Vineyard
Water content
Distance correlation
Functional analysis
Design points
P. 1-10
This 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 intervals
SI
2018-01-16
2018-01-12T13:20:20Z
2018-01-12T13:20:20Z
2018-01-12
info:eu-repo/semantics/article
Chemometrics and Intelligent Laboratory Systems, 2018, n. 172
http://hdl.handle.net/10612/7087
eng
Elsevier
https://buleria.unileon.es/bitstream/10612/7087/4/Embargado%2012%20meses.pdf.jpg
Hispana
TEXT
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BULERIA. Repositorio Institucional de la Universidad de León
http://hdl.handle.net/10612/7087