Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/88442
Type of publication: Straipsnis Clarivate Analytics Web of Science ar/ir Scopus / Article in Clarivate Analytics Web of Science or / and Scopus (S1)
Field of Science: Miškotyra / Forestry (A004)
Author(s): Danusevičius, Darius;Masaitis, Gediminas;Mozgeris, Gintautas
Title: Visible and near infrared hyperspectral imaging reveals significant differences in needle reflectance among Scots pine provenances
Is part of: Silvae genetica. Warsaw: De Gruyter, 2014, Vol. 63, iss. 4
Extent: p. 169-180
Date: 2014
Keywords: Pinus sylvestris;Forest inventory;Genetic diversity;Phenology;Remote sensing
Abstract: Genetic diversity is an important indicator of forest sustainability requiring particular attention and new methods to obtain fast and cheap estimates of genetic diversity. We assessed the differences in visible (VIS) and near infrared (NIR) spectral reflectance properties of detached shoots of several distant Scots pine provenances aiming to identify the most informative spectral wavebands and the seasonal time for the genetic diversity scoring. Shoots of five trees per provenance were sampled at two week intervals during the active growth and fall. The samples were scanned using a hyperspectral camera, equipped with a highly sensitive spectrometer capable of covering the spectral range of 400-1000 nm with a sampling interval of 0.6 nm. The ANOVAs revealed significant provenance effects on the spectral reflectance at variable spectral intervals depending on the sampling occasion. During the active growth, PCA identified the most informative wavebands over whole spectral range investigated. During the shoot/needle hardiness development, NIR was the most informative. Provenance ranking in spectral reflectance returned geographically interpretable pattern. We conclude that there are significant provenance attributable and interpretable differences in spectral reflectance of Scots pine needles providing a good opportunity for detecting this spectral variation with the hyperspectral imaging technique
Internet: https://content.sciendo.com/downloadpdf/journals/sg/63/1-6/article-p169.xml
https://doi.org/10.1515/sg-2014-0022
Affiliation(s): Lietuvos agrarinių ir miškų mokslų centro filialas Miškų institutas
Vytauto Didžiojo universitetas
Žemės ūkio akademija
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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