Publicación:
Identification of tree species from the Peruvian tropical amazon “Selva Central” forests according to wood anatomy
Identification of tree species from the Peruvian tropical amazon “Selva Central” forests according to wood anatomy
Fecha
2021
Autores
Alves Ferrerira, Cassiana
Inga Guillen, Janet Gaby
Vidal Alanya, Osir Daygor
Goytendia Centeno, Walter
Moya Mateo, Sthefany Madjory
Centeno Utos, Thonny
Vélez Echeverry, Andrés
Gamarra Moreno, Daniel
Tomazello-Filho, Mario
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NC State University
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Abstracto
The “Selva Central” of Peru is characterized by its forest species richness that produces quality wood for countless uses. Therefore, it is necessary to identify the wood and its macroscopic anatomy, which is an important tool for the botanical identification of tree species. For this purpose, 13 sawmills located in 3 provinces were selected that exploit several tree species of “Selva Central”. Sampling of representative woods was carried out, identified by common names and, in the laboratory, they were polished, examined, and grouped by the similarity of the macroscopic anatomical structure, leading to the tree species identification. Twenty tree species were identified, belonging to 17 genera, with emphasis on the Lauraceae and Fabaceae families. However, Moraceae, Meliaceae, Lecythidaceae, Euphorbiaceae, Bignoniaceae, Myristicaceae, Combretaceae, and Burseraceae families were also identified. The anatomical structures of all the identified tree species were described, transversal and longitudinal tangential cross section images were collected, and a species identification key was constructed. The implications and importance of tree species identification via wood anatomy were discussed, in terms of controlling forest exploitation, traceability of the production chain, and the future development of an artificial intelligence tree-species identification method.
Descripción
This research was supported by the Project Concytec – Banco Mundial, through its executing unit is the Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica (FONDECYT) (Project No. 043-2019-FONDECYT- BMINC.INV). A special thanks to the entire team of the research project “MaderApp: Un aplicativo móvil para el reconocimiento automático y en tiempo real de especies maderables comerciales para combatir la tala ilegal en Selva Central, Perú”.
Palabras clave
Wood identification,
Tropical wood species,
Amazon tree species,
Peruvian Forest