Identifying tropical trees using comparisons with single specimens of species Report as inadecuate

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Eduardo van den Berg ; Douglas Antonio de Carvalho ; Ary Teixeira de Oliveira Filho ;CERNE 2009, 15 1

Author: Peter Hargreaves



CERNE ISSN: 0104-7760 Universidade Federal de Lavras Brasil Hargreaves, Peter; Berg, Eduardo van den; Carvalho, Douglas Antonio de; Oliveira Filho, Ary Teixeira de IDENTIFYING TROPICAL TREES USING COMPARISONS WITH SINGLE SPECIMENS OF SPECIES CERNE, vol.
15, núm.
1, enero-marzo, 2009, pp.
41-48 Universidade Federal de Lavras Lavras, Brasil Available in: How to cite Complete issue More information about this article Journals homepage in Scientific Information System Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Non-profit academic project, developed under the open access initiative IDENTIFYING TREES USING WITH SINGLE SPECIMENS OF SPECIES 41 Identifying tropical TROPICAL trees using comparisons withCOMPARISONS single. Peter Hargreaves1, Eduardo van den Berg2, Douglas Antonio de Carvalho2, Ary Teixeira de Oliveira Filho3 (received: november 13, 2007; accepted: november 28, 2008) ABSTRACT: A taxonomic database system CARipé with integrated links to plant images was constructed to characterize the 800 forest tree species recorded for the catchments of the Rio Grande in the south of Minas Gerais state in Brazil using vegetative morphology.
After a description was ready, its integrated system Empar, completed in a few seconds an identification attempt using automatic character correlation.
Empar proved operationally successful in identification tests of 62 specimens, of as many species, against 554 reference specimens and species from the ESAL Herbarium.
Empar employed a similarity coefficient with the option of a weighting based on character frequency and, in tests, the use of this rarity weighting further improved the performance.
Three tree groups based on leaf type and phyllotaxy were analyzed separately.
From the start, those with compound leaves received more descriptors and the result was little difference in identification performance bet...

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