Título:	Lumber volume modeling of Amazon Brazilian species.
Autoria:	LIMA. R. B. de FERREIRA, R. L. C. SILVA, J. A. A. da GUEDES, M. C. OLIVEIRA, C. P. de SILVA, D. A. S. da SANTOS, R. M. CARVALHO, E. P. F. SILVA, R. M. de A.
Afiliação:	ROBSON B. DE LIMA, UEAP RINALDO L. CARACIOLO FERREIRA, UFRPE JOSÉ A. ALEIXO DA SILVA, UFRPE MARCELINO CARNEIRO GUEDES, CPAF-AP CINTHIA P. DE OLIVEIRA, UFRPE DIEGO A. SILVA DA SILVA, IFAP RENAN M. SANTOS, UEAP ERIK PATRIK F. CARVALHO, UEAP ROBSON MATHEUS DE A. SILVA, UEAP.
Ano de publicação:	2019
Referência:	Journal of Sustainable Forestry, v. 38, n. 3, p. 262-274, 2019.
Conteúdo:	Accurate estimates of lumber volume become an important indicator of production and monetary value for a sawmill. However, such estimates are only obtained directly after logging, and no accurate predictions are made for the Amazonian commercial species. In this sense, the objective was to generate equations of lumber volume for commercial species in Amapá (a state in northern Brazil) by adjusting and selecting regression models. The data of 50 logs processed from 10 commercial species were collected, as well as the quantity and volume of sawn products. Sixteen (16) statistical models were adjusted and statistical weights were performed to evaluate the quality of the estimates and to select the best equation by species. In summary, precise estimates of lumber volume can be obtained by the nº16 model for Carapa guianensis, while the models nº13 and nº15 are the most recommended for Dinizia excelsa and Hymenolobium petraeum, respectively. Model 7 presented the best adjustments for Hymenaea courbaril and Vochysia guianensis. Equations using only the log diameter variable suggest less precise estimates. Also, the log volume should be considered as an important predictor variable to obtain the serrated/lumber volume for the different Amazonian commercial species.
NAL Thesaurus:	Regression analysis
Palavras-chave:	Amazon rainforest Forest production Sawmill
Digital Object Identifier:	https://doi.org/10.1080/10549811.2018.1546596
Tipo do material:	Artigo de periódico
Acesso:	openAccess
Aparece nas coleções:	Artigo em periódico indexado (CPAF-AP)