02109naa a2200277 a 450000100080000000500110000800800410001902400550006010000190011524500790013426000090021352012870022265000240150965300220153365300220155565300120157770000230158970000230161270000180163570000230165370000230167670000180169970000230171770000230174077300680176321047722023-06-16       2019    bl uuuu     u00u1 u    #d7 ahttps://doi.org/10.1080/10549811.2018.15465962DOI1 aLIMA. R. B. de  aLumber volume modeling of Amazon Brazilian species.h[electronic resource]  c2019  aAccurate 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.  aRegression analysis  aAmazon rainforest  aForest production  aSawmill1 aFERREIRA, R. L. C.1 aSILVA, J. A. A. da1 aGUEDES, M. C.1 aOLIVEIRA, C. P. de1 aSILVA, D. A. S. da1 aSANTOS, R. M.1 aCARVALHO, E. P. F.1 aSILVA, R. M. de A.  tJournal of Sustainable Forestrygv. 38, n. 3, p. 262-274, 2019.