Floresta e Ambiente
https://floram.org/article/doi/10.1590/2179-8087.038117
Floresta e Ambiente
Original Article Forest Management

Alternatives to Growth and Yield Prognosis for Pinus caribaea var. caribaea Barrett & Golfari

Ouorou Ganni Mariel Guera; José Antônio Aleixo da Silva; Rinaldo Luiz Caraciolo Ferreira; Daniel Alberto Álvarez Lazo; Héctor Barrero Medel

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Abstract

ABSTRACT: The objective of this study was to obtain regression equations and artificial neural networks (ANNs) for prediction and prognosis of the yield of Pinus caribaea var. caribaea Barrett & Golfari. The data used for modeling comes from measuring the variables diameter at breast height (DBH) and total height (Ht) in 550 temporary plots and 14 circular permanent plots with 500 m2 in Pinus caribaea var. caribaea plantations, aged between 3 and 41 years old. In growth prediction, the results indicated Schumacher model as the best fit to the data. On prognosis, the modified Buckman system was better than Clutter’s. ANNs presented a similar performance to the Buckman model in volume prognosis, however these were superior for basal area prognosis.

Keywords

plantations, nonlinear regression, artificial neural networks

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Submitted date:
03/28/2017

Accepted date:
11/21/2017

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