TITLE:
Use of Logistic Regression Model for Prediction of Non-Timber Forest Products
AUTHORS:
Alexandre Leandro Santos de Abreu, Ricardo de Oliveira Gaspar, Mirella Basileu de Oliveira Lima, Mauro Eloi Nappo, Eraldo Aparecido Trondoli
KEYWORDS:
Forest Management, Regression Model, Logit, Euterpe edulis Mart
JOURNAL NAME:
American Journal of Plant Sciences,
Vol.8 No.11,
October
30,
2017
ABSTRACT: The use of non-timber is a valuable alternative for
the conservation of tropical forests. Juçara (Euterpe edulis Mart.) is considered one of the main alternatives in
the Atlantic Forest for the production of açaí pulp. However, there are few
studies that aim to evaluate their production. The present study aimed to
construct a probabilistic model to predict the production of Euterpe edulis bunches, using
dendrometric variables and competition index. Twenty plots of 10 × 50 m were sampled in an area with said specie, showing the arboreal
entities with diameter at breast height > 4.8 cm, and recording the Euterpe
edulis phenomena. The main variables influencing the production of bunches
were assessed using logistic regression model. The logistic regression showed
the variables diameter breast height (DBH) and total height (h) as significant
to explain the variation between productive and non-productive entities. The
competition index tested was not significant (p-value = 0.221). The model of prediction of curl production in Juçara can be
written as: Zi = -6.878594
+ 0.2522454 × DBH + 0.1951574 × h. The use of a logistic regression model showed potential for prediction
of non-timber forest products.