SPATIAL DISTRIBUTION OF SPONTANEOUS PRODUCTION OF Attalea maripa (Aubl) Mart. IN THE LOW TOCANTINS

• Autor(a) principal: BRITO,RAIMUNDO DIONÍZIO PINTO
• Data de Publicação: 2017
• Outros Autores: FARIAS,PAULO ROBERTO DA SILVA, RODRIGUES,NARA ELISA LOBATO, OLIVEIRA,FABIO JÚNIOR DE, TEXEIRA,RENATO ALVES
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista brasileira de fruticultura (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-29452017000300903
• topic: Spatial dependence; Maripa palm; Kriging; Semivariogram; Variables morphoagronomics

ABSTRACT The production of biofuels from native Amazonian palm trees, belonging to the family of Arecaceae, like Attalea maripa (Aubl) Mart. (Maripa palm), are objects of studies of alternative energy sources for the biofuels production. Thus, the aim of this research was to evaluate the spatial dynamics of agronomic variables of Maripa palm crop production associated with the characteristics of the sampling sites in a spontaneous growth area in the Low Tocantins region. 100 palms of A. maripa were selected, of spontaneous growth and in production phase, on a 10 ha area in the municipality of Cametá / PA, in which the morpho-agronomical variables were collected (MIN, FIN, ABN, LN, DBH, AWAB and AFW), from January 2014 to June 2014. The semivariograms were produced for each variable, which presented a spatial dependence range of 75 meters to MIN, FIN, AWAB and AFW, 80 meters to LN and DBH and 98 meters to ABN. The area of reach found was 17,671.5 m² for MIN, FIN, AWAB and AFW variables, 20,106.2 m² for LN and DBH and 30,171.9 m² for ABN. The data of the variables were adjusted to the spherical model presenting determination coefficient (R²) that ranged from 0.57 to 0.99. The spatial dependence index (SDI) for MIN and FIN variables was 0.49 and 0.31, respectively, indicating moderate spatial dependence. For ABN, LN, DBH and AWAB variables ranged from 0.17 to 0.22, resulting in poor spatial dependence. The AFW variable presented SDI of 0.77. For the visual analysis of the spatial distribution of the studied variables, kriging maps were created.