WOOD DENSITY VARIATION AND TREE RING DEMARCATION IN Gmelina arborea TREES USING X-RAY DENSITOMETRY

Due to its relationship with other properties, wood density is the main wood quality parameter. Modern, accurate methods - such as X-ray densitometry - are applied to determine the spatial distribution of density in wood sections and to evaluate wood quality. The objectives of this study were to determinate the influence of growing conditions on wood density variation and tree ring demarcation of gmelina trees from fast growing plantations in Costa Rica. The wood density was determined by X-ray densitometry method. Wood samples were cut from gmelina trees and were exposed to low X-rays. The radiographic films were developed and scanned using a 256 gray scale with 1000 dpi resolution and the wood density was determined by CRAD and CERD software. The results showed tree-ring boundaries were distinctly delimited in trees growing in site with rainfall lower than 25 10 mm/year. It was demonstrated that tree age, climatic conditions and management of plantation affects wood density and its variability. The specific effect of variables on wood density was quantified by for multiple regression method. It was determined that tree year explained 25.8% of the total variation of density and 19.9% were caused by climatic condition where the tree growing. Wood density was less affected by the intensity of forest management with 5.9% of total variation.

Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms

J.A. Ferreira Neto, E.C. Santos Junior, U. Fra Paleo, D. Miranda Barros, and M.C.O. Moreira. 2011. Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms. Cien. Inv. Agr. 38(2): 169-178. The objective of this manuscript is to develop a new procedure to achieve optimal land subdivision using genetic algorithms (GA). The genetic algorithm was tested in the rural settlement of Veredas, located in Minas Gerais, Brazil. This implementation was based on the land aptitude and its productivity index. The sequence of tests in the study was carried out in two areas with eight different agricultural aptitude classes, including one area of 391.88 ha subdivided into 12 lots and another of 404.1763 ha subdivided into 14 lots. The effectiveness of the method was measured using the shunting line standard value of a parceled area lot`s productivity index. To evaluate each parameter, a sequence of 15 calculations was performed to record the best individual fitness average (MMI) found for each parameter variation. The best parameter combination found in testing and used to generate the new parceling with the GA was the following: 320 as the generation number, a population of 40 individuals, 0.8 mutation tax, and a 0.3 renewal tax. The solution generated rather homogeneous lots in terms of productive capacity.