Natural durability of five tropical wood species in field decay tests

Measuring the natural resistance of wood is fundamental for proper use. The natural durability of five tropical wood species was investigated by field decay testing during exposure for 360 days. Wood logs (length of 0,5 m; diameter of 8 cm - 12 cm) were used in this study. The mass loss and decay index were calculated and visual analysis during the exposure time was performed for all samples. The samples presented evidence of two different groups concerning natural durability. The species in the first group (Mimosa caesalpiniifolia, Mimosa ophthalmocentra, and Mimosa tenuiflora) showed the highest resistance to biodeterioration, better or similar performance compared to treated eucalyptus wood (as control). The other group (Aspidosperma pyrifolium and Cordia oncocalyx) had lower natural resistance in outdoor service, being more susceptible to decay. In general, the wood of the first group is indicated for outdoor uses that require medium or prolonged exposure, such as timber stakes and fence posts

Estimation of the basic density of Eucalyptus grandis wood chips at different moisture levels using benchtop and handheld NIR instruments

With the increasing demand for productivity and quality in the forestry sector, near-infrared (NIR) spectroscopy is promising in the monitoring of wood properties, such as density. However, most predictive models are based on spectra acquired in wood at equilibrium moisture content using benchtop equipment. The objective of this study was to evaluate the performance of the NIR instruments in predicting the basic density of Eucalyptus grandis wood at different moisture contents. The wood chips were evaluated from saturated conditions (freshly felled) to hygroscopic equilibrium conditions using benchtop and portable NIR instruments. Principal component analysis (PCA) was performed to verify the behavior of spectral data, partial least squares discriminant analysis (PLS-DA) to classify density categories, and partial least squares regression (PLS-R) to develop predictive models. The moisture gradient was not the limiting factor for the statistical modeling. PCA discriminated 99.50% of the variation in the data, while the PLS-DA correctly categorized in the range of 0–94% the density classes. The models developed by PLS-R with the benchtop instrument showed a prediction coefficient (R²) ranging from 0.79 to 0.85 and those with the portable instrument ranged from 0.77 to 0.82; the ratios of prediction deviation (RPD) were 2.20 and 2.45, respectively. Thus, NIR spectroscopy has shown potential application in wood under saturated conditions, regardless of the type of instrument. In the industrial context, the use of a portable NIR instrument could streamline wood characterization without the need for drying and transporting samples to the laboratories