The understanding of the relationship between the properties of wood and charcoal makes it possible to improve the production of charcoal. Therefore, the random forest algorithm was used in this study to analyze the influence of eucalyptus wood properties on the quality of charcoal as well as the accuracy of the predicted values concerning the results estimated by support vector regression and multiple linear regression. Six properties of wood and six properties of charcoal obtained from the hybrid Eucalyptus grandis x Eucalyptus urophylla and from twelve clones of Corymbia torelliana x Corymbia critriodora at the age of seven were measured. In the analysis, the measure of mean decrease in node impurity (residual sum of squares) calculated with the random forest and the copula correlation was used to evaluate the relationship between properties of wood and charcoal. The random forest was compared to the support vector regression and multiple linear regression through the coefficient of determination, linear correlation between observed and predicted values, mean absolute error and root mean squared error. The accuracy of the random forest was greater than that obtained with the support vector regression and multiple linear regression, mainly in terms of the coefficient of determination and the linear correlation between observed and predicted values. The yield and quality of the charcoal produced from clones were mainly influenced by the holocellulose content, heartwood/sapwood ratio, and basic wood density. The apparent relative density of charcoal was the variable in which the random forest algorithm reached the best level of explanation of the variability as a function of the properties of wood, while the minor error was observed for the fixed carbon content.

The objective of the present work was to evaluate the accuracy of the fitted Gompertz and von Bertalanffy models for male and female Guzerá cattle, respectively. Four production regions in Northeast Brazil were included in the models as a fixed effect, and the animals were included as a random effect. In addition, the coefficients of the growth models in the production regions were compared. The accuracy of the fit equations was assessed with the Akaike information criterion, Bayesian information criterion, mean absolute deviation, mean squared error, and coefficient of determination. Confidence intervals were used for comparing the production regions. The Guzerá males in the Gado-Algodão and Serra Geral da Bahia production regions were statistically equal in asymptotic weight, and the animals in the Itapetinga-Valadares and Mata-Agreste regions had equivalent maturity rates. The Guzerá females in the Itapetinga-Valadares and Serra Geral da Bahia regions had the same asymptotic weight. The maturity rates in Itapetinga-Valadares were equal to those estimated for Mata-Agreste and Serra Geral da Bahia. The inclusion of the fixed effect of the production region and the random effect of the animals in the models improved the fit quality and increased the possibility of generating growth curves for each region.

The objective of this study was to evaluate the morphological and physiological changes in paricá plants (Schizolobium parahyba var. amazonicum) intoxicated by glyphosate. The experiment was conducted in a protected environment using paricá plants during their planting stage, which were intoxicated with increasing doses of glyphosate: 0 (control); 43.2; 86.2; 129.6 and 172.8 g.ha^-1. At 7 and 21 days after the application of the herbicide, the photosynthesis, transpiration, stomatal conductance and leaf temperature were measured. The visual intoxication degree and the growth of the shoot and the root of the plants were evaluated 21 days after the application. Paricá shows symptoms of visual intoxication characterized by chlorosis/winding, evolving to necrosis/abscission of the youngest leaflets. The growth of the stem and the roots of the intoxicated plants is preserved; however, an expressive leaf loss occurs, and paricá may have adaptation mechanisms to tolerate the action of the herbicide molecule. The photosynthesis decrease promoted by an indirect action of glyphosate represents the main reduction on the growth of plants. The decrease on the stomatal conductance, which was the most sensitive physiological variable to glyphosate, resulted in lower transpiration rates, which, consequently, caused increases on the leaf temperature.

The objective of this work was to define experimental blocks for sugarcane experiments using geostatistical techniques, principal component analysis, and clustering techniques applied to soil properties. For this, data of soil chemical properties from a sugarcane experiment were used. Geostatistical techniques were applied to identify the spatial variability of these properties and to estimate the values for non-sampled locations through kriging. The principal components analysis was used for dimensional reduction, and, with the new variables obtained, the cluster analysis was performed using the k-means method to determine the experimental blocks with two to five replicates. Of the 12 analyzed variables, 10 showed spatial dependence. The principal component analysis allowed reducing the dimensionality of the data to two variables, which explained 82.27% of total variance. The obtained blocks presented irregular polygonal shapes, with different formats and sizes, and some of them showed discontinuities. The proposed methodology has the potential to identify more uniform areas in terms of soil chemical properties to allocate experimental blocks for sugarcane.

The aim of this study was to evaluate the growth of the hybrid clone Eucalyptus grandis × Eucalyptus urophylla submitted to competition with weeds and determine the period prior to economic loss (PPEL). The experiment was carried out in Ulianópolis, Pará State, Brazil, and consisted of the treatments continuous control and no control of weeds. Weed management was carried out by integrating both mechanical and chemical control. Stem base diameter, height, canopy diameter of eucalyptus plants were measured on the 16th month after planting. Wood volume was estimated by means of a volumetric equation. The treatments continuous control and no control of weeds were compared using the Hotelling’s T2 test and the parameters for PPEL calculation were defined from volume estimation. The treatment continuous control promoted significant gains in eucalyptus growth. PPEL tended to be reduced by 3.8287 and 0.2393 units with the increase of a unit in the price of wood and the increase of planting yield, respectively. For different eucalyptus wood prices, the calculated PPEL ranged from 40 to 161 days of coexistence with weeds.

Modeling animal growth is essential to manage quality meat production systems at a low cost. This study aimed to compare the linear-linear, linear-plateau, and linear-linear-linear spline functions with the nonlinear models Brody, Richards, and von Bertalanffy to model the growth of crossbred sheep in the Northeast of Brazil. Weighing data from the genetic groups of meat sheep Dorper x Morada Nova, Dorper x Rabo Largo, and Dorper x Santa Inês were used. Knots in the spline fitting were considered unknown and estimated under the segmented nonlinear regression approach. Overall, splines were more accurate than traditional nonlinear models in describing the growth of sheep of all genetic groups. The linear-plateau spline was superior in predicting weight as a function of the age of sheep. The linear-plateau function also resulted in estimates of parameters (growth rates, time for animals to reach adult weight, and adult weight) with easier biological interpretations, which can be used in practice for decision-making for herd management.