Considerando a crescente demanda por mudas florestais e a escassez de matérias-primas dos substratos utilizados para o crescimento das plantas, faz-se necessário avaliar novos componentes e formulações que assegurem a qualidade das mudas. Nesse experimento foram estudados o desenvolvimento e a qualidade de mudas clonais de Eucalyptus urophylla x E. grandis, provenientes de miniestacas, em função de nove composições de substrato produzidos a partir de vermiculita granulometria fina, casca de arroz carbonizada e fibra de coco em tubetes de 50 mL. Foram avaliados as propriedades físicas dos substratos, o desenvolvimento morfológico e a qualidade do sistema radicular das mudas, aos 90 dias após o estaqueamento. Os substratos com maior porosidade total promovem maior qualidade do sistema radicular o que, consequentemente, resulta em mudas com maior diâmetro, massa seca aérea e radicular e Índice de Qualidade de Dickson. Outros valores para as características físicas dos substratos, diferentes dos citados na literatura, também podem ser considerados adequados.

The correct capture of forest operations information carried out in forest plantations can help in the management of mechanized harvesting timber. Proper management must be able to dimension resources and tools necessary for the fulfillment of operations and helping in strategic, tactical, and operational planning. In order to facilitate the decision making of forest managers, this work aimed to analyze the performance of machine learning algorithms in estimating the productivity of timber harvesters. As predictors of productivity, we used the availability of hours of machine use, individual mean volumes of trees, and terrain slopes. The dataset was composed of 144,973 records, carried out over a period of 28 months. We tested the predictive performance of 24 machine learning algorithms in default mode. In addition, we tested the performance of blending and stacking joint learning methods. We evaluated the model’s fit using the root mean squared error, mean absolute error, mean absolute percentage error, and determination coefficient. After cleaning the initial database, we used only 1.12% to build the model. Learning by blending ensemble stood out with a determination coefficient of 0.71 and a mean absolute percentage error of 15%. From the use of data from machine learning algorithms, it became possible to predict the productivity of timber harvesters. Testing a variety of machine learning algorithms with different dynamics contributed to the machine learning technique that helped us reach our goal: maximizing the model’s performance by conducting experimentation.

Http://dx.doi.org/10.5902/198050985082Os componentes utilizados na produção de substratos influem diretamente no ciclo vegetativo, na qualidade e consequentemente nos custos de produção das mudas. Nesse experimento estudou-se o desenvolvimento, qualidade e custos de produção de mudas de Eucalyptus grandis Hill ex Maiden × Eucalyptus urophylla S. T. Blake, por meio de propagação sexuada, utilizando 12 composições de substrato. A análise dos resultados evidenciou que os substratos puros, a exceção da fibra de coco, não apresentaram características físicas adequadas para a produção de mudas, via sexuada, de Eucalyptus grandis Hill ex Maiden × Eucalyptus urophylla S. T. Blake em tubetes. Os melhores resultados foram obtidos nos substratos com mistura 1:1 de casca de arroz carbonizada e fibra de coco e na mistura 1:1 de vermiculita e fibra de coco, devido às melhores características morfológicas apresentadas e da possibilidade de redução do tempo de produção, levando à redução no custo final das mudas.

Http://dx.doi.org/10.5902/1980509815742A racionalização da colheita florestal e a minimização dos custos é uma busca constante por parte dos gestores envolvidos nesse processo, competindo a esses deliberar práticas economicamente viáveis para otimizar essa operação. O objetivo deste estudo foi avaliar técnica e economicamente a produtividade do feller-buncher e do processador florestal em povoamento de eucalipto em primeiro corte. A análise técnica englobou um estudo de tempos e movimentos, produtividade, eficiência operacional e disponibilidade mecânica. A análise econômica englobou os parâmetros do custo operacional, custo de colheita florestal e rendimento energético. Visando à otimização do custo de colheita florestal, o sistema composto pelo feller-buncher e processador florestal apresenta-se como uma alternativa viável tecnicamente e economicamente para a colheita em povoamentos de eucalipto de primeiro corte ou para povoamentos que não possuam árvores bifurcadas.

Forest road construction projects mainly depend on factors related to terrain physiography, watershed, and wood harvesting. In the whole tree system, wood extraction is the activity most impacted by the density of forest roads, influencing the extraction distance. One of the alternatives is the optimal forest road density approach, which allows for the minimization of wood extraction costs and the optimization of the productive area. Given the above, the objective of this study was to analyze whether the optimal forest road density in areas of forests planted with eucalyptus allows for maximum productivity and the lowest cost of the road-wood extraction binomial in a whole tree system. The technical and economic analysis of wood extraction was based on the study of time, operational efficiency, productivity, and the cost of wood extraction with a grapple skidder. For the optimal forest road density, the cost of the wood extraction activity was considered, as well as the cost of construction, reconstruction, and maintenance of roads. In addition, the cost of a loss of productive area and the cost of excess forest roads were weighted. The optimal forest road density was 30.49 m ha⁻¹ for an average extraction distance of 81.99 m, with the cost of loss of productive area of 0.49 USD m³ and the excess road of 80.19 m, which represented a cost of 978.31 USD ha⁻¹. It is concluded that the optimal forest road density allows for the identification of excess forest roads, allowing for a reduction in the total cost for the implementation of roads. Therefore, it can be considered an essential variable in the planning of the forest road network, providing improvements in productivity and the costs of wood extraction with a grapple skidder.

In mechanized harvesting of wood operations, in a cut-to-length system, occupational noise is emitted by self-propelled forest machines, which compromises the safety and health of operators. Therefore, the occupational noise levels emitted by self-propelled forestry machines, in a cut-to-length system, were investigated to determine which are in line with current Brazilian legislation. The noise levels issued by 22 self-propelled forestry machines in the mechanized harvesting of wood operations, in Eucalyptus and Pinus planted forests, were collected during a full day of measurement. Taking into account the operations performed and the type of planted forest, homogeneous groups of operators were formed. Based on Regulatory Norms N.9 and N.15 adopted for labor purposes in Brazil, occupational noise levels were analyzed. In relation to harvester operators, 36.4% were exposed to values above the exposure limit of 85 dB (A) and 63.6% to the action level of 80 dB (A). Regarding the forwarder operators, 100% were exposed to values that exceeded the action level. For the analyzed conditions, for the cut-to-length system employed in harvesting wood in forest planted with Eucalyptus and Pinus, the occupational noise levels of the self-propelled forest machines are not in line with current Brazilian legislation for labor purposes.