One of the main diseases occurring in clonal nurseries of Eucalyptus spp. is powdery mildew caused by the fungus Oidium eucalypti. This work evaluated the efficiency of biological products based on Trichoderma spp. and Bacillus spp. applied as preventive and curative treatments for the control of Oidium eucalypti in clonal seedlings of E. benthamii Maiden et Cambage. Treatments were: Trichoderma harzianum (THP), T. atroviride (TAI), T. harzianum (THE), Trichoderma spp. (TTA), Bacillus spp. (BNE), Sulfur (KUM), Difenoconazol (SCO) and distilled water (AD). Treatments were applied preventively by spraying seven days before inoculation of the pathogen, and in curatively, ten days after inoculation. Weekly evaluations of the incidence and severity of the disease were done. The analyzed variables were: Disease Index (ID) and Incidence (I), calculating the area under the disease curve (AUDPC) for each treatment. The results pointed BNE (Bacillus spp.) and TAI (isolate T. atroviride) as effective preventive treatments and BNE (Bacillus spp.), applied curatively for the control of O. eucalypti in E. benthamii seedlings, proving that treatments based on biological products may be effective for controlling eucalyptus powdery mildew in clonal nurseries.

The use of a standard area diagram (SAD) set for bacterial blight is a way to obtain greater objectivity (reliability, precision, and accuracy) in disease assessment on eucalyptus trees under field conditions. Besides, assessments using SADs are fast and do not require equipment because they allow for raters’ training (^{BOCK et al., 2010}; ²⁰¹⁶; ^{ARAÚJO et al., 2019}). The rapid quantification of the severity of bacterial blight is essential to select elite disease-resistant genotypes in field research. This is because the disease can manifest itself on eucalyptus trees up to 2 years old (^{COUTINHO et al., 2011}), under field conditions. In this context, the development and validation of a SAD set are reported to estimate the severity of bacterial blight on eucalyptus trees.

A dormência e a presença de microrganismos são importantes fatores que podem reduzir o vigor germinativo de sementes de Acacia mearnsii. A presença de fungos e bactérias junto às sementes empregadas em testes de laboratório podem fornecer explantes contaminados quando utilizados nas culturas in vitro. Assim, os objetivos do presente estudo foram determinar uma metodologia adequada para a quebra de dormência de sementes da acácia-negra e indicar um método eficiente para desinfestação das sementes. Sementes de acácia negra foram autoclavadas durante diferentes períodos: 5, 10, 15, 20, 25 e 30 minutos. As testemunhas usadas sofreram quebra de dormência com água quente (800C) por três minutos, e foram tratadas com: fungicida Benomyl, produto comercial Hipoclorito de sodio e/ou álcool a 70%. O ensaio foi conduzido em sala de incubação com temperatura de 250C (± 3) e fotoperíodo de 12 horas de luz fluorescente. Os resultados mostraram que a autoclavagem das sementes durante 20 e 25 minutos foram suficientes para quebrar a dormência e simultaneamente, promover a desinfestação de sementes de acácia-negra. Períodos de autoclavagem inferiores a 20 minutos, não foram eficientes na desinfestação de sementes de acácia-negra, embora tivessem propiciado elevados percentuais de germinação. A exposição de sementes à autoclavagem, por 30 minutos, promoveu a desinfestação das sementes, porém levou o embrião à morte.

Accurate and low-cost tree inventories in forest plantations are essential for an effective production management. Stimulated by recent advancements in Unmanned Aerial Vehicle (UAV) imagery coupled with artificial intelligence, and by the interest in developing models capable of supporting decision-making on silvicultural and forest management, this study aimed to evaluate the performance of different vegetation indices in detecting Eucaliptus saligna individuals by using an improved deep learning model. The tree-individual detection model was created using the YOLOv8n algorithm using UAV RGB images and vegetation indices (VI) generated from the multispectral sensor onboard the UAV. Nine VIs were selected for training (65%) and testing (35%) the models. The proposed framework demonstrated that the MPRI, PSRI, and NDVI indices achieved an F1 score of 0.98 and a precision of 0.97 for detecting E. saligna individual trees six months after planting. Our study demonstrates the robustness of the proposed framework and recommends the application of the MPRI index in individual tree detection due to its efficient performance, cost-effectiveness, and simplicity, as it only utilizes regions of the visible spectrum.

This study reports the first occurrence of Spodoptera cosmioides (Walker, 1858) (Lepidoptera: Noctuidae) larvae causing defoliation in transplanted seedlings in a clonal plantation of Eucalyptus urophylla S.T. Blake (Myrtaceae), in Butiá municipality, Rio Grande do Sul State (30°9’45” S; 51°59’42” W). The S. cosmioides caterpillars are polyphagous, including eucalyptus among their host plants. It was observed that the caterpillar infestation damaged 80% of the seedlings, while the defoliation varied from 13% to 24% per plant. This is the first record of S. cosmioides caterpillars causing injuries in a new plantation of E. urophylla.