DSpace Communidade: Embrapa Agroenergia (CNPAE)Embrapa Agroenergia (CNPAE)https://www.alice.cnptia.embrapa.br/alice/handle/item/412026-05-14T00:42:57Z2026-05-14T00:42:57ZVisualizando a difratometria.VALADARES, L. F.VALADARES, N. F.https://www.alice.cnptia.embrapa.br/alice/handle/doc/11868242026-05-13T17:48:44Z2026-01-01T00:00:00ZTítulo: Visualizando a difratometria.
Autoria: VALADARES, L. F.; VALADARES, N. F.
Conteúdo: This classroom-oriented study goes beyond simple visualization by directly comparing laser diffractometry and light microscopy measurements to quantify micron-scale spacings in commercial CDs/DVDs (compact disc/digital versatile disc) and electron-microscopy grids. Diffraction angles from reflection (CD/DVD) and transmission (grids) patterns were captured using a digital camera. We systematically validate the diffractometry results with microscopy, teaching the scientific principle of cross-validation. Furthermore, by employing grids with square, rectangular, and hexagonal symmetries, we provide a tangible introduction to symmetry and reciprocal space, demonstrating the inverse relationship between grating spacing and diffraction pattern scale. Designed for educational settings, these experiments use affordable materials to teach core principles of diffraction with applications in material science and chemistry.2026-01-01T00:00:00ZDeep learning and aerial imagery for macaúba palm identificationSANTOS, W. R. dosFAVARO, S. P.CORDÃO, M. A.SANO, E. E.CARDOSO, A. N.https://www.alice.cnptia.embrapa.br/alice/handle/doc/11867182026-05-09T15:18:52Z2026-01-01T00:00:00ZTítulo: Deep learning and aerial imagery for macaúba palm identification
Autoria: SANTOS, W. R. dos; FAVARO, S. P.; CORDÃO, M. A.; SANO, E. E.; CARDOSO, A. N.
Conteúdo: The objective of this work was to use deep learning and images taken by unmanned aerial vehicles to develop a model to identify the occurrence of macaúba (Acrocomia intumescens) palm trees. The model was trained and tested using data from areas in the southern region of the state of Ceará, Brazil. Later, the tested model was evaluated using data from areas in the Midwestern region of the country. The primary challenge was to distinguish macaúba from other native palm trees, such as babassu (Attalea speciosa). Babassu has spectral similarities and a random distribution, which makes it difficult to identify. Red-green-blue mosaics were cropped into smaller size images and processed using a convolutional neural network deep-learning technique. Identification performance was evaluated using metrics of accuracy, precision, recall, and F1-score. In an area of 1,000 ha, 3,679 macaúba palm trees and 12,410 babassu palm trees were identified, achieving a 93% accuracy. The proposed approach was evaluated in a 4.0 ha site located in the municipality of Batayporã, in the southern region of the state of Mato Grosso do Sul, with an 89% accuracy. The model was able to identify macaúba palm trees occurring in natural areas in the Semiarid and in Midwestern regions of Brazil.2026-01-01T00:00:00ZConserved transcriptional responses to salt and water stress in oil palm (Elaeis guineensis Jacq.) leaf tissues.SALGADO, F. F.SILVA, T. L. C. daLEAO, A. P.TOGAWA, R. C.SOUSA, C. A. F. deGRYNBERG, P.SOUZA JUNIOR, M. T.https://www.alice.cnptia.embrapa.br/alice/handle/doc/11862052026-04-12T01:35:53Z2026-01-01T00:00:00ZTítulo: Conserved transcriptional responses to salt and water stress in oil palm (Elaeis guineensis Jacq.) leaf tissues.
Autoria: SALGADO, F. F.; SILVA, T. L. C. da; LEAO, A. P.; TOGAWA, R. C.; SOUSA, C. A. F. de; GRYNBERG, P.; SOUZA JUNIOR, M. T.
Conteúdo: Abiotic stresses negatively impact oil palm (Elaeis guineensis Jacq.) cultivation. Transcription factors (TFs) are essential proteins regulating gene expression in plants. While numerous TF gene families are implicated in plant responses to abiotic stress, their specific roles in oil palm’s drought and salinity responses remain largely unexplored. This study aimed to get insights into the TFs’ involvement in the oil palm’s response to these stresses.2026-01-01T00:00:00ZEngenharia genética para aumento da tolerância a inibidores de hidrolisados lignocelulósicos em Komagataella phaffii.BRANDALISE, E. F.DUARTE, L. T.ALMEIDA, J. R. M. dehttps://www.alice.cnptia.embrapa.br/alice/handle/doc/11861762026-04-12T01:35:27Z2025-01-01T00:00:00ZTítulo: Engenharia genética para aumento da tolerância a inibidores de hidrolisados lignocelulósicos em Komagataella phaffii.
Autoria: BRANDALISE, E. F.; DUARTE, L. T.; ALMEIDA, J. R. M. de
Conteúdo: Os carboidratos presentes na biomassa lignocelulósica podem ser usados como fonte de carbono por microrganismos para produzir produtos químicos renováveis. Os processos de pré-tratamento e hidrólise da biomassa levam a liberação de açúcares, mas também acarretam na formação e liberação de compostos que inibem o metabolismo microbiano, incluindo furfural, 5-hidroxi-metil-furfural (HMF) e ácido acético. Neste contexto, o objetivo deste trabalho foi validar genes potencialmente envolvidos na resposta da levedura K. phaffii à estes inibidores e obter cepas com maior tolerância a hidrolisados lignocelulósicos.2025-01-01T00:00:00Z