Embrapa Agroenergia (CNPAE) https://www.alice.cnptia.embrapa.br/alice/handle/item/41 2026-06-03T22:13:04Z 2026-06-03T22:13:04Z BERGMANN, J. C. LACERDA, V. A. M. ALENCAR, K. L. C. FAVARO, L. C. de L. RODRIGUES, D. de S. MARINS, L. F. QUIRINO, B. F. https://www.alice.cnptia.embrapa.br/alice/handle/doc/1187279 2026-06-01T15:48:38Z 2026-01-01T00:00:00Z

Título: A new GH3 B-Glucosidase from Chryseobacterium sp. with applications in cellulosic ethanol production and agri-biotechnological processes. Autoria: BERGMANN, J. C.; LACERDA, V. A. M.; ALENCAR, K. L. C.; FAVARO, L. C. de L.; RODRIGUES, D. de S.; MARINS, L. F.; QUIRINO, B. F. Conteúdo: Abstract: β-Glucosidases catalyze the hydrolysis of β-glycosidic bonds and play key roles in biomass conversion and glycoside processing. We report the identification and characterization of Cr_B1, a GH3 β-glucosidase from Chryseobacterium sp. containing a predicted signal peptide. Cr_B1 hydrolyzed pNPG, cellobiose, salicin, and daidzin, showing optimal activity at pH 5.0−5.5 and 45−55 °C. The enzyme retained over 90% activity after 190 days at 4°C and 25 °C and above 80% activity after 24 h at 50 °C, indicating remarkable long-term and thermal stability. Cr_B1 exhibited high glucose tolerance (IC50: 1.5−1.8 M) and substrate-dependent kinetics. In synergy with Celluclast, it increased glucose release from CMC by 69%, demonstrating its potential to enhance enzymatic saccharification. These properties highlight Cr_B1 as a promising biocatalyst for improving saccharification, enhancing isoflavone bioavailability, and reducing bitterness in food and feed applications.

2026-01-01T00:00:00Z SOUZA, A. P. R. de PASQUINI, D. VAZ JUNIOR, S. https://www.alice.cnptia.embrapa.br/alice/handle/doc/1187275 2026-06-01T14:48:47Z 2025-01-01T00:00:00Z

Título: Obtenção, caracterização e avaliação de membranas poliméricas à base de lignina e amido termoplástico para separação de CO2. Autoria: SOUZA, A. P. R. de; PASQUINI, D.; VAZ JUNIOR, S. Conteúdo: Resumo: A tecnologia de separação de gases através de membranas se mostra promissora diante da sua processabilidade e aplicação. Esse trabalho tem como objetivo obter e caracterizar membranas poliméricas renováveis (MPR) para separação de dióxido de carbono (CO2). A metodologia consiste em duas etapas: 1) oxipropilação de ligninas e 2) obtenção de MPR a partir da adição de amido termoplástico (ATP). FTIR, TGA e MEV foram realizadas nas MPR. Dióxido de titânio (TiO2) foi adicionado ao material visando a otimização dos parâmetros de permeação. As MPR sem TiO2 não se mostraram favoráveis à permeação de nitrogênio (N2) e CO2, enquanto as MPR com TiO2 apresentaram resultados promissores para a permeação de CO2. Diante disso, a utilização de TiO2 se faz essencial na composição das MPR.

2025-01-01T00:00:00Z VALADARES, L. F. VALADARES, N. F. https://www.alice.cnptia.embrapa.br/alice/handle/doc/1186824 2026-05-17T22:09:55Z 2026-01-01T00:00:00Z

Título: 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.

2026-01-01T00:00:00Z SANTOS, W. R. dos FAVARO, S. P. CORDÃO, M. A. SANO, E. E. CARDOSO, A. N. https://www.alice.cnptia.embrapa.br/alice/handle/doc/1186718 2026-05-09T15:18:52Z 2026-01-01T00:00:00Z

Título: 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.

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