https://www.alice.cnptia.embrapa.br/alice/handle/item/394 Artigo em periódico indexado (CNPAE) Fri, 12 Jun 2026 04:09:28 GMT 2026-06-12T04:09:28Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1187414 Título: Enhancing wheat bran deconstruction with enzyme cocktails from Penicillium spp. and Trichoderma harzianum: the impact of β-glucosidase supplementation. Autoria: HAMANN, P. R. V.; MARTINS, H. S.; COSTA, P. H. C. da; BRITO, D. T. de A.; SILVA, V. R. C. da; TAVARES, Y. F.; QUIRINO, B. F.; NORONHA, E. F. Conteúdo: Abstract: Forests and natural environments are valuable sources of organisms capable of degrading plant cell wall carbohydrates. In the present study, two isolates, Penicillium polonicum and Penicillium chrysogenum, obtained from Brazilian Cerrado soil, along with a previously characterized isolate of Trichoderma harzianum, were evaluated for their ability to produce carbohydrate-active enzymes when grown in the presence of wheat bran. P. chrysogenum exhibited higher production of endoglucanases, xylanases, and pectinases. Biochemical characterization showed that most enzymes were active at pH 5 and within a temperature range of 30–50 °C, with the exception of P. chrysogenum endoglucanases, which displayed optimal activity at 60 °C. Hydrolysis of cellulose and carboxymethyl cellulose by the three enzyme sources demonstrated that supplementation with recombinant β-glucosidase from Clostridium thermocellum (BglA) significantly enhanced reducing sugar release; specifically, when applied to P. chrysogenum, the reducing sugar yield from cellulose hydrolysis increased by 2.53-fold. In the hydrolysis of wheat bran, enzymes from P. chrysogenum and T. harzianum supplemented with BglA resulted in a 1.6- and 3.93-fold increase in D-glucose yield, respectively. The results presented in this study contribute to the development of more robust enzyme cocktails for wheat bran valorization. Thu, 01 Jan 2026 00:00:00 GMT https://www.alice.cnptia.embrapa.br/alice/handle/doc/1187414 2026-01-01T00:00:00Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1187279 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. Thu, 01 Jan 2026 00:00:00 GMT https://www.alice.cnptia.embrapa.br/alice/handle/doc/1187279 2026-01-01T00:00:00Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1186824 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. Thu, 01 Jan 2026 00:00:00 GMT https://www.alice.cnptia.embrapa.br/alice/handle/doc/1186824 2026-01-01T00:00:00Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1186718 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. Thu, 01 Jan 2026 00:00:00 GMT https://www.alice.cnptia.embrapa.br/alice/handle/doc/1186718 2026-01-01T00:00:00Z