75 resultados para characteristic variety
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Increasing water scarcity and depleted water productivity in irrigated soils are inducing farmers to adopt improved varieties, such as those with high-capacity tolerance. The use of tolerant varieties of sugarcane might substantially avoid the decline of productivity under water deficit. This research aimed to evaluate the harmful effects of drought on the physiology of two sugarcane varieties (RB867515 and RB962962) during the initial development. Young plants were subjected to irrigation suspension until total stomata closure, and then rewatered. Significant reduction on stomatal conductance, transpiration, and net photosynthesis were observed. RB867515 showed a faster stomatal closure while RB962962 slowed the effects of drought on the gas exchanges parameters with a faster recovering after rewatering. Accumulation of carbohydrates, amino acids, proline, and protein in the leaves and roots of the stressed plants occurred in both varieties, substantially linked to reduction of the leaf water potential. Due to the severity of stress, this accumulation was not enough to maintain the cell turgor pressure, so relative water content was diminished. Water stress affected the contents of chlorophyll (a, b, and total) in both varieties, but not the levels of carotenoids. There was a significant reduction in dry matter under stress. In conclusion, RB962962 variety endured stressed conditions more than RB867515, since it slowed down the damaging effects of drought on the gas exchanges. In addition, RB962962 presented a faster recovery than RB867515, a feature that qualifies it as a variety capable of enduring short periods of drought without major losses in the initial stage of its development.
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The effects of aluminum (Al) on the activities of antioxidant enzymes and ferritin expression were studied in cell suspension cultures of two varieties of Coffea arabica, Mundo Novo and Icatu, in medium with pH at 5.8. The cells were incubated with 300 µM Al3+, and the Al speciation as Al3+ was 1.45% of the mole fraction. The activities of superoxide dismutase (SOD), catalase (CAT), and glutathione S-transferase (GST) were increased in Mundo Novo, whereas glutathione reductase (GR) and guaiacol peroxidase (GPOX) activities remained unchanged. SOD, GR, and GST activities were increased in Icatu, while CAT activity was not changed, and GPOX activity decreased. The expression of two ferritin genes (CaFer1 and CaFer2) were analyzed by Real-Time PCR. Al caused a downregulation of CaFER1 expression and no changes of CaFER2 expression in both varieties. The Western blot showed no alteration in ferritin protein levels in Mundo Novo and a decrease in Icatu. The differential enzymes responses indicate that the response to Al is variety-dependent.
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PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas. Faculdade de Educação Física
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Universidade Estadual de Campinas. Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas. Faculdade de Educação Física
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Universidade Estadual de Campinas. Faculdade de Educação Física
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Universidade Estadual de Campinas. Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas. Faculdade de Educação Física