997 resultados para Pre-imbibition


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The effect of osmoconditioning and controlled water sowing was analysed in seeds of Phaseolus vulgaris L. cv. carioca on germination under water stress conditions. The pre-sowing in water at low temperature to limit germination resulted in the increase in the tolerance to water stress. The osmoconditioning with PEG for 48 hours increased the tolerance of bean seeds to water stress of -0.51MPa. The osmoconditioning or controlled water sowing can be used as a practice to increase the tolerance of bean seeds to water stress before planting in the field.

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The electrical conductivity of leachates from imbibing seeds has been used as a vigor test for several species. The adaptation of this methodology to different species requires knowledge on the leaching kinetics of electrolytes. For Brazilwood seeds, the classic method was not satisfactory and rapid tests are essential because they have low storage capacity at room temperature. Leaching kinetics during seed imbibition is a function of physiological quality, presence or absence of seed coat, imbibing temperature and the initial moisture content of seed. In this study, the electrolyte leaching rate of six different categories of seeds, from two regions, was evaluated in seeds with and without seed coat and incubated with different moisture contents and at different temperatures. The results showed that the electrolyte leaching rate in Brazilwood seeds is independent of the physiological quality, the presence or absence of seed coat and imbibition temperature, but these factors changed the total amount of electrolytes leached. The leaching rate increased in the first few minutes of imbibition, suggesting that the adjustment of the methodology must consider the reduction in imbibition time, reduction in temperature, use of a controlled and slower pre-imbibition, and replacement of the imbibition solution after the first few minutes.

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Passiflora seeds germinate erratically presenting difficulties for their handling in a greenhouse. The effect of removing of basal point of seeds (RB) and pre-imbibition of seeds of sweet granadilla and yellow passion fruit in 50, 100, 200, and 400 mg mL-1 solutions of gibberellic acid (GA3) or 0.1% KNO3 solution was studied. The experiment was conducted in greenhouses in La Plata, Colombia. Two accessions PrJ1 and PrJ2 of sweet granadilla were evaluated. There were calculated the final percentage of germination (PG), mean germination time (MGT), and the mean germination rate (MGR). The leaf area and dry mass of seedlings were measured 22 days after sowing (das); with this data, specific leaf area and relation root/shoot were calculated. In all cases, the highest germination percentages were achieved treating seeds with KNO3 (89, 92, and 87% for yellow passion fruit, PrJ2, and PrJ1, respectively), but the increase in MGR (3.3 germinated seeds per day) and the decrease in MGT (16 days) were only significant for PrJ1. RB had a significant reduction of PG in all cases (28, 12, and 33% for passion fruit, PrJ2 and PrJ1, respectively). With the increase in the concentration of GA3, PG was reduced for two accessions of sweet granadilla, for yellow passion fruit this trend was not clear, no treatment with GA3 showed significant differences with the control. Leaf area (24.07 cm2) and dry mass of seedlings (135 mg) were significantly higher than seeds previously treated with KNO3 only for PrJ1.The solution of KNO3 0,1% is recommended to improve the germination and initial growth of granadilla seedlings.

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The difficulty on identifying, lack of segregation systems and absence of suitable standards for coexistence of non trangenic and transgenic soybean are contributing for contaminations that occur during productive system. The objective of this study was to evaluate the efficiency of two methods for detecting mixtures of seeds genetically modified (GM) into samples of non-GM soybean, in a way that seed lots can be assessed within the standards established by seed legislation. Two sizes of soybean samples (200 and 400 seeds), cv. BRSMG 810C (non-GM) and BRSMG 850GRR (GM), were assessed with four contamination levels (addition of GM seeds, for obtaining 0.0%, 0.5%, 1.0%, and 1.5% contamination), and two detection methods: immunoassay of lateral flux (ILF) and bioassay (pre-imbibition into 0.6% herbicide solution; 25 ºC; 16 h). The bioassay is efficient in detecting presence of GM seeds in seed samples of non-GM soybean, even for contamination lower than 1.0%, provided that seeds have high physiological quality. The ILF was positive, detecting the presence of target protein in contaminated samples, indicating test effectiveness. There was significant correlation between the two detection methods (r = 0.82; p < 0.0001). Sample size did not influence efficiency of the two methods in detecting presence of GM seeds.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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In this paper, absolute water permeability is estimated from capillary imbibition and pore structure for 15 sedimentary rock types. They present a wide range of petrographic characteristics that provide degrees of connectivity, porosities, pore size distributions, water absorption coefficients by capillarity and water permeabilities. A statistical analysis shows strong correlations among the petrophysical parameters of the studied rocks. Several fundamental properties are fitted into different linear and multiple expressions where water permeability is expressed as a generalized function of the properties. Some practical aspects of these correlations are highlighted in order to use capillary imbibition tests to estimate permeability. The permeability–porosity relation is discussed in the context of the influence of pore connectivity and wettability. As a consequence, we propose a generalized model for permeability that includes information about water fluid rate (water absorption coefficient by capillarity), water properties (density and viscosity), wetting (interfacial tension and contact angle) and pore structure (pore radius and porosity). Its application is examined in terms of the type of pores that contribute to water transport and wettability. The results indicate that the threshold pore radius, in which water percolates through rock, achieves the best description of the pore system. The proposed equation is compared against Carman–Kozeny's and Katz–Thompson's equations. The proposed equation achieves very accurate predictions of the water permeability in the range of 0.01 to 1000 mD.

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To identify risk factors associated with post-operative temporomandibular joint dysfunction after craniotomy. The study sample included 24 patients, mean age of 37.3 ± 10 years; eligible for surgery for refractory epilepsy, evaluated according to RDC/TMD before and after surgery. The primary predictor was the time after the surgery. The primary outcome variable was maximal mouth opening. Other outcome variables were: disc displacement, bruxism, TMJ sound, TMJ pain, and pain associated to mandibular movements. Data analyses were performed using bivariate and multiple regression methods. The maximal mouth opening was significantly reduced after surgery in all patients (p = 0.03). In the multiple regression model, time of evaluation and pre-operative bruxism were significantly (p < .05) associated with an increased risk for TMD post-surgery. A significant correlation between surgery follow-up time and maximal opening mouth was found. Pre-operative bruxism was associated with increased risk for temporomandibular joint dysfunction after craniotomy.

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To analyze the relationship between parity, pre-pregnancy body mass index (BMI), and gestational weight gain (GWG). This observational controlled study was conducted from November 2013 to April 2014, with postpartum women who started antenatal care up to 14 weeks and had full-term births. Data were collected from medical records and antenatal cards. Descriptive and bivariate analyses were performed. The significance level was 5%. Data were collected from 130 primiparous and 160 multiparous women. At the beginning of prenatal care, 54.62% of the primiparous were eutrophic, while the majority of multiparous were overweight or obese (62.51%). Multiparas are two times more likely to be obese at the beginning of their pregnancies, when compared to primiparas. The average pre-pregnancy weight and final pregnancy weight was significantly higher in multiparous, however, the mean GWG was higher among primiparous. We found an inverse correlation between parity and the total GWG, but initial BMI was significantly higher in multiparas. Nevertheless, monitoring of the GWG through actions that promote a healthier lifestyle is needed, regardless of parity and nutritional status, in order to prevent excessive GWG and postpartum weight retention and consequently inadequate pre-pregnancy nutritional status in future pregnancies.

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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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Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.