85 resultados para Variables from CGTMSE
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The purpose of this study was to investigate the genotypes of Giardia lamblia from human and animal feces and their epidemiological and clinical characteristics in Argentina, South America. Seventy isolates, 60 from humans (adults and children), eight from dogs and two from cows were processed by polymerase chain reaction-restriction fragment length polymorphism. Data corresponding to demographic, socio-cultural and environmental variables and presence/absence of signs/symptoms were collected. The triosephosphate isomerase gene was amplified from 43 (71.66%) of the 60 human fecal samples. Among these, 3/43 (6.98%) were genotype AII and 40/43 (93.02%) were genotype B. Assemblage AII was detected in three children who lived together in a shantytown and they were oligosymptomatic and none had diarrhea. This genotype was not found in animals. Genotype B showed a high prevalence in both adults and children. It was also found in polysymptomatic people, many of whom presented diarrhea. It was also found only in one dog. The present study represents the first contribution to the knowledge of G. lamblia genotypes in Argentina.
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Mosquito community composition in dynamic landscapes from the Atlantic Forest biome (Diptera, Culicidae). Considering that some species of Culicidae are vectors of pathogens, both the knowledge of the diversity of the mosquito fauna and how some environment factors influence in it, are important subjects. In order to address the composition of Culicidae species in a forest reserve in southern Atlantic Forest, we compared biotic and abiotic environmental determinants and how they were associated with the occurrence of species between sunset and sunrise. The level of conservation of the area was also considered. The investigation was carried out at Reserva Natural do Morro da Mina, in Antonina, state of Paraná, Brazil. We performed sixteen mosquito collections employing Shannon traps at three-hour intervals, from July 2008 to June 2009. The characterization of the area was determined using ecological indices of diversity, evenness, dominance and similarity. We compared the frequency of specimens with abiotic variables, i.e., temperature, relative humidity and pluviosity. Seven thousand four hundred ten mosquito females were captured. They belong to 48 species of 12 genera. The most abundant genera were Anopheles, Culex, Coquillettidia, Aedes and Runchomyia. Among the species, the most abundant was Anopheles cruzii, the primary vector of Plasmodium spp. in the Atlantic Forest. Results of the analyses showed that the abiotic variables we tested did not influence the occurrence of species, although certain values suggested that there was an optimum range for the occurrence of culicid species. It was possible to detect the presence of species of Culicidae with different epidemiologic profiles and habitat preference.
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Nitrous oxide (N2O) is the most important non-CO2 greenhouse gas and soil management systems should be evaluated for their N2O mitigation potential. This research evaluated a long-term (22 years) experiment testing the effect of soil management systems on N2O emissions in the postharvest period (autumn) from a subtropical Rhodic Hapludox at the research center FUNDACEP, in Cruz Alta, state of Rio Grande do Sul. Three treatments were evaluated, one under conventional tillage with soybean residues (CTsoybean) and two under no-tillage with soybean (NTsoybean) and maize residues (NTmaize). N2O emissions were measured eight times within 24 days (May 2007) using closed static chambers. Gas flows were obtained based on the relations between gas concentrations in the chamber at regular intervals (0, 15, 30, 45 min) analyzed by gas chromatography. After soybean harvest, accumulated N2O emissions in the period were approximately three times higher in the untilled soil (164 mg m-2 N) than under CT (51 mg m-2 N), with a short-lived N2O peak of 670 mg m-2 h-1 N. In contrast, soil N2O emissions in NT were lower after maize than after soybean, with a N2O peak of 127 g m-2 h-1 N. The multivariate analysis of N2O fluxes and soil variables, which were determined simultaneously with air sampling, demonstrated that the main driving variables of soil N2O emissions were soil microbial activity, temperature, water-filled pore space, and NO3- content. To replace soybean monoculture, crop rotation including maize must be considered as a strategy to decrease soil N2O emissions from NT soils in Southern Brazil in a Autumn.
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The soil surface roughness increases water retention and infiltration, reduces the runoff volume and speed and influences soil losses by water erosion. Similarly to other parameters, soil roughness is affected by the tillage system and rainfall volume. Based on these assumptions, the main purpose of this study was to evaluate the effect of tillage treatments on soil surface roughness (RR) and tortuosity (T) and to investigate the relationship with soil and water losses in a series of simulated rainfall events. The field study was carried out at the experimental station of EMBRAPA Southeastern Cattle Research Center in São Carlos (Fazenda Canchim), in São Paulo State, Brazil. Experimental plots of 33 m² were treated with two tillage practices in three replications, consisting of: untilled (no-tillage) soil (NTS) and conventionally tilled (plowing plus double disking) soil (CTS). Three successive simulated rain tests were applied in 24 h intervals. The three tests consisted of a first rain of 30 mm/h, a second of 30 mm/h and a third rain of 70 mm/h. Immediately after tilling and each rain simulation test, the surface roughness was measured, using a laser profile meter. The tillage treatments induced significant changes in soil surface roughness and tortuosity, demonstrating the importance of the tillage system for the physical surface conditions, favoring water retention and infiltration in the soil. The increase in surface roughness by the tillage treatments was considerably greater than its reduction by rain action. The surface roughness and tortuosity had more influence on the soil volume lost by surface runoff than in the conventional treatment. Possibly, other variables influenced soil and water losses from the no-tillage treatments, e.g., soil type, declivity, slope length, among others not analyzed in this study.
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Biological nitrogen fixation by rhizobium-legume symbiosis represents one of the most important nitrogen sources for plants and depends strongly on the symbiotic efficiency of the rhizobium strain. This study evaluated the symbiotic capacity of rhizobial isolates from calopo (CALOPOGONIUM MUCUNOIDES) taken from an agrisoil under BRACHIARIA DECUMBENS pasture, sabiá (MIMOSA CAESALPINIIFOLIA) plantations and Atlantic Forest areas of the Dry Forest Zone of Pernambuco. A total of 1,575 isolates were obtained from 398 groups. A single random isolate of each group was authenticated, in randomized blocks with two replications. Each plant was inoculated with 1 mL of a bacterial broth, containing an estimated population of 10(8) rhizobial cells mL-1. Forty-five days after inoculation, the plants were harvested, separated into shoots, roots and nodules, oven-dried to constant mass, and weighed. Next, the symbiotic capability was tested with 1.5 kg of an autoclaved sand:vermiculite (1:1) mixture in polyethylene bags. The treatments consisted of 122 authenticated isolates, selected based on the shoot dry matter, five uninoculated controls (treated with 0, 50, 100, 150, or 200 kg ha-1 N) and a control inoculated with SEMIA 6152 (=BR1602), a strain of BRADYRHIZOBIUM JAPONICUM The test was performed as described above. The shoot dry matter of the plants inoculated with the most effective isolates did not differ from that of plants treated with 150 kg ha-1 N. Shoot dry matter was positively correlated with all other variables. The proportion of effective isolates was highest among isolates from SABIÁ forests. There was great variation in nodule dry weight, as well as in N contents and total N.
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Taking into account the nature of the hydrological processes involved in in situ measurement of Field Capacity (FC), this study proposes a variation of the definition of FC aiming not only at minimizing the inadequacies of its determination, but also at maintaining its original, practical meaning. Analysis of FC data for 22 Brazilian soils and additional FC data from the literature, all measured according to the proposed definition, which is based on a 48-h drainage time after infiltration by shallow ponding, indicates a weak dependency on the amount of infiltrated water, antecedent moisture level, soil morphology, and the level of the groundwater table, but a strong dependency on basic soil properties. The dependence on basic soil properties allowed determination of FC of the 22 soil profiles by pedotransfer functions (PTFs) using the input variables usually adopted in prediction of soil water retention. Among the input variables, soil moisture content θ (6 kPa) had the greatest impact. Indeed, a linear PTF based only on it resulted in an FC with a root mean squared residue less than 0.04 m³ m-3 for most soils individually. Such a PTF proved to be a better FC predictor than the traditional method of using moisture content at an arbitrary suction. Our FC data were compatible with an equivalent and broader USA database found in the literature, mainly for medium-texture soil samples. One reason for differences between FCs of the two data sets of fine-textured soils is due to their different drainage times. Thus, a standardized procedure for in situ determination of FC is recommended.
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The objective of this work was to perform a quantitative analysis of the amino acid composition of soybean seeds as affected by climatic variables during seed filling. Amino acids were determined from seed samples taken at harvest in 31 multi-environment field trials carried out in Argentina. Total amino acids ranged from 31.69 to 49.14%, and total essential and nonessential amino acids varied from 12.83 to 19.02% and from 18.86 to 31.15%, respectively. Variance components expressed as the percentage of total variation showed that the environment was the most important source of variation for all traits, followed by the genotype x environment interaction. Significant explanatory linear regressions were detected for amino acid content regarding: average daily mean air temperature and cumulative solar radiation, during seed filling; precipitation minus potential evapotranspiration, during the whole reproductive period; and the combinations of these climatic variables. Each amino acid behaves differently according to environmental conditions, indicating compensatory effects among them.
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The objective of this work was to develop and validate linear regression models to estimate the production of dry matter by Tanzania grass (Megathyrsus maximus, cultivar Tanzania) as a function of agrometeorological variables. For this purpose, data on the growth of this forage grass from 2000 to 2005, under dry‑field conditions in São Carlos, SP, Brazil, were correlated to the following climatic parameters: minimum and mean temperatures, degree‑days, and potential and actual evapotranspiration. Simple linear regressions were performed between agrometeorological variables (independent) and the dry matter accumulation rate (dependent). The estimates were validated with independent data obtained in São Carlos and Piracicaba, SP, Brazil. The best statistical results in the development and validation of the models were obtained with the agrometeorological parameters that consider thermal and water availability effects together, such as actual evapotranspiration, accumulation of degree‑days corrected by water availability, and the climatic growth index, based on average temperature, solar radiation, and water availability. These variables can be used in simulations and models to predict the production of Tanzania grass.
Genetic diversity between improved banana diploids using canonical variables and the Ward-MLM method
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The objective of this work was to estimate the genetic diversity of improved banana diploids using data from quantitative analysis and from simple sequence repeats (SSR) marker, simultaneously. The experiment was carried out with 33 diploids, in an augmented block design with 30 regular treatments and three common ones. Eighteen agronomic characteristics and 20 SSR primers were used. The agronomic characteristics and the SSR were analyzed simultaneously by the Ward-MLM, cluster, and IML procedures. The Ward clustering method considered the combined matrix obtained by the Gower algorithm. The Ward-MLM procedure identified three ideal groups (G1, G2, and G3) based on pseudo-F and pseudo-t² statistics. The dendrogram showed relative similarity between the G1 genotypes, justified by genealogy. In G2, 'Calcutta 4' appears in 62% of the genealogies. Similar behavior was observed in G3, in which the 028003-01 diploid is the male parent of the 086079-10 and 042079-06 genotypes. The method with canonical variables had greater discriminatory power than Ward-MLM. Although reduced, the genetic variability available is sufficient to be used in the development of new hybrids.
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The objective of this work was to assess the degree of multicollinearity and to identify the variables involved in linear dependence relations in additive-dominant models. Data of birth weight (n=141,567), yearling weight (n=58,124), and scrotal circumference (n=20,371) of Montana Tropical composite cattle were used. Diagnosis of multicollinearity was based on the variance inflation factor (VIF) and on the evaluation of the condition indexes and eigenvalues from the correlation matrix among explanatory variables. The first model studied (RM) included the fixed effect of dam age class at calving and the covariates associated to the direct and maternal additive and non-additive effects. The second model (R) included all the effects of the RM model except the maternal additive effects. Multicollinearity was detected in both models for all traits considered, with VIF values of 1.03 - 70.20 for RM and 1.03 - 60.70 for R. Collinearity increased with the increase of variables in the model and the decrease in the number of observations, and it was classified as weak, with condition index values between 10.00 and 26.77. In general, the variables associated with additive and non-additive effects were involved in multicollinearity, partially due to the natural connection between these covariables as fractions of the biological types in breed composition.
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The objective of this work was to evaluate the spore density and diversity of arbuscular mycorrhizal fungi (AMF) in soil aggregates from fields of "murundus" (large mounds of soil) in areas converted and not converted to agriculture. The experiment was conducted in a completely randomized design with five replicates, in a 5x3 factorial arrangement: five areas and three aggregate classes (macro-, meso-, and microaggregates). The evaluated variables were: spore density and diversity of AMF, total glomalin, total organic carbon (TOC), total extraradical mycelium (TEM), and geometric mean diameter (GMD) of soil aggregates. A total of 21 AMF species was identified. Spore density varied from 29 to 606 spores per 50 mL of soil and was higher in microaggregates and in the area with 6 years of conversion to agriculture. Total glomalin was higher between murundus in all studied aggregate classes. The area with 6 years showed lower concentration of TOC in macroaggregates (8.6 g kg-1) and in microaggregates (10.1 g kg-1). TEM was greater at the top of the murundus in all aggregate classes. GMD increased with the conversion time to agriculture. The density and diversity of arbuscular mycorrhizal spores change with the conversion of fields of murundus into agriculture.
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Analytical curves are normally obtained from discrete data by least squares regression. The least squares regression of data involving significant error in both x and y values should not be implemented by ordinary least squares (OLS). In this work, the use of orthogonal distance regression (ODR) is discussed as an alternative approach in order to take into account the error in the x variable. Four examples are presented to illustrate deviation between the results from both regression methods. The examples studied show that, in some situations, ODR coefficients must substitute for those of OLS, and, in other situations, the difference is not significant.
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Phase transition and viscosity behavior of emulsified systems were studied after modifying their physicochemical formulation. Effects of concentration and nature of salts and n-alcohols, and water/oil relation on the rheological properties of emulsions were also studied. Pre-equilibrated systems were emulsified according to an agitation procedure, and the viscosity (cP) was measured at different shear rates ranging from 1 to 300 s-1. The phase behavior, as well as the emulsion type based on electrolytic conductivity, was observed. Several interpretations of the flow and viscosity curves of emulsions were made through the estimation of rheological parameters such as consistency index "k" and behavior index "n".
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This study was carried to evaluate the efficiency of the Bitterlich method in growth and yield modeling of the even-aged Eucalyptus stands. 25 plots were setup in Eucalyptus grandis cropped under a high bole system in the Central Western Region of Minas Gerais, Brazil. The sampling points were setup in the center of each plot. The data of four annual mesurements were colleted and used to adjust the three model types using the age, the site index and the basal area as independent variables. The growths models were fitted for volume and mass of trees. The efficiency of the Bitterlich method was confirmed for generating the data for growth and yield modeling.
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The increasing demand of consumer markets for the welfare of birds in poultry house has motivated many scientific researches to monitor and classify the welfare according to the production environment. Given the complexity between the birds and the environment of the aviary, the correct interpretation of the conduct becomes an important way to estimate the welfare of these birds. This study obtained multiple logistic regression models with capacity of estimating the welfare of broiler breeders in relation to the environment of the aviaries and behaviors expressed by the birds. In the experiment, were observed several behaviors expressed by breeders housed in a climatic chamber under controlled temperatures and three different ammonia concentrations from the air monitored daily. From the analysis of the data it was obtained two logistic regression models, of which the first model uses a value of ammonia concentration measured by unit and the second model uses a binary value to classify the ammonia concentration that is assigned by a person through his olfactory perception. The analysis showed that both models classified the broiler breeder's welfare successfully.