101 resultados para soil data requirements


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The present study was carried out in two different areas of Province of Cordoba, Argentina, where there was a suspicious of endemic mycosis. The previous data were the presence of a clinical case of pulmonary cryptococcosis in one area (Alta Gracia) and the previous findings of a high incidence of coccidioidin and cryptococcin reactors in the population of the second one (Villa Dolores). In both areas soil samples for fungi were studied and Cryptococcus neoformans was found in 2/25 samples from Alta Gracia. In Villa Dolores Coccidioides immitis was isolated in 2/40 samples, and C. neoformans in 1/40 samples. Delayed hypersensitivity test with cryptococcin was determined in the population from Alta Gracia and it was found to be 5.3%. Positive cutaneous tests with coccidioidin (33.8%) and cryptococcin (31.9%) in Villa Dolores were obtained. With these findings two endemic areas of systemic mycoses in Cordoba, Argentina were delimited.

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Soil conditions under pasture were examined in a range of sites representing the sequence of conversion of forest to pasture at two locations in the vicinity of Ilha de Maracã, Roraima. Comparisons were made with adjacent savana. Soil bulk densities shown to increase after forest clearance and soil chemical data indicate that the initial beneficial effects on nutrient supply of burning forest debris are rather short-lived. Very low levels of available phosphorus prevail in areas of savanna and cultivated pasture of all ages. Variations in the status of older cultivated pastures are mainly attributable to different grazing levelt.

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Soil respiration plays a significant role in the carbon cycle of Amazonian rainforests. Measurements of soil respiration have only been carried out in few places in the Amazon. This study investigated the effects of the method of ring insertion in the soil as well as of rainfall and spatial distribution on CO2 emission in the central Amazon region. The ring insertion effect increased the soil emission about 13-20% for sandy and loamy soils during the firsts 4-7 hours, respectively. After rainfall events below 2 mm, the soil respiration did not change, but for rainfall greater than 3 mm, after 2 hours there was a decrease in soil temperature and respiration of about 10-34% for the loamy and sand soils, with emissions returning to normal after around 15-18 hours. The size of the measurement areas and the spatial distribution of soil respiration were better estimated using the Shuttle Radar Topographic Mission (SRTM) data. The Campina reserve is a mosaic of bare soil, stunted heath forest-SHF and tall heath forest-THF. The estimated total average CO2 emissions from the area was 3.08±0.8 µmol CO2 m-2 s-1. The Cuieiras reserve is another mosaic of plateau, slope, Campinarana and riparian forests and the total average emission from the area was 3.82±0.76 µmol CO2 m-2 s-1. We also found that the main control factor of the soil respiration was soil temperature, with 90% explained by regression analysis. Automated soil respiration datasets are a good tool to improve the technique and increase the reliability of measurements to allow a better understanding of all possible factors driven by soil respiration processes.

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Bionomic data and larval density of Scarabaeidae (Pleurosticti) in sugarcane in the central region of Mato Grosso do Sul, Brazil. Phytophagous larvae of Scarabaeidae cause damage to diverse crops. Information on these pests is scarce; therefore, the objective of this study was to determine biological aspects and larval density of species occurring in an area of sugarcane. The studies were developed in Sidrolândia from April 2009 to March 2010. Scarab beetle larvae were collected in sugarcane roots every fifteen days, taken to the laboratory and reared to obtain the adults and determine biological parameters. A total of 2,656 larvae were collected, being 162 Liogenys fuscus, 120 Cyclocephala verticalis, 37 Cyclocephala forsteri, and 2337 Anomonyx sp. In January, 53.65 larvae m-2 were obtained, and the most abundant species was Anomonyx sp, representing 87.99% of the total larvae collected. From November to March, the greatest densities of Anomonyx were observed in the field. The adults of this species occurred from May to September, and egg laying from September to November. Eggs measured 1.1 x 1.7 mm, and incubation period last 15.4 days. First instar larvae were observed mainly in October; second instar larvae from November to April; and third instar from January to July. Pupae were observed from May to August. The most abundant scarab beetle, Anomonyx sp. in roots of sugarcane presents one generation per year in Sidrolândia, MS.

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Studies from some semi-arid regions of the world have shown the beneficial effect of trees in silvopastoral systems, by promoting the formation of resource islands and increasing the sustainability of the system. No data are available in this respect for tree species of common occurrence in semi-arid Northeastern Brazil. In the present study, conducted in the summer of 1996, three tree species (Zyziphus joazeiro, Spondias tuberosa and Prosopis juliflora: ) found within Cenchrus ciliaris pastures were selected to evaluate differences on herbaceous understory and soil chemical characteristics between samples taken under the tree canopy and in open grass areas. Transects extending from the tree trunk to open grass areas were established, and soil (0-15 cm) and herbaceous understory (standing live biomass in 1 m² plots) samples were taken at 0, 25, 50, 100, 150 and 200% of the average canopy radius (average radius was 6.6 ± 0.5, 4.5 ± 0.5, and 5.3 ± 0.8 m for Z. joazeiro, P. juliflora, and S. tuberosa , respectively). Higher levels of soil C, N, P, Ca, Mg, K, and Na were found under the canopies of Z. joazeiro and P. juliflora: trees, as compared to open grass areas. Only soil Mg organic P were higher under the canopies of S. tuberosa trees, as compared to open grass areas. Herbaceous understory biomass was significantly lower under the canopy of S. tuberosa and P. juliflora trees (107 and 96 g m-2, respectively) relatively to open grass areas (145 and 194 g m-2). No herbaceous biomass differences were found between Z. joazeiro canopies and open grass areas (107 and 87 g m-2, respectively). Among the three tree species studied, Z. joazeiro was the one that presented the greatest potential for use in a silvopastoral system at the study site, since it had a larger nutrient stock in the soil without negatively affecting herbaceous understory biomass, relatively to open grass areas.

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In this study, we investigated the feasibility of using the C-band European Remote Sensing Satellite (ERS-1) synthetic aperture radar (SAR) data to estimate surface soil roughness in a semiarid rangeland. Radar backscattering coefficients were extracted from a dry and a wet season SAR image and were compared with 47 in situ soil roughness measurements obtained in the rocky soils of the Walnut Gulch Experimental Watershed, southeastern Arizona, USA. Both the dry and the wet season SAR data showed exponential relationships with root mean square (RMS) height measurements. The dry C-band ERS-1 SAR data were strongly correlated (R² = 0.80), while the wet season SAR data have somewhat higher secondary variation (R² = 0.59). This lower correlation was probably provoked by the stronger influence of soil moisture, which may not be negligible in the wet season SAR data. We concluded that the single configuration C-band SAR data is useful to estimate surface roughness of rocky soils in a semiarid rangeland.

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The quality of semi-detailed (scale 1:100.000) soil maps and the utility of a taxonomically based legend were assessed by studying 33 apparently homogeneous fields with strongly weathered soils in two regions in São Paulo State: Araras and Assis. An independent data set of 395 auger sites was used to determine purity of soil mapping units and analysis of variance within and between mapping units and soil classification units. Twenty three soil profiles were studied in detail. The studied soil maps have a high purity for some legend criteria, such as B horizon type (> 90%) and soil texture class (> 80%). The purity for the "trophic character" (eutrophic, dystrophic, allic) was only 55% in Assis. It was 88% in Araras, where many soil units had been mapped as associations. In both regions, the base status of clay-textured soils was generally better than suggested by the maps. Analysis of variance showed that mapping was successful for "durable" soil characteristics such as clay content (> 80% of variance explained) and cation exchange capacity (≥ 50% of variance explained) of 0-20 and 60-80 cm layers. For soil characteristics that are easily modified by management, such as base saturation of the 0-20 cm layer, the maps had explained very little (< 15%) of the total variance in the study areas. Intermediate results were obtained for base saturation of the 60-80 cm layer (56% in Assis; 42% in Araras). Variance explained by taxonomic groupings that formed the basis for the legend of the soil maps was similar to, often even smaller than, variance explained by mapping units. The conclusion is that map boundaries have been very carefully located, but descriptions of mapping units could be improved. In future mappings, this could possibly be done at low cost by (a) bulk sampling to remove short range variation and enhance visualization of spatial patterns at distances > 100 m; (b) taking advantage of correlations between easily measured soil characteristics and chemical soil properties and, (c) unbending the link between legend criteria and a taxonomic system. The maps are well suited to obtain an impression of land suitability for high-input farming. Additional field work and data on former land use/management are necessary for the evaluation of chemical properties of surface horizons.

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Site-specific regression coefficient values are essential for erosion prediction with empirical models. With the objective to investigate the surface-soilconsolidation factor, Cf, linked to the RUSLE's prior-land-use subfactor, PLU, an erosion experiment using simulated rainfall on a 0.075 m m-1 slope, sandy loam Paleudult soil, was conducted at the Agriculture Experimental Station of the Federal University of Rio Grande do Sul (EEA/UFRGS), in Eldorado do Sul, State of Rio Grande do Sul, Brazil. Firstly, a row-cropped area was excluded from cultivation (March 1995), the existing crop residue removed from the field, and the soil kept clean-tilled the rest of the year (to get a degraded soil condition for the intended purpose of this research). The soil was then conventional-tilled for the last time (except for a standard plot which was kept continuously cleantilled for comparison purposes), in January 1996, and the following treatments were established and evaluated for soil reconsolidation and soil erosion until May 1998, on duplicated 3.5 x 11.0 m erosion plots: (a) fresh-tilled soil, continuously in clean-tilled fallow (unit plot); (b) reconsolidating soil without cultivation; and (c) reconsolidating soil with cultivation (a crop sequence of three corn- and two black oats cycles, continuously in no-till, removing the crop residues after each harvest for rainfall application and redistributing them on the site after that). Simulated rainfall was applied with a Swanson's type, rotating-boom rainfall simulator, at 63.5 mm h-1 intensity and 90 min duration, six times during the two-and-half years of experimental period (at the beginning of the study and after each crop harvest, with the soil in the unit plot being retilled before each rainfall test). The soil-surface-consolidation factor, Cf, was calculated by dividing soil loss values from the reconsolidating soil treatments by the average value from the fresh-tilled soil treatment (unit plot). Non-linear regression was used to fit the Cf = e b.t model through the calculated Cf-data, where t is time in days since last tillage. Values for b were -0.0020 for the reconsolidating soil without cultivation and -0.0031 for the one with cultivation, yielding Cf-values equal to 0.16 and 0.06, respectively, after two-and-half years of tillage discontinuation, compared to 1.0 for fresh-tilled soil. These estimated Cf-values correspond, respectively, to soil loss reductions of 84 and 94 %, in relation to soil loss from the fresh-tilled soil, showing that the soil surface reconsolidated intenser with cultivation than without it. Two distinct treatmentinherent soil surface conditions probably influenced the rapid decay-rate of Cf values in this study, but, as a matter of a fact, they were part of the real environmental field conditions. Cf-factor curves presented in this paper are therefore useful for predicting erosion with RUSLE, but their application is restricted to situations where both soil type and particular soil surface condition are similar to the ones investigate in this study.

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Intensification of agricultural production without a sound management and regulations can lead to severe environmental problems, as in Western Santa Catarina State, Brazil, where intensive swine production has caused large accumulations of manure and consequently water pollution. Natural resource scientists are asked by decision-makers for advice on management and regulatory decisions. Distributed environmental models are useful tools, since they can be used to explore consequences of various management practices. However, in many areas of the world, quantitative data for model calibration and validation are lacking. The data-intensive distributed environmental model AgNPS was applied in a data-poor environment, the upper catchment (2,520 ha) of the Ariranhazinho River, near the city of Seara, in Santa Catarina State. Steps included data preparation, cell size selection, sensitivity analysis, model calibration and application to different management scenarios. The model was calibrated based on a best guess for model parameters and on a pragmatic sensitivity analysis. The parameters were adjusted to match model outputs (runoff volume, peak runoff rate and sediment concentration) closely with the sparse observed data. A modelling grid cell resolution of 150 m adduced appropriate and computer-fit results. The rainfall runoff response of the AgNPS model was calibrated using three separate rainfall ranges (< 25, 25-60, > 60 mm). Predicted sediment concentrations were consistently six to ten times higher than observed, probably due to sediment trapping along vegetated channel banks. Predicted N and P concentrations in stream water ranged from just below to well above regulatory norms. Expert knowledge of the area, in addition to experience reported in the literature, was able to compensate in part for limited calibration data. Several scenarios (actual, recommended and excessive manure applications, and point source pollution from swine operations) could be compared by the model, using a relative ranking rather than quantitative predictions.

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In agriculture, the soil strength is used to describe the susceptibility to deformation by pressure caused by agricultural machine. The purpose of this study was to compare different methods for estimating the inherent soil strength and to identify their suitability for the evaluation of load support capacity, compaction susceptibility and root growth. The physical, chemical, mineralogical and intrinsic strength properties of seven soil samples, collected from five sampling pits at different locations in Brazil, were measured. Four clay (CS) and three sandy clay loam (SCL) soils were used. The clay soils were collected on a farm in Santo Ângelo, RS (28 º 16 ' 16 '' S; 54 º 13 ' 11 '' W 290 m); A and B horizons at the Universidade Federal de Lavras, Lavras, MG (21 º 13 ' 47 '' S; 44 º 58 ' 6'' W; 918 m) and on the farm Sygenta, in Uberlandia, MG (18 º 58 ' 37 '' S; 48 º 12 ' 05 '' W 866 m). The sandy clay loam soils were collected in Aracruz, ES (19 º 47 ' 10 '' S; 40 º 16 ' 29 '' W 81 m), and on the farm Xavier, Lavras, MG (21 º 13 ' 24 '' S; 45 º 05 ' 00 '' W; 844 m). Soil strength was estimated based on measurements of: (a) a pneumatic consolidometer, (b) manual pocket (non-rotating) penetrometer; and (c) automatic (rotating) penetrometer. The results of soil strength properties were similar by the three methods. The soil structure had a significant influence on soil strength. Results of measurements with both the manual pocket and the electric penetrometer were similar, emphasizing the influence of soil texture. The data showed that, to enhance the reliability of predictions of preconsolidation pressure by penetrometers, it is better to separate the soils into the different classes, rather than analyze them jointly. It can be concluded that the consolidometer method, although expensive, is the best when evaluations of load support capacity and compaction susceptibility of soil samples are desired.

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Laser diffraction (LD) provides detailed analysis of particle size distribution. Its application to testing the stability of soil aggregates can assist studies on the aggregation of soils with contrasting electrochemical properties. The objectives of the present work were: (a) to propose a protocol for using LD to study soil aggregation, (b) to study the aggregation of an Acrisol under the influence of different doses and forms of lime. Samples were collected in 2005 from a Brazilian Acrisol that in 1994 had received 0.0; 2.0; 8.5 and 17.0 Mg ha-1 of lime, left on the soil surface or incorporated. Aggregates from 4.76 to 8.00 mm diameters were studied using the traditional method proposed by Kemper & Chepil (1965), with wet sieving, while aggregates from 1.00 to 2.00 mm were studied using a CILAS® laser diffractometer that distinguishes particles ranging from 0.04 to 2,500.00 μm. LD readings were made after six consecutive pre-treatments, using agitation times, a chemical dispersion agent and ultrasound. Mean Weighted Diameter (MWD) and the Aggregate Stability Index (ASI) calculated, using the traditional method does not discriminate the treatments. However, LD is able to produce detailed data on soil aggregation, resulting in indexes of stability of aggregates that are linearly related to the doses of lime applied (MWD: R² = 0.986 and ASI: R² = 0.876). It may be concluded that electrochemical changes in the Brazilian Acrisol resulting from incorporated lime affect the stability of aggregates, increasing stability with increased doses of lime.

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Soil science has sought to develop better techniques for the classification of soils, one of which is the use of remote sensing applications. The use of ground sensors to obtain soil spectral data has enabled the characterization of these data and the advancement of techniques for the quantification of soil attributes. In order to do this, the creation of a soil spectral library is necessary. A spectral library should be representative of the variability of the soils in a region. The objective of this study was to create a spectral library of distinct soils from several agricultural regions of Brazil. Spectral data were collected (using a Fieldspec sensor, 350-2,500 nm) for the horizons of 223 soil profiles from the regions of Matão, Paraguaçu Paulista, Andradina, Ipaussu, Mirandópolis, Piracicaba, São Carlos, Araraquara, Guararapes, Valparaíso (SP); Naviraí, Maracajú, Rio Brilhante, Três Lagoas (MS); Goianésia (GO); and Uberaba and Lagoa da Prata (MG). A Principal Component Analysis (PCA) of the data was then performed and a graphic representation of the spectral curve was created for each profile. The reflectance intensity of the curves was principally influenced by the levels of Fe2O3, clay, organic matter and the presence of opaque minerals. There was no change in the spectral curves in the horizons of the Latossolos, Nitossolos, and Neossolos Quartzarênicos. Argissolos had superficial horizon curves with the greatest intensity of reflection above 2,200 nm. Cambissolos and Neossolos Litólicos had curves with greater reflectance intensity in poorly developed horizons. Gleisols showed a convex curve in the region of 350-400 nm. The PCA was able to separate different data collection areas according to the region of source material. Principal component one (PC1) was correlated with the intensity of reflectance samples and PC2 with the slope between the visible and infrared samples. The use of the Spectral Library as an indicator of possible soil classes proved to be an important tool in profile classification.

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The most advanced stage of water erosion, the gully, represents severe problems in different contexts, both in rural and urban environments. In the search for a stabilization of the process in a viable manner it is of utmost importance to assess the efficiency of evaluation methodologies. For this purpose, the efficiency of low-cost conservation practices were tested for the reduction of soil and nutrient losses caused by erosion from gullies in Pinheiral, state of Rio de Janeiro. The following areas were studied: gully recovered by means of physical and biological strategies; gullies in recovering stage, by means of physical strategies only, and gullies under no restoration treatment. During the summer of 2005/2006, the following data sets were collected for this study: soil classification of each of the eroded gully areas; planimetric and altimetric survey; determination of rain erosivity indexes; determination of amount of soil sediment; sediment grain size characteristics; natural amounts of nutrients Ca, Mg, K and P, as well as total C and N concentrations. The results for the three first measurements were 52.5, 20.5, and 29.0 Mg in the sediments from the gully without intervention, and of 1.0, 1.7 and 1.8 Mg from the gully with physical interventions, indicating an average reduction of 95 %. The fully recovered gully produced no sediment during the period. The data of total nutrient loss from the three gullies under investigation showed reductions of 98 % for the recovering gully, and 99 % for the fully recovered one. As for the loss of nutrients, the data indicate a nutrient loss of 1,811 kg from for the non-treated gully. The use of physical and biological interventions made it possible to reduce overall nutrient loss by more than 96 %, over the entire rainy season, as compared to the non-treated gully. Results show that the methods used were effective in reducing soil and nutrient losses from gullies.

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Irrigation with treated domestic sewage wastewater (TSE) is an agricultural practice to reduce water requirements of agroecossystems and the nutrient load impact on freshwaters, but adverse effects on soil chemical (salinization, sodification, etc.) and soil physical properties (alteration in soil porosity and hydraulic conductivity, etc.) have been reported. This study aimed to define some relationships among these changes in an Oxisol using multivariate analysis. Corn (Zea mays L.) and sunflower (Helianthus annuus L.) were grown for two years, irrigated with TSE. The following soil properties were determined: Ca2+; Mg2+; Na+; K+ and H + Al contents, cationic exchangeable capacity (CEC), sum of bases (SB), base saturation (V), texture (sand, silt and clay), macro-, micro-, and cryptoporosity (V MA, V MI and V CRI), water content at soil saturation (θS) and at field capacity (θFC), residual water content (θR), soil bulk density (d s), water dispersed clay (WDC) and saturated hydraulic conductivity (K SAT). Factor analysis revealed the following six principal factors: Fine Porosity (composed of Na+; K+; WDC, θR, θRFC, and V CRI); Large Porosity (θS, d s, V MA, Vs); Soil CEC (Ca2+; Mg2+; CEC, SB, V); Soil Acidity (H + Al); and Soil Texture (factors 5 and 6). A dual pore structure appears clearly to the factors 1 and 2, with an apparent relationship between fine porosity and the monovalent cations Na+ and K+. The irrigation (with potable sodic tap water or sewage wastewater) only had a significant effect on Fine Porosity and Large Porosity factors, while factors 3 and 4 (Soil CEC and Soil Acidity) were correlated with soil depth. The main conclusion was a shift in pore distribution (large to fine pores) during irrigation with TSE, which induces an increase of water storage and reduces the capacity of drainage of salts.

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Statistical models allow the representation of data sets and the estimation and/or prediction of the behavior of a given variable through its interaction with the other variables involved in a phenomenon. Among other different statistical models, are the autoregressive state-space models (ARSS) and the linear regression models (LR), which allow the quantification of the relationships among soil-plant-atmosphere system variables. To compare the quality of the ARSS and LR models for the modeling of the relationships between soybean yield and soil physical properties, Akaike's Information Criterion, which provides a coefficient for the selection of the best model, was used in this study. The data sets were sampled in a Rhodic Acrudox soil, along a spatial transect with 84 points spaced 3 m apart. At each sampling point, soybean samples were collected for yield quantification. At the same site, soil penetration resistance was also measured and soil samples were collected to measure soil bulk density in the 0-0.10 m and 0.10-0.20 m layers. Results showed autocorrelation and a cross correlation structure of soybean yield and soil penetration resistance data. Soil bulk density data, however, were only autocorrelated in the 0-0.10 m layer and not cross correlated with soybean yield. The results showed the higher efficiency of the autoregressive space-state models in relation to the equivalent simple and multiple linear regression models using Akaike's Information Criterion. The resulting values were comparatively lower than the values obtained by the regression models, for all combinations of explanatory variables.