975 resultados para Soil parameters variation
Resumo:
The Restinga vegetation consists of a mosaic of plant communities, which are defined by the characteristics of the substrates, resulting from the type and age of the depositional processes. This mosaic complex of vegetation types comprises restinga forest in advanced (high restinga) and medium regeneration stages (low restinga), each with particular differentiating vegetation characteristics. The climate along the coast is tropical (Köppen). Of all ecosystems of the Atlantic Forest, Restinga is the most fragile and susceptible to anthropic disturbances. Plants respond to soil characteristics with physiological and morphological modifications, resulting in changes in the architecture (spatial configuration) of the root system. The purpose of this study was to characterize the soil fertility of high and low restinga forests, by chemical and physical parameters, and its relation to the root system distribution in the soil profile. Four locations were studied: (1) Ilha Anchieta State Park, Ubatuba; (2) two Ecological Stations of Jureia-Itatins and of Chauás, in the municipality of Iguape; (3) Vila de Pedrinhas in the municipality of Ilha Comprida; and (4) Ilha do Cardoso State Park, Cananeia. The soil fertility (chemical and physical properties) was analyzed in the layers 0-5, 0-10, 0-20, 20-40 and 40-60 cm. In addition, the distribution of the root system in the soil profile was evaluated, using digital images and the Spring program. It was concluded that the root system of all vegetation types studied is restricted to the surface layers, 0-10 and 10-20 cm, but occupies mainly the 0-10 cm layer (70 %); that soil fertility is low in all environments studied, with base saturation values below 16 %, since most exchange sites are occupied by aluminum; and that restinga vegetation is edaphic.
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Pedotransfer functions (PTF) were developed to estimate the parameters (α, n, θr and θs) of the van Genuchten model (1980) to describe soil water retention curves. The data came from various sources, mainly from studies conducted by universities in Northeast Brazil, by the Brazilian Agricultural Research Corporation (Embrapa) and by a corporation for the development of the São Francisco and Parnaíba river basins (Codevasf), totaling 786 retention curves, which were divided into two data sets: 85 % for the development of PTFs, and 15 % for testing and validation, considered independent data. Aside from the development of general PTFs for all soils together, specific PTFs were developed for the soil classes Ultisols, Oxisols, Entisols, and Alfisols by multiple regression techniques, using a stepwise procedure (forward and backward) to select the best predictors. Two types of PTFs were developed: the first included all predictors (soil density, proportions of sand, silt, clay, and organic matter), and the second only the proportions of sand, silt and clay. The evaluation of adequacy of the PTFs was based on the correlation coefficient (R) and Willmott index (d). To evaluate the PTF for the moisture content at specific pressure heads, we used the root mean square error (RMSE). The PTF-predicted retention curve is relatively poor, except for the residual water content. The inclusion of organic matter as a PTF predictor improved the prediction of parameter a of van Genuchten. The performance of soil-class-specific PTFs was not better than of the general PTF. Except for the water content of saturated soil estimated by particle size distribution, the tested models for water content prediction at specific pressure heads proved satisfactory. Predictions of water content at pressure heads more negative than -0.6 m, using a PTF considering particle size distribution, are only slightly lower than those obtained by PTFs including bulk density and organic matter content.
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Studies of soil-water dynamics using toposequences are essential to improve the understanding of soil-water-vegetation relationships. This study assessed the hydro-physical and morphological characteristics of soils of Atlantic Rainforest in the Parque Estadual de Carlos Botelho, state of São Paulo, Brazil. The study area of 10.24 ha (320 x 320 m) was covered by dense tropical rainforest (Atlantic Rainforest). Based on soil maps and topographic maps of the area, a representative transect of the soil in this plot was chosen and five soil trenches were opened to determine morphological properties. To evaluate the soil hydro-physical functioning, soil particle size distribution, bulk density (r), particle density (r s), soil water retention curves (SWRC), field saturated hydraulic conductivity (Ks), macroporosity (macro), and microporosity (micro) and total porosity (TP) were determined. Undisturbed samples were collected for micromorphometric image analysis, to determine pore size, shape, and connectivity. The soils in the study area were predominantly Inceptisols, and secondly Entisols and Epiaquic Haplustult. In the soil hydro-physical characterization of the selected transect, a change was observed in Ks between the surface and subsurface layers, from high/intermediate to intermediate/low permeability. This variation in soil-water dynamics was also observed in the SWRC, with higher water retention in the subsurface horizons. The soil hydro-physical behavior was influenced by the morphogenetic characteristics of the soils.
Resumo:
Since different pedologists will draw different soil maps of a same area, it is important to compare the differences between mapping by specialists and mapping techniques, as for example currently intensively discussed Digital Soil Mapping. Four detailed soil maps (scale 1:10.000) of a 182-ha sugarcane farm in the county of Rafard, São Paulo State, Brazil, were compared. The area has a large variation of soil formation factors. The maps were drawn independently by four soil scientists and compared with a fifth map obtained by a digital soil mapping technique. All pedologists were given the same set of information. As many field expeditions and soil pits as required by each surveyor were provided to define the mapping units (MUs). For the Digital Soil Map (DSM), spectral data were extracted from Landsat 5 Thematic Mapper (TM) imagery as well as six terrain attributes from the topographic map of the area. These data were summarized by principal component analysis to generate the map designs of groups through Fuzzy K-means clustering. Field observations were made to identify the soils in the MUs and classify them according to the Brazilian Soil Classification System (BSCS). To compare the conventional and digital (DSM) soil maps, they were crossed pairwise to generate confusion matrices that were mapped. The categorical analysis at each classification level of the BSCS showed that the agreement between the maps decreased towards the lower levels of classification and the great influence of the surveyor on both the mapping and definition of MUs in the soil map. The average correspondence between the conventional and DSM maps was similar. Therefore, the method used to obtain the DSM yielded similar results to those obtained by the conventional technique, while providing additional information about the landscape of each soil, useful for applications in future surveys of similar areas.
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The S-index was introduced in 2004 in a publication by A.R. Dexter. S was proposed as an indicator of soil physical quality. A critical value delimiting soils with rich and poor physical quality was proposed. At present, Brazil is world leader in citations of Dexter's publication. In this publication the S-theory is mathematically revisited and extended. It is shown that S is mathematically correlated to bulk density and total porosity. As an absolute indicator, the value of S alone has proven to be incapable of predicting soil physical quality. The critical value does not always hold under boundary conditions described in the literature. This is to be expected because S is a static parameter, therefore implicitly unable to describe dynamic processes. As a relative indicator of soil physical quality, the S-index has no additional value over bulk density or total porosity. Therefore, in the opinion of the author, the fact that bulk density or total porosity are much more easily determined than the water retention curve for obtaining S disqualifies S as an advantageous indicator of relative soil physical quality. Among the several equations available for the fitting of water retention curves, the Groenevelt-Grant equation is preferable for use with S since one of its parameters and S are linearly correlated. Since efforts in soil physics research have the purpose of describing dynamic processes, it is the author's opinion that these efforts should shift towards mechanistic soil physics as opposed to the search for empirical correlations like S which, at present, represents far more than its reasonable share of soil physics in Brazil.
Resumo:
Incorporation of rice straw into the soil just before flooding for water-seeded rice can immobilize mineral nitrogen (N) and lead to the production of acetic acid harmful to the rice seedlings, which negatively affects grain yield. This study aimed to evaluate the formation of organic acids and variation in pH and to quantify the mineral N concentration in the soil as a function of different times of incorporation of rice straw or of ashes from burning the straw before flooding. The experiment was carried out in a greenhouse using an Inceptisol (Typic Haplaquept) soil. The treatments were as follows: control (no straw or ash); incorporation of ashes from previous straw burning; rice straw incorporated to drained soil 60 days before flooding; straw incorporated 30 days before flooding; straw incorporated 15 days before flooding and straw incorporated on the day of flooding. Experimental units were plastic buckets with 6.0 kg of soil. The buckets remained flooded throughout the trial period without rice plants. Soil samples were collected every seven days, beginning one day before flooding until the 13th week of flooding for determination of mineral N- ammonium (NH4+) and nitrate (NO3-). Soil solution pH and concentration of organic acids (acetic, propionic and butyric) were determined. All NO3- there was before flooding was lost in approximately two weeks of flooding, in all treatments. There was sigmoidal behavior for NH4+ formation in all treatments, i.e., ammonium ion concentration began to rise shortly after soil flooding, slightly decreased and then went up again. On the 91st day of flooding, the NH4+ concentrations in soil was 56 mg kg-1 in the control treatment, 72 mg kg-1 for the 60-day treatment, 73 mg kg-1 for the 30-day treatment and 53 mg kg-1 for the ash incorporation treatment. These ammonium concentrations correspond to 84, 108, 110 and 80 kg ha-1 of N-NH4+, respectively. When the straw was incorporated on the day of flooding or 15 days before, the concentration of N-NH4+ in the soil was 28 and 54 mg kg-1, equivalent to an accumulation of 42 and 81 kg ha-1 of N-NH4+, respectively. There was formation of acetic acid in which toxic concentrations were reached (7.2 mmol L-1) on the 15th day of flooding only for the treatment with straw incorporated on the day of flooding. The pH of the soil solution of all the treatments increased after flooding and this increase was faster in the treatments with incorporation of straw, followed by the ash treatment and then the control. After 60 days of flooding, however, the pH values were around 6.5 for all treatments, except for the control, which reached a pH of 6.3. Rice straw should be incorporated into the soil at least 30 days before flooding; otherwise, it may immobilize part of the mineral N and produce acetic acid in concentrations toxic to rice seedlings.
Resumo:
The dynamics of N losses in fertilizer by ammonia volatilization is affected by several factors, making investigation of these dynamics more complex. Moreover, some features of the behavior of the variable can lead to deviation from normal distribution, making the main commonly adopted statistical strategies inadequate for data analysis. Thus, the purpose of this study was to evaluate the patterns of cumulative N losses from urea through ammonia volatilization in order to find a more adequate and detailed way of assessing the behavior of the variable. For that reason, changes in patterns of ammonia volatilization losses as a result of applying different combinations of two soil classes [Planossolo and Chernossolo (Typic Albaqualf and Vertic Argiaquolls)] and different rates of urea (50, 100 and 150 kg ha-1 N), in the presence or absence of a urease inhibitor, were evaluated, adopting a 2 × 3 × 2 factorial design with four replications. Univariate and multivariate analysis of variance were performed using the adjusted parameter values of a logistic function as a response variable. The results obtained from multivariate analysis indicated a prominent effect of the soil class factor on the set of parameters, indicating greater relevance of soil adsorption potential on ammonia volatilization losses. Univariate analysis showed that the parameters related to total N losses and rate of volatilization were more affected by soil class and the rate of urea applied. The urease inhibitor affected only the rate and inflection point parameters, decreasing the rate of losses and delaying the beginning of the process, but had no effect on total ammonia losses. Patterns of ammonia volatilization losses provide details on behavior of the variable, details which can be used to develop and adopt more accurate techniques for more efficient use of urea.
Variability of soil fertility properties in areas planted to sugarcane in the State of Goias, Brazil
Resumo:
Soil sampling should provide an accurate representation of a given area so that recommendations for amendments of soil acidity, fertilization and soil conservation may be drafted to increase yield and improve the use of inputs. The aim of this study was to evaluate the variability of soil fertility properties of Oxisols in areas planted to sugarcane in the State of Goias, Brazil. Two areas of approximately 8,100 m² each were selected, representing two fields of the Goiasa sugarcane mill in Goiatuba. The sugarcane crop had a row spacing of 1.5 m and subsamples were taken from 49 points in the row and 49 between the row with a Dutch auger at depths of 0.0-0.2 and 0.2-0.4 m, for a total of 196 subsamples for each area. The samples were individually subjected to chemical analyses of soil fertility (pH in CaCl2, potential acidity, organic matter, P, K, Ca and Mg) and particle size analysis. The number of subsamples required to compose a sample within the acceptable ranges of error of 5, 10, 20 and 40 % of each property were computed from the coefficients of variation and the Student t-value for 95 % confidence. The soil properties under analysis exhibited different variabilities: high (P and K), medium (potential acidity, Ca and Mg) and low (pH, organic matter and clay content). Most of the properties analyzed showed an error of less than 20 % for a group of 20 subsamples, except for P and K, which were capable of showing an error greater than 40 % around the mean. The extreme variability in phosphorus, particularly at the depth of 0.2-0.4 m, attributed to banded application of high rates of P fertilizers at planting, places limitations on assessment of its availability due to the high number of subsamples required for a composite sample.
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Soil properties have an enormous impact on economic and environmental aspects of agricultural production. Quantitative relationships between soil properties and the factors that influence their variability are the basis of digital soil mapping. The predictive models of soil properties evaluated in this work are statistical (multiple linear regression-MLR) and geostatistical (ordinary kriging and co-kriging). The study was conducted in the municipality of Bom Jardim, RJ, using a soil database with 208 sampling points. Predictive models were evaluated for sand, silt and clay fractions, pH in water and organic carbon at six depths according to the specifications of the consortium of digital soil mapping at the global level (GlobalSoilMap). Continuous covariates and categorical predictors were used and their contributions to the model assessed. Only the environmental covariates elevation, aspect, stream power index (SPI), soil wetness index (SWI), normalized difference vegetation index (NDVI), and b3/b2 band ratio were significantly correlated with soil properties. The predictive models had a mean coefficient of determination of 0.21. Best results were obtained with the geostatistical predictive models, where the highest coefficient of determination 0.43 was associated with sand properties between 60 to 100 cm deep. The use of a sparse data set of soil properties for digital mapping can explain only part of the spatial variation of these properties. The results may be related to the sampling density and the quantity and quality of the environmental covariates and predictive models used.
Resumo:
Knowledge of the soil water retention curve (SWRC) is essential for understanding and modeling hydraulic processes in the soil. However, direct determination of the SWRC is time consuming and costly. In addition, it requires a large number of samples, due to the high spatial and temporal variability of soil hydraulic properties. An alternative is the use of models, called pedotransfer functions (PTFs), which estimate the SWRC from easy-to-measure properties. The aim of this paper was to test the accuracy of 16 point or parametric PTFs reported in the literature on different soils from the south and southeast of the State of Pará, Brazil. The PTFs tested were proposed by Pidgeon (1972), Lal (1979), Aina & Periaswamy (1985), Arruda et al. (1987), Dijkerman (1988), Vereecken et al. (1989), Batjes (1996), van den Berg et al. (1997), Tomasella et al. (2000), Hodnett & Tomasella (2002), Oliveira et al. (2002), and Barros (2010). We used a database that includes soil texture (sand, silt, and clay), bulk density, soil organic carbon, soil pH, cation exchange capacity, and the SWRC. Most of the PTFs tested did not show good performance in estimating the SWRC. The parametric PTFs, however, performed better than the point PTFs in assessing the SWRC in the tested region. Among the parametric PTFs, those proposed by Tomasella et al. (2000) achieved the best accuracy in estimating the empirical parameters of the van Genuchten (1980) model, especially when tested in the top soil layer.
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The area under the no-tillage system (NT) has been increasing over the last few years. Some authors indicate that stabilization of soil physical properties is reached after some years under NT while other authors debate this. The objective of this study was to determine the effect of the last crop in the rotation sequence (1st year: maize, 2nd year: soybean, 3rd year: wheat/soybean) on soil pore configuration and hydraulic properties in two different soils (site 1: loam, site 2: sandy loam) from the Argentinean Pampas region under long-term NT treatments in order to determine if stabilization of soil physical properties is reached apart from a specific time in the crop sequence. In addition, we compared two procedures for evaluating water-conducting macroporosities, and evaluated the efficiency of the pedotransfer function ROSETTA in estimating the parameters of the van Genuchten-Mualem (VGM) model in these soils. Soil pore configuration and hydraulic properties were not stable and changed according to the crop sequence and the last crop grown in both sites. For both sites, saturated hydraulic conductivity, K0, water-conducting macroporosity, εma, and flow-weighted mean pore radius, R0ma, increased from the 1st to the 2nd year of the crop sequence, and this was attributed to the creation of water-conducting macropores by the maize roots. The VGM model adequately described the water retention curve (WRC) for these soils, but not the hydraulic conductivity (K) vs tension (h) curve. The ROSETTA function failed in the estimation of these parameters. In summary, mean values of K0 ranged from 0.74 to 3.88 cm h-1. In studies on NT effects on soil physical properties, the crop effect must be considered.
Resumo:
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.
Resumo:
Citrus plants are the most important fruit species in the world, with emphasis to oranges, mandarins and lemons. In Rio Grande do Sul, Brazil, most fruit production is found on small properties under organic cultivation. Soil compaction is one of the factors limiting production and due to the fixed row placement of this crop, compaction can arise in various manners in the interrows of the orchard. The aim of this study was to evaluate soil physical properties and water infiltration capacity in response to interrow management in an orchard of mandarin (Citrus deliciosa Tenore 'Montenegrina') under organic cultivation. Interrow management was performed through harrowing, logs in em "V", mowing, and cutting/knocking down plants with a knife roller. Soil physical properties were evaluated in the wheel tracks of the tractor (WT), between the wheel tracks (BWT), and in the area under the line projection of the canopy (CLP), with undisturbed soil samples collected in the 0.00-0.15, 0.15-0.30, 0.30-0.45, and 0.45-0.60 m layers, with four replicates. The soil water infiltration test was performed using the concentric cylinder method, with a maximum time of 90 min for each test. In general, soil analysis showed a variation in the physical-hydraulic properties of the Argissolo Vermelho-Amarelo distrófico arênico (sandy loam Typic Paleudalf) in the three sampling sites in all layers, regardless of the management procedure in the interrows. Machinery traffic leads to heterogeneity in the soil physical-hydraulic properties in the interrows of the orchard. Soil porosity and bulk density are affected especially in the wheel tracks of the tractor (WT), which causes a reduction in the constant rate of infiltration and in the accumulated infiltration of water in this sampling site. The use of the disk harrow and mower leads to greater harmful effects on the soil, which can interfere with mandarin production.
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The spatial correlation between soil properties and weeds is relevant in agronomic and environmental terms. The analysis of this correlation is crucial for the interpretation of its meaning, for influencing factors such as dispersal mechanisms, seed production and survival, and the range of influence of soil management techniques. This study aimed to evaluate the spatial correlation between the physical properties of soil and weeds in no-tillage (NT) and conventional tillage (CT) systems. The following physical properties of soil and weeds were analyzed: soil bulk density, macroporosity, microporosity, total porosity, aeration capacity of soil matrix, soil water content at field capacity, weed shoot biomass, weed density, Commelina benghalensis density, and Bidens pilosa density. Generally, the ranges of the spatial correlations were higher in NT than in CT. The cross-variograms showed that many variables have a structure of combined spatial variation and can therefore be mapped from one another by co-kriging. This combined variation also allows inferences about the physical and biological meanings of the study variables. Results also showed that soil management systems influence the spatial dependence structure significantly.
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Soil microbial biomass (SMB) plays an important role in nutrient cycling in agroecosystems, and is limited by several factors, such as soil water availability. This study assessed the effects of soil water availability on microbial biomass and its variation over time in the Latossolo Amarelo concrecionário of a secondary forest in eastern Amazonia. The fumigation-extraction method was used to estimate the soil microbial biomass carbon and nitrogen content (SMBC and SMBN). An adaptation of the fumigation-incubation method was used to determine basal respiration (CO2-SMB). The metabolic quotient (qCO2) and ratio of microbial carbon:organic carbon (CMIC:CORG) were calculated based on those results. Soil moisture was generally significantly lower during the dry season and in the control plots. Irrigation raised soil moisture to levels close to those observed during the rainy season, but had no significant effect on SMB. The variables did not vary on a seasonal basis, except for the microbial C/N ratio that suggested the occurrence of seasonal shifts in the structure of the microbial community.