Method to estimate soil macroporosity and microporosity based on sand content and bulk density

Macroporosity is often used in the determination of soil compaction. Reduced macroporosity can lead to poor drainage, low root aeration and soil degradation. The aim of this study was to develop and test different models to estimate macro and microporosity efficiently, using multiple regression. Ten soils were selected within a large range of textures: sand (Sa) 0.07-0.84; silt 0.03-0.24; clay 0.13-0.78 kg kg-1 and subjected to three compaction levels (three bulk densities, BD). Two models with similar accuracy were selected, with a mean error of about 0.02 m³ m-3 (2 %). The model y = a + b.BD + c.Sa, named model 2, was selected for its simplicity to estimate Macro (Ma), Micro (Mi) or total porosity (TP): Ma = 0.693 - 0.465 BD + 0.212 Sa; Mi = 0.337 + 0.120 BD - 0.294 Sa; TP = 1.030 - 0.345 BD 0.082 Sa; porosity values were expressed in m³ m-3; BD in kg dm-3; and Sa in kg kg-1. The model was tested with 76 datum set of several other authors. An error of about 0.04 m³ m-3 (4 %) was observed. Simulations of variations in BD as a function of Sa are presented for Ma = 0 and Ma = 0.10 (10 %). The macroporosity equation was remodeled to obtain other compaction indexes: a) to simulate maximum bulk density (MBD) as a function of Sa (Equation 11), in agreement with literature data; b) to simulate relative bulk density (RBD) as a function of BD and Sa (Equation 13); c) another model to simulate RBD as a function of Ma and Sa (Equation 16), confirming the independence of this variable in relation to Sa for a fixed value of macroporosity and, also, proving the hypothesis of Hakansson & Lipiec that RBD = 0.87 corresponds approximately to 10 % macroporosity (Ma = 0.10 m³ m-3).

Soil phosphorus dynamics and availability and irrigated coffee yield

Research data have demonstrated that the P demand of coffee (Coffea arabica L.) is similar to that of short-cycle crops. In this context, the objective of this study was to evaluate the influence of annual P fertilization on the soil P status by the quantification of labile, moderately labile, low-labile, and total P fractions, associating them to coffee yield. The experiment was installed in a typical dystrophic Red Latosol (Oxisol) cultivated with irrigated coffee annually fertilized with triple superphosphate at rates of 0, 50, 100, 200, and 400 kg ha-1 P2O5. Phosphorus fractions were determined in two soil layers: 0-10 and 10-20 cm. The P leaf contents and coffee yield in 2008 were also evaluated. The irrigated coffee responded to phosphate fertilization in the production phase with gains of up to 138 % in coffee yield by the application of 400 kg ha-1 P2O5. Coffee leaf P contents increased with P applications and stabilized around 1.98 g kg-1, at rates of 270 kg ha-1 P2O5 and higher. Soil P application caused, in general, an increase in bioavailable P fractions, which constitute the main soil P reservoir.

Determination of hydraulic properties of a tropical soil of Hawaii using column experiments and inverse modeling

A method for determining soil hydraulic properties of a weathered tropical soil (Oxisol) using a medium-sized column with undisturbed soil is presented. The method was used to determine fitting parameters of the water retention curve and hydraulic conductivity functions of a soil column in support of a pesticide leaching study. The soil column was extracted from a continuously-used research plot in Central Oahu (Hawaii, USA) and its internal structure was examined by computed tomography. The experiment was based on tension infiltration into the soil column with free outflow at the lower end. Water flow through the soil core was mathematically modeled using a computer code that numerically solves the one-dimensional Richards equation. Measured soil hydraulic parameters were used for direct simulation, and the retention and soil hydraulic parameters were estimated by inverse modeling. The inverse modeling produced very good agreement between model outputs and measured flux and pressure head data for the relatively homogeneous column. The moisture content at a given pressure from the retention curve measured directly in small soil samples was lower than that obtained through parameter optimization based on experiments using a medium-sized undisturbed soil column.

Implications of the variability in soil penetration resistance for statistical analysis

Soil penetration resistance (PR) is a measure of soil compaction closely related to soil structure and plant growth. However, the variability in PR hampers the statistical analyses. This study aimed to evaluate the variability of soil PR on the efficiency of parametric and nonparametric analyses in indentifying significant effects of soil compaction and to classify the coefficient of variation of PR into low, medium, high and very high. On six dates, the PR of a typical dystrophic Red Ultisol under continuous no-tillage for 16 years was measured. Three tillage and/or traffic conditions were established with the application of: (i) no chiseling or additional traffic, (ii) additional compaction, and (iii) chiseling. On each date, the nineteen PR data (measured at every 1.5 cm to a depth of 28.5 cm) were grouped in layers with different thickness. In each layer, the treatment effects were evaluated by variance (ANOVA) and Kruskal-Wallis analyses in a completely randomized design, and the coefficients of variation of all analyses were classified (low, intermediate, high and very high). The ANOVA performed better in discriminating the compaction effects, but the rejection rate of null hypothesis decreased from 100 to 80 % when the coefficient of variation increased from 15 to 26 %. The values of 15 and 26 % were the thresholds separating the low/intermediate and the high/very high coefficient variation classes of PR in this Ultisol.

Hydraulic conductivity and soil-sewage sludge interactions

One of the main problems faced by humanity is pollution caused by residues resulting from the production and use of goods, e.g, sewage sludge. Among the various alternatives for its disposal, the agricultural use seems promising. The purpose of this study was to evaluate the hydraulic conductivity and interaction of soil with sandy-silty texture, classified as Spodosols, from the Experimental Station Itapirema - IPA, in Goiana, state of Pernambuco, in mixtures with sewage sludge from the Mangueira Sewage Treatment Station, in the city of Recife, Pernambuco at rates of 25, 50 and 75 Mg ha-1. Tests were conducted to let water percolate the natural saturated soil and soil-sludge mixtures to characterize their physical, chemical, and microstructural properties as well as hydraulic conductivity. Statistical data analysis showed that the presence of sewage sludge in soils leads to an increase of the < 0.005 mm fraction, reduction in real specific weight and variation in optimum moisture content from 11.60 to 12.90 % and apparent specific dry weight from 17.10 and 17.50 kN m-3. In the sludge-soil mixture, the quartz grains were covered by sludge and filling of the empty soil macropores between grains. There were changes in the chemical characteristics of soil and effluent due to sewage sludge addition and a small decrease in hydraulic conductivity. The results indicate the possibility that soil acidity influenced the concentrations of the elements found in the leachate, showing higher levels at higher sludge doses. It can be concluded that the leaching degree of potentially toxic elements from the sewage sludge treatments does not harm the environment.

Chemical and structural characterization of soil humic substances under agroforestry and conventional systems

Studies have proven that the agroforestry systems in the semi-arid region of the State of Ceará, Brazil, induce an increase in soil organic C levels. Notwithstanding, there is no information if this increase also results in qualitative changes in different pools of soil organic matter. The objective of this study was to verify the possible chemical and structural alterations in fulvic and humic acids of a Luvisol in areas adopting agroforestry, traditional intensive cultivation and native forest in a long-term experiment conducted in the semi-arid region of Ceará State, Brazil. The study was conducted in an experimental area of the National Goat Research Center (Embrapa) in Sobral, CE. The following treatments were evaluated: agrosilvopasture (AGP), silvopasture (SILV), intensive cultivation under fallow (ICF), and areas with native forest (NF). Soil fulvic and humic acids fractions were extracted from the 0-6 and 6-12 cm layers and characterized by elemental composition, thermogravimetry and infrared spectroscopy analyses. The elemental composition analysis of humic acids confirmed the data found for fulvic acids, showing reduction in the C, H and N levels, followed by an increase in O contents in the AGP and ICF treatments over SILV and NF. In all treatments, except to SILV in the 0-6 cm layer, the percentage of mass loss was highest (300-600 °C) for humic acids in the thermally most stable region. Despite the similarity between infrared spectra, soil fulvic acids in the SILV treatment extracted from 6-12 cm depth decrease the absorption bands at 1708 and 1408 cm-1 followed by an increase in the absorption band at 1608 cm-1 attributed to aromatic C=C groups. This behavior suggests an increase in the aromatic character of the structure. The AGP and ICF treatments, which increase the soil tilling, favored the maintenance of humic substances with a more aromatic character in the soil than SILV and NF. The less aromatic humic substances in the SILV treatment resulted in an increase of exchange sites of soil organic matter, indicating improved nutrient cycling and maintenance of productivity in the system.

Local influence for spatial analysis of soil physical properties and soybean yield using student's t-distribution

The modeling and estimation of the parameters that define the spatial dependence structure of a regionalized variable by geostatistical methods are fundamental, since these parameters, underlying the kriging of unsampled points, allow the construction of thematic maps. One or more atypical observations in the sample data can affect the estimation of these parameters. Thus, the assessment of the combined influence of these observations by the analysis of Local Influence is essential. The purpose of this paper was to propose local influence analysis methods for the regionalized variable, given that it has n-variate Student's t-distribution, and compare it with the analysis of local influence when the same regionalized variable has n-variate normal distribution. These local influence analysis methods were applied to soil physical properties and soybean yield data of an experiment carried out in a 56.68 ha commercial field in western Paraná, Brazil. Results showed that influential values are efficiently determined with n-variate Student's t-distribution.

Influence of organic-mineral fertilization of an oxisol on soil chemical properties and Bracharia brizantha production

The use of organic-mineral fertilizer produced by the manufacturing industry of lysine and threonine amino acids can improve the fertility of tropical soils. The objective of this study was to evaluate the influence of different doses of the organic-mineral fertilizer named Ajifer L-14 on chemical properties and on the response with increased production of a forage on a Red Latosol in the northwestern region of São Paulo State, Brazil. A randomized block design was used with seven treatments and four replications. The treatments consisted of: T1- control (without application of Ajifer L-14); T2- control (natural vegetation); T3- mineral fertilization according to crop requirements and soil analysis (application of 1.35 kg plot-1 of urea, 2.20 single superphosphate, and 0.51 KCl, corresponding to 60 of N, 40 P2O5 and 30 kg ha-1 of K2O); T4- fertilization with Ajifer L-14 according to the recommendation resulting from the soil chemical analysis (40 L plot-1, corresponding to 60 kg ha-1 N); T5- fertilization with Ajifer L-14, at a rate of 150 % of the recommended values (60 L plot-1, corresponding to 90 kg ha-1 N); T6- fertilization with Ajifer L-14 at a rate of 50 % of the recommended values (20 L plot-1, corresponding to 30 kg ha-1 N); T7- fertilization with Ajifer L-14 at a rate of 125 % of the recommended values (50 L plot-1, corresponding to 75 kg ha-1 N); T8- fertilization with Ajifer L-14 at a rate of 75 % of the recommended values (30 L plot-1, corresponding to 45 kg ha-1 N). The following soil chemical properties were evaluated (layers 0.0-0.1 and 0.1-0.2 m): P, organic matter, pH, K+, Ca2+, Mg2+, cation exchange capacity, potential acidity, and base saturation. The application of this organic-mineral fertilizer does not influence the soil chemical properties. Regression analysis indicated a polynomial relationship between the application rates of organic-mineral fertilizer and the production of dry matter and crude protein of Bracharia Brizantha.

Spatial relationships between soil attributes and corn yield in no-tillage system

Soil properties play an important role in spatial variability of crop yield. However, a low spatial correlation has generally been observed between maps of crop yield and of soil properties. The objectives of the present investigation were to assess the spatial pattern variability of soil properties and of corn yield at the same sampling intensity, and evaluate its cause-and-effect relationships. The experimental site was structured in a grid of 100 referenced points, spaced at 10 m intervals along four parallel 250 m long rows spaced 4.5 m apart. Thus, points formed a rectangle containing four columns and 25 rows. Therefore, each sampling cell encompassed an area of 45 m² and consisted of five 10 m long crop rows, in which the referenced points represented the center. Samples were taken from the layers 0-0.1 m and 0.1-0.2 m. Soil physical and chemical properties were evaluated. Statistical analyses consisted of data description and geostatistics. The spatial dependence of corn yield and soil properties was confirmed. The hypothesis of this study was confirmed, i.e., when sampling the soil to determine the values of soil characteristics at similar to sampling intensity as for crop yield assessments, correlations between the spatial distribution of soil characteristics and crop yield were observed. The spatial distribution pattern of soil properties explained 65 % of the spatial distribution pattern of corn yield. The spatial distribution pattern of clay content and percentage of soil base saturation explained most of the spatial distribution pattern of corn yield.

Spatial and linear correlations between soil and corn

The Technologies setting at Agricultural production system have the main characteristics the vertical productivity, reduced costs, soil physical, chemical and biological improvement to promote production sustainable growth. Thus, the study aimed to determine the variability and the linear and special correlations between the plant and soil attributes in order to select and indicate good representation of soil physical quality for forage productivity. In the growing season of 2006, on the Fazenda Bonança in Pereira Barreto (SP), the productivity of autumn corn forage (FDM) in an irrigated no-tillage system and the soil physical properties were analyzed. The purpose was to study the variability and the linear and spatial correlations between the plant and soil properties, to select an indicator of soil physical quality related to corn forage yield. A geostatistical grid was installed to collect soil and plant data, with 125 sampling points in an area of 2,500 m². The results show that the studied properties did not vary randomly and that data variability was low to very high, with well-defined spatial patterns, ranging from 7.8 to 38.0 m. On the other hand, the linear correlation between the plant and the soil properties was low and highly significant. The pairs forage dry matter versus microporosity and stem diameter versus bulk density were best correlated in the 0-0.10 m layer, while the other pairs - forage dry matter versus macro - and total porosity - were inversely correlated in the same layer. However, from the spatial point of view, there was a high inverse correlation between forage dry matter with microporosity, so that microporosity in the 0-0.10 m layer can be considered a good indicator of soil physical quality, with a view to corn forage yield.

Performance of a reciprocal shaker in mechanical dispersion of soil samples for particle-size analysis

The dispersion of the samples in soil particle-size analysis is a fundamental step, which is commonly achieved with a combination of chemical agents and mechanical agitation. The purpose of this study was to evaluate the efficiency of a low-speed reciprocal shaker for the mechanical dispersion of soil samples of different textural classes. The particle size of 61 soil samples was analyzed in four replications, using the pipette method to determine the clay fraction and sieving to determine coarse, fine and total sand fractions. The silt content was obtained by difference. To evaluate the performance, the results of the reciprocal shaker (RSh) were compared with data of the same soil samples available in reports of the Proficiency testing for Soil Analysis Laboratories of the Agronomic Institute of Campinas (Prolab/IAC). The accuracy was analyzed based on the maximum and minimum values defining the confidence intervals for the particle-size fractions of each soil sample. Graphical indicators were also used for data comparison, based on dispersion and linear adjustment. The descriptive statistics indicated predominantly low variability in more than 90 % of the results for sand, medium-textured and clay samples, and for 68 % of the results for heavy clay samples, indicating satisfactory repeatability of measurements with the RSh. Medium variability was frequently associated with silt, followed by the fine sand fraction. The sensitivity analyses indicated an accuracy of 100 % for the three main separates (total sand, silt and clay), in all 52 samples of the textural classes heavy clay, clay and medium. For the nine sand soil samples, the average accuracy was 85.2 %; highest deviations were observed for the silt fraction. In relation to the linear adjustments, the correlation coefficients of 0.93 (silt) or > 0.93 (total sand and clay), as well as the differences between the angular coefficients and the unit < 0.16, indicated a high correlation between the reference data (Prolab/IAC) and results obtained with the RSh. In conclusion, the mechanical dispersion by the reciprocal shaker of soil samples of different textural classes was satisfactory. The results allowed recommending the use of the equipment at low agitation for particle size- analysis. The advantages of this Brazilian apparatus are its low cost, the possibility to simultaneously analyze a great number of samples using ordinary, easily replaceable glass or plastic bottles.

Correction of resistance to penetration by pedofunctions and a reference soil water content

The soil penetration resistance is an important indicator of soil compaction and is strongly influenced by soil water content. The objective of this study was to develop mathematical models to normalize soil penetration resistance (SPR), using a reference value of gravimetric soil water content (U). For this purpose, SPR was determined with an impact penetrometer, in an experiment on a Dystroferric Red Latossol (Rhodic Eutrudox), at six levels of soil compaction, induced by mechanical chiseling and additional compaction by the traffic of a harvester (four, eight, 10, and 20 passes); in addition to a control treatment under no-tillage, without chiseling or additional compaction. To broaden the range of U values, SPR was evaluated in different periods. Undisturbed soil cores were sampled to quantify the soil bulk density (BD). Pedotransfer functions were generated correlating the values of U and BD to the SPR values. By these functions, the SPR was adequately corrected for all U and BD data ranges. The method requires only SPR and U as input variables in the models. However, different pedofunctions are needed according to the soil layer evaluated. After adjusting the pedotransfer functions, the differences in the soil compaction levels among the treatments, previously masked by variations of U, became detectable.

Strategy of specification of management areas: rice grain yield as related to soil fertility

It is well-known nowadays that soil variability can influence crop yields. Therefore, to determine specific areas of soil management, we studied the Pearson and spatial correlations of rice grain yield with organic matter content and pH of an Oxisol (Typic Acrustox) under no- tillage, in the 2009/10 growing season, in Selvíria, State of Mato Grosso do Sul, in the Brazilian Cerrado (longitude 51º24' 21'' W, latitude 20º20' 56'' S). The upland rice cultivar IAC 202 was used as test plant. A geostatistical grid was installed for soil and plant data collection, with 120 sampling points in an area of 3.0 ha with a homogeneous slope of 0.055 m m-1. The properties rice grain yield and organic matter content, pH and potential acidity and aluminum content were analyzed in the 0-0.10 and 0.10-0.20 m soil layers. Spatially, two specific areas of agricultural land management were discriminated, differing in the value of organic matter and rice grain yield, respectively with fertilization at variable rates in the second zone, a substantial increase in agricultural productivity can be obtained. The organic matter content was confirmed as a good indicator of soil quality, when spatially correlated with rice grain yield.

Soil losses from typic cambisols and red latosol as related to three erosive rainfall patterns

Rainfall erosivity is one of the main factors related to water erosion in the tropics. This work focused on relating soil loss from a typic dystrophic Tb Haplic Cambisol (CXbd) and a typic dystrophic Red Latosol (LVdf) to different patterns of natural erosive rainfall. The experimental plots of approximately 26 m² (3 x 8.67 m) consisted of a CXbd area with a 0.15 m m-1 slope and a LVdf area with 0.12 m m-1 slope, both delimited by galvanized plates. Drainpipes were installed at the lower part of these plots to collect runoff, interconnected with a Geib or multislot divisor. To calculate erosivity (EI30), rainfall data, recorded continuously at a weather station in Lavras, were used. The data of erosive rainfall events were measured (10 mm precipitation intervals, accuracy 0.2 mm, 24 h period, 20 min intervals), characterized as rainfall events with more than 10 mm precipitation, maximum intensity > 24 mm h-1 within 15 min, or kinetic energy > 3.6 MJ, which were used in this study to calculate the rainfall erosivity parameter, were classified according to the moment of peak precipitation intensity in advanced, intermediate and delayed patterns. Among the 139 erosive rainfall events with CXbd soil loss, 60 % were attributed to the advanced pattern, with a loss of 415.9 Mg ha-1, and total losses of 776.0 Mg ha-1. As for the LVdf, of the 93 erosive rainfall events with soil loss, 58 % were listed in the advanced pattern, with 37.8 Mg ha-1 soil loss and 50.9 Mg ha-1 of total soil loss. The greatest soil losses were observed in the advanced rain pattern, especially for the CXbd. From the Cambisol, the soil loss per rainfall event was greatest for the advanced pattern, being influenced by the low soil permeability.

Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.