Soil physical properties and grape yield influenced by cover crops and management systems

The use of cover crops in vineyards is a conservation practice with the purpose of reducing soil erosion and improving the soil physical quality. The objective of this study was to evaluate cover crop species and management systems on soil physical properties and grape yield. The experiment was carried out in Bento Gonçalves, RS, Southern Brazil, on a Haplic Cambisol, in a vineyard established in 1989, using White and Rose Niagara grape (Vitis labrusca L.) in a horizontal, overhead trellis system. The treatments were established in 2002, consisting of three cover crops: spontaneous species (SS), black oat (Avena strigosa Schreb) (BO), and a mixture of white clover (Trifolium repens L.), red clover (Trifolium pratense L.) and annual rye-grass (Lolium multiflorum L.) (MC). Two management systems were applied: desiccation with herbicide (D) and mechanical mowing (M). Soil under a native forest (NF) area was collected as a reference. The experimental design consisted of completely randomized blocks, with three replications. The soil physical properties in the vine rows were not influenced by cover crops and were similar to the native forest, with good quality of the soil structure. In the inter-rows, however, there was a reduction in biopores, macroporosity, total porosity and an increase in soil density, related to the compaction of the surface soil layer. The M system increased soil aggregate stability compared to the D system. The treatments affected grapevine yield only in years with excess or irregular rainfall.

Physical quality of an Oxisol after different periods of management systems

Management systems may lead to a loss of soil physical quality as a result of removal of the plant cover and excessive agricultural mechanization. The hypothesis of this study was that the soil aggregate stability, bulk density, macro- and microporosity, and the S index and saturated hydraulic conductivity may be used as indicators of the soil physical quality. The aim was to study the effects of different periods and managements on the physical attributes of a medium-textured Red Oxisol under soybean and corn for two growing seasons, and determine which layers are most susceptible to variations. A completely randomized experimental design was used with split plots (five treatments and four layers), with four replications. The treatments in 2008/09 consisted of: five years of no-tillage (NTS5), seven years of no-tillage (NTS7), nine years of no-tillage (NTS9), conventional tillage (CTS) and an adjacent area of native forest (NF). The treatments were extended for another year, identified in 2009/10 as: NTS6, NTS8, NTS10, CTS and NF. The soil layers 0-0.05, 0.05-0.10, 0.10-0.20 and 0.20-0.30 m were sampled. The highest S index values were observed in the treatment CTS in the 0-0.05 m layer (0.106) and the 0.05-0.10 m layer (0.099) in 2008/09, and in the 0-0.05 m layer (0.066) in 2009/10. This fact may be associated with soil turnover, resulting in high macroporosity in this treatment. In contrast, in the NTS, limiting macroporosity values were observed in some layers (below 0.10 m³ m-3). Highest aggregate stability as well as the highest saturated hydraulic conductivity (Kθ) values were observed in NF in relation to the other treatments. In 2009/10, the Kθ in NF differed only from NTS10. This study showed that the use of the S index alone cannot be recommended as an absolute indicator of the soil physical quality, even at values greater than 0.035.

Influence of field slope and coffee plantation age on the physical properties of a red-yellow Latosol

In modern agriculture, several factors cause changes in the soil physical properties. The time of establishment of a crop (plantation age) and the slope are examples of factors that moderate the impact of mechanized operations on the soil structure. The objective of this study was to analyze the effect of machinery traffic on the physical properties of a Red-Yellow Latosol under coffee plantations with different ages (2, 7, 18, and 33 years) and slope positions (3, 9 and 15 %). Samples were collected from three positions between coffee rows (lower wheel track, inter-row and upper wheel track) and at two depths (surface layer and sub-surface). Changes in the total porosity, macroporosity, microporosity, organic matter, bulk density, and aggregate stability were investigated. Our results showed that the slope influenced the organic matter content, microporosity and aggregate stability. The soil samples under the inter-row were minimally damaged in their structure, compared to those from under the lower and upper wheel track, while the structure was better preserved under the lower than the upper track. The time since the establishment of the crop, i.e., the plantation age, was the main factor determining the extent of structural degradation in the coffee plantation.

Impacts of land leveling on lowland soil physical properties

The practice of land leveling alters the soil surface to create a uniform slope to improve land conditions for the application of all agricultural practices. The aims of this study were to evaluate the impacts of land leveling through the magnitudes, variances and spatial distributions of selected soil physical properties of a lowland area in the State of Rio Grande do Sul, Brazil; the relationships between the magnitude of cuts and/or fills and soil physical properties after the leveling process; and evaluation of the effect of leveling on the spatial distribution of the top of the B horizon in relation to the soil surface. In the 0-0.20 m layer, a 100-point geo-referenced grid covering two taxonomic soil classes was used in assessment of the following soil properties: soil particle density (Pd) and bulk density (Bd); total porosity (Tp), macroporosity (Macro) and microporosity (Micro); available water capacity (AWC); sand, silt, clay, and dispersed clay in water (Disp clay) contents; electrical conductivity (EC); and weighted average diameter of aggregates (WAD). Soil depth to the top of the B horizon was also measured before leveling. The overall effect of leveling on selected soil physical properties was evaluated by paired "t" tests. The effect on the variability of each property was evaluated through the homogeneity of variance test. The thematic maps constructed by kriging or by the inverse of the square of the distances were visually analyzed to evaluate the effect of leveling on the spatial distribution of the properties and of the top of the B horizon in relation to the soil surface. Linear regression models were fitted with the aim of evaluating the relationship between soil properties and the magnitude of cuts and fills. Leveling altered the mean value of several soil properties and the agronomic effect was negative. The mean values of Bd and Disp clay increased and Tp, Macro and Micro, WAD, AWC and EC decreased. Spatial distributions of all soil physical properties changed as a result of leveling and its effect on all soil physical properties occurred in the whole area and not specifically in the cutting or filling areas. In future designs of leveling, we recommend overlaying a cut/fill map on the map of soil depth to the top of the B horizon in order to minimize areas with shallow surface soil after leveling.

Physical Properties of a Hapludox after Three Decades under Different Soil Management Systems

ABSTRACT Changes in soil physical properties due to different management systems occur slowly, and long-term studies are needed to assess soil quality. The objectives of this study were to evaluate the effects of soil management systems and liming methods on the physical properties of a Latossolo Bruno Alumínico típico (Hapludox). A long-term experiment that began in 1978 with conventional and no-tillage systems was assessed. In addition, different liming methods (no lime, incorporated lime, and lime on the soil surface) have been applied since 1987 and were also evaluated in this study. Moreover, an area of native forest was evaluated and considered a reference for the natural condition of the soil. Soil physical properties were evaluated in layers to a depth of 1.00 m. Compared to native forest, the conventional tillage and no-tillage systems had higher soil bulk density, penetration resistance, and microporosity, and lower aggregate stability and macroporosity. Compared to the conventional tillage system, long-term no-tillage improved the structure of the Hapludox, as evidenced by increased microporosity and aggregate stability, especially in the soil surface layer. In no-tillage with lime applications sporadically incorporated, soil physical properties did not differ from no-tillage without lime and with lime applied on the soil surface, indicating that this practice maintains the physical quality of soil under no-tillage. Liming in a conventional tillage system improved soil aggregation and reduces penetration resistance in the soil layers near the soil surface. No-tillage was the main practice related to improvement of soil physical quality, and liming methods did not influence soil physical properties in this soil management system.

Sampling Position under No-Tillage System Affects the Results of Soil Physical Properties

ABSTRACT Understanding the spatial behavior of soil physical properties under no-tillage system (NT) is required for the adoption and maintenance of a sustainable soil management system. The aims of this study were to quantify soil bulk density (BD), porosity in the soil macropore domain (PORp) and in the soil matrix domain (PORm), air capacity in the soil matrix (ACm), field capacity (FC), and soil water storage capacity (FC/TP) in the row (R), interrow (IR), and intermediate position between R and IR (designated IP) in the 0.0-0.10 and 0.10-0.20 m soil layers under NT; and to verify if these soil properties have systematic variation in sampling positions related to rows and interrows of corn. Soil sampling was carried out in transect perpendicular to the corn rows in which 40 sampling points were selected at each position (R, IR, IP) and in each soil layer, obtaining undisturbed samples to determine the aforementioned soil physical properties. The influence of sampling position on systematic variation of soil physical properties was evaluated by spectral analysis. In the 0.0-0.1 m layer, tilling the crop rows at the time of planting led to differences in BD, PORp, ACm, FC and FC/TP only in the R position. In the R position, the FC/TP ratio was considered close to ideal (0.66), indicating good water and air availability at this sampling position. The R position also showed BD values lower than the critical bulk density that restricts root growth, suggesting good soil physical conditions for seed germination and plant establishment. Spectral analysis indicated that there was systematic variation in soil physical properties evaluated in the 0.0-0.1 m layer, except for PORm. These results indicated that the soil physical properties evaluated in the 0.0-0.1 m layer were associated with soil position in the rows and interrows of corn. Thus, proper assessment of soil physical properties under NT must take into consideration the sampling positions and previous location of crop rows and interrows.

Spatial variability of soil physical properties in two management systems in sugarcane crop

The aim of this study was to characterize the spatial variability of soil bulk density (Bd), soil moisture content (θ) and total porosity (Tp) in two management systems of sugarcane harvesting, with or without burning, in a Haplustox soil, in the 0-0.20 m layer. The study area is located in Rio Brilhante, state of Mato Grosso do Sul, Brazil, in Eldorado Sugar Mill. The plots have presented 180 m length, and 145.6 m width, totaling 90 points distributed in the form of a grid of nine rows by ten columns, with points spaced 20 m from its neighbor. Soil samples were collected at 0-0.20 m layer in 2007/2008 and 2008/2009 crops. The harvest with burning system had a higher density compared to mechanized harvest, in the two study periods. The moisture content as well as the porosity increased proportionally with the decrease of the density of the harvest burning system compared to the mechanized.

Effects of vinasse application under the physical attributes of soil covered with sugarcane straw

Areas under vinasse application have been associated to favorable physical conditions for root development, aeration, infiltration and water movement in soil profile. This study aimed to evaluate changes on physical attributes of soil under sugarcane straw after vinasse application in two sugarcane growing areas (Area 1 and Area 2) under mechanized management in the state of Paraíba, Brazil. In each area, the samples were collected in the 0-0.20, 0.20-0.40 and 0.40-0.60m layers of the soil, in 36 points, distributed in a 10×10m mesh, one day before and 40 days after vinasse application. The data were submitted to multivariate analysis with repeated measures and geostatistics. The vinasse application decreased soil density and increased total porosity in both Areas and increased organic matter in Area 2. In Area 1 occurred pure nugget effect for the fractions of sand, silt and clay, independent of soil layer. In Area 2, this effect was verified mostly at superficial layers, except for the fraction of clay that presented a moderate degree of spatial dependence.

Soil physical attributes in chemigated banana plantation with wastewater

ABSTRACT The feasibility of using sewage wastewater as a water and nutrient source for plants is an alternative to harness agricultural natural resource, observing its influence on the organic matter dynamics and soil energy. Our objective here was to evaluate the effects of applying different doses of effluent from a sewage treatment plant, in Janaúba – MG, Brazil, over the physical attributes of a soil grown with “Prata Anã” banana. From soil sample collection at depths of 0-20, 20-40, and 40-60 cm, we determined the following soil properties: soil density, total porosity, macroporosity, microporosity, organic matter, clay dispersed in water and stability of soil aggregate. The experimental design was in randomized blocks with four repetitions. Wastewater raising doses promoted increase in suspended solids, contributing to macroporosity reduction at 20-40 and 40-60 cm depths; as well as a reduction in organic matter within 0-20 cm layer. Clay dispersal was observed in the depths of 0-20 cm, being derived from an increase in sodium content. Concurrently, there was a reduction of soil aggregate stability.

Non-Linear Unsteady Aerodynamic Response Approximation Using Multi-Layer Functionals

Non-linear functional representation of the aerodynamic response provides a convenient mathematical model for motion-induced unsteady transonic aerodynamic loads response, that accounts for both complex non-linearities and time-history effects. A recent development, based on functional approximation theory, has established a novel functional form; namely, the multi-layer functional. For a large class of non-linear dynamic systems, such multi-layer functional representations can be realised via finite impulse response (FIR) neural networks. Identification of an appropriate FIR neural network model is facilitated by means of a supervised training process in which a limited sample of system input-output data sets is presented to the temporal neural network. The present work describes a procedure for the systematic identification of parameterised neural network models of motion-induced unsteady transonic aerodynamic loads response. The training process is based on a conventional genetic algorithm to optimise the network architecture, combined with a simplified random search algorithm to update weight and bias values. Application of the scheme to representative transonic aerodynamic loads response data for a bidimensional airfoil executing finite-amplitude motion in transonic flow is used to demonstrate the feasibility of the approach. The approach is shown to furnish a satisfactory generalisation property to different motion histories over a range of Mach numbers in the transonic regime.

Detection of Horizontal Two-Phase Flow Patterns Through a Neural Network Model

One of the main problems related to the transport and manipulation of multiphase fluids concerns the existence of characteristic flow patterns and its strong influence on important operation parameters. A good example of this occurs in gas-liquid chemical reactors in which maximum efficiencies can be achieved by maintaining a finely dispersed bubbly flow to maximize the total interfacial area. Thus, the ability to automatically detect flow patterns is of crucial importance, especially for the adequate operation of multiphase systems. This work describes the application of a neural model to process the signals delivered by a direct imaging probe to produce a diagnostic of the corresponding flow pattern. The neural model is constituted of six independent neural modules, each of which trained to detect one of the main horizontal flow patterns, and a last winner-take-all layer responsible for resolving when two or more patterns are simultaneously detected. Experimental signals representing different bubbly, intermittent, annular and stratified flow patterns were used to validate the neural model.

Artificial neural network models for predicting 1-year mortality in elderly patients with intertrochanteric fractures in China

The mortality rate of older patients with intertrochanteric fractures has been increasing with the aging of populations in China. The purpose of this study was: 1) to develop an artificial neural network (ANN) using clinical information to predict the 1-year mortality of elderly patients with intertrochanteric fractures, and 2) to compare the ANN's predictive ability with that of logistic regression models. The ANN model was tested against actual outcomes of an intertrochanteric femoral fracture database in China. The ANN model was generated with eight clinical inputs and a single output. ANN's performance was compared with a logistic regression model created with the same inputs in terms of accuracy, sensitivity, specificity, and discriminability. The study population was composed of 2150 patients (679 males and 1471 females): 1432 in the training group and 718 new patients in the testing group. The ANN model that had eight neurons in the hidden layer had the highest accuracies among the four ANN models: 92.46 and 85.79% in both training and testing datasets, respectively. The areas under the receiver operating characteristic curves of the automatically selected ANN model for both datasets were 0.901 (95%CI=0.814-0.988) and 0.869 (95%CI=0.748-0.990), higher than the 0.745 (95%CI=0.612-0.879) and 0.728 (95%CI=0.595-0.862) of the logistic regression model. The ANN model can be used for predicting 1-year mortality in elderly patients with intertrochanteric fractures. It outperformed a logistic regression on multiple performance measures when given the same variables.