Desenvolvimento e análise de uma rede neural artificial para estimativa da erosividade da chuva para o Estado de São Paulo

O conhecimento do valor da erosividade da chuva (R) de determinada localidade é fundamental para a estimativa das perdas de solo feitas a partir da Equação Universal de Perdas de Solo, sendo, portanto, de grande importância no planejamento conservacionista. A fim de obter estimativas do valor de R para localidades onde este é desconhecido, desenvolveu-se uma rede neural artificial (RNA) e analisou-se a acurácia desta com o método de interpolação "Inverso de uma Potência da Distância" (ID). Comparando a RNA desenvolvida com o método de interpolação ID, verificou-se que a primeira apresentou menor erro relativo médio na estimativa de R e melhor índice de confiança, classificado como "Ótimo", podendo, portanto, ser utilizada no planejamento de uso, manejo e conservação do solo no Estado de São Paulo.

Root abundance of maize in conventionally-tilled and zero-tilled soils of Argentina

Maize root growth is negatively affected by compacted layers in the surface (e.g. agricultural traffic) and subsoil layers (e.g. claypans). Both kinds of soil mechanical impedances often coexist in maize fields, but the combined effects on root growth have seldom been studied. Soil physical properties and maize root abundance were determined in three different soils of the Rolling Pampa of Argentina, in conventionally-tilled (CT) and zero-tilled (ZT) fields cultivated with maize. In the soil with a light Bt horizon (loamy Typic Argiudoll, Chivilcoy site), induced plough pans were detected in CT plots at a depth of 0-0.12 m through significant increases in bulk density (1.15 to 1.27 Mg m-3) and cone (tip angle of 60 º) penetrometer resistance (7.18 to 9.37 MPa in summer from ZT to CT, respectively). This caused a reduction in maize root abundance of 40-80 % in CT compared to ZT plots below the induced pans. Two of the studied soils had hard-structured Bt horizons (clay pans), but in only one of them (silty clay loam Abruptic Argiudoll, Villa Lía site) the expected penetrometer resistance increases (up to 9 MPa) were observed with depth. In the other clay pan soil (silty clay loam Vertic Argiudoll, Pérez Millán site), penetrometer resistance did not increase with depth but reached 14.5 MPa at 0.075 and 0.2 m depth in CT and ZT plots, respectively. However, maize root abundance was stratified in the first 0.2 m at the Villa Lía and Pérez Millán sites. There, the hard Bt horizons did not represent an absolute but a relative mechanical impedance to maize roots, by the observed root clumping through desiccation cracks.

Rugosidade da superfície do solo sob diferentes sistemas de manejo e influenciada por chuva artificial

A rugosidade da superfície do solo é influenciada pelo manejo, formada em especial pelo tipo de preparo e reduzida pela ação da chuva, principalmente. O objetivo deste estudo foi avaliar a influência de diferentes sistemas de manejo do solo e da aplicação de chuva artificial na rugosidade da superfície do solo. Os tratamentos estudados resultaram da combinação de três sistemas de manejo do solo, semeadura direta (SD), preparo convencional (PC) e cultivo mínimo (CM), com três doses de resíduo vegetal seco de soja (Glycine max L. Merrill): 0, 2 e 4 Mg ha-1. Nas unidades experimentais foram aplicadas sete chuvas, com intensidade de precipitação pluvial de 60 mm h-1 e duração de 60 min cada, totalizando 420 mm de lâmina de chuva. A rugosidade foi avaliada imediatamente antes e após o preparo do solo e imediatamente após a aplicação de cada uma das sete chuvas artificiais. Obtiveram-se valores do índice de rugosidade ao acaso entre 1,88 e 5,41 mm na semeadura direta; entre 3,88 e 8,30 mm no preparo convencional; e entre 8,99 e 17,45 mm no cultivo mínimo. Concluiu-se que: as operações de preparo do solo aumentaram a rugosidade da sua superfície, em geral; o cultivo mínimo foi o sistema de preparo do solo que proporcionou os maiores valores de rugosidade ao acaso; e nos tratamentos semeadura direta com cobertura do solo a ação da chuva não promoveu decaimento do microrrelevo do solo.

Temporal variability of soil water content under different surface conditions in the semiarid region of the Pernambuco state

Rainfall in the semiarid region of Pernambuco is characterized by irregular distribution in time and space, which significantly hinders the rainfed agriculture in the region. This work aims to evaluate the temporal profile of soil moisture in the semiarid region of the Pernambuco State (Brazil) and the effect of different soil surface conditions on soil water content variation and the yield of rainfed beans. To monitor soil water content, five plots 4.5 m wide by 11 m long were installed in a Yellow Argisol (Ultisol). The following treatments were adopted in the experimental plots: natural vegetation, bean intercropped with cactus, beans planted down the slope, beans planted along contour lines with mulch and rock barriers, and bare soil. In each plot, eight PVC access tubes were installed for monitoring the soil water content profile at depths of 0.20 and 0.40 m using a neutron probe device. The surface condition significantly influenced the soil water content variation, both in the dry and rainy seasons. The use of mulch, associated with rock barriers, provided higher soil water content levels than the other treatments and increased the rainfed beans production.

New methods to quantify NH3 volatilization from fertilized surface soil with urea

Gaseous N losses from soil are considerable, resulting mostly from ammonia volatilization linked to agricultural activities such as pasture fertilization. The use of simple and accessible measurement methods of such losses is fundamental in the evaluation of the N cycle in agricultural systems. The purpose of this study was to evaluate quantification methods of NH3 volatilization from fertilized surface soil with urea, with minimal influence on the volatilization processes. The greenhouse experiment was arranged in a completely randomized design with 13 treatments and five replications, with the following treatments: (1) Polyurethane foam (density 20 kg m-3) with phosphoric acid solution absorber (foam absorber), installed 1, 5, 10 and 20 cm above the soil surface; (2) Paper filter with sulfuric acid solution absorber (paper absorber, 1, 5, 10 and 20 cm above the soil surface); (3) Sulfuric acid solution absorber (1, 5 and 10 cm above the soil surface); (4) Semi-open static collector; (5) 15N balance (control). The foam absorber placed 1 cm above the soil surface estimated the real daily rate of loss and accumulated loss of NH3N and proved efficient in capturing NH3 volatized from urea-treated soil. The estimates based on acid absorbers 1, 5 and 10 cm above the soil surface and paper absorbers 1 and 5 cm above the soil surface were only realistic for accumulated N-NH3 losses. Foam absorbers can be indicated to quantify accumulated and daily rates of NH3 volatilization losses similarly to an open static chamber, making calibration equations or correction factors unnecessary.

Relations between soil surface roughness, tortuosity, tillage treatments, rainfall intensity and soil and water losses from a red yellow latosol

The soil surface roughness increases water retention and infiltration, reduces the runoff volume and speed and influences soil losses by water erosion. Similarly to other parameters, soil roughness is affected by the tillage system and rainfall volume. Based on these assumptions, the main purpose of this study was to evaluate the effect of tillage treatments on soil surface roughness (RR) and tortuosity (T) and to investigate the relationship with soil and water losses in a series of simulated rainfall events. The field study was carried out at the experimental station of EMBRAPA Southeastern Cattle Research Center in São Carlos (Fazenda Canchim), in São Paulo State, Brazil. Experimental plots of 33 m² were treated with two tillage practices in three replications, consisting of: untilled (no-tillage) soil (NTS) and conventionally tilled (plowing plus double disking) soil (CTS). Three successive simulated rain tests were applied in 24 h intervals. The three tests consisted of a first rain of 30 mm/h, a second of 30 mm/h and a third rain of 70 mm/h. Immediately after tilling and each rain simulation test, the surface roughness was measured, using a laser profile meter. The tillage treatments induced significant changes in soil surface roughness and tortuosity, demonstrating the importance of the tillage system for the physical surface conditions, favoring water retention and infiltration in the soil. The increase in surface roughness by the tillage treatments was considerably greater than its reduction by rain action. The surface roughness and tortuosity had more influence on the soil volume lost by surface runoff than in the conventional treatment. Possibly, other variables influenced soil and water losses from the no-tillage treatments, e.g., soil type, declivity, slope length, among others not analyzed in this study.

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.

Surface mapping, organic matter and water stocks in peatlands of the Serra do Espinhaço meridional - Brazil

Peatlands are soil environments that store carbon and large amounts of water, due to their composition (90 % water), low hydraulic conductivity and a sponge-like behavior. It is estimated that peat bogs cover approximately 4.2 % of the Earth's surface and stock 28.4 % of the soil carbon of the planet. Approximately 612 000 ha of peatlands have been mapped in Brazil, but the peat bogs in the Serra do Espinhaço Meridional (SdEM) were not included. The objective of this study was to map the peat bogs of the northern part of the SdEM and estimate the organic matter pools and water volume they stock. The peat bogs were pre-identified and mapped by GIS and remote sensing techniques, using ArcGIS 9.3, ENVI 4.5 and GPS Track Maker Pro software and the maps validated in the field. Six peat bogs were mapped in detail (1:20,000 and 1:5,000) by transects spaced 100 m and each transect were determined every 20 m, the UTM (Universal Transverse Mercator) coordinates, depth and samples collected for characterization and determination of organic matter, according to the Brazilian System of Soil Classification. In the northern part of SdEM, 14,287.55 ha of peatlands were mapped, distributed over 1,180,109 ha, representing 1.2 % of the total area. These peatlands have an average volume of 170,021,845.00 m³ and stock 6,120,167 t (428.36 t ha-1) of organic matter and 142,138,262 m³ (9,948 m³ ha-1) of water. In the peat bogs of the Serra do Espinhaço Meridional, advanced stages of decomposing (sapric) organic matter predominate, followed by the intermediate stage (hemic). The vertical growth rate of the peatlands ranged between 0.04 and 0.43 mm year-1, while the carbon accumulation rate varied between 6.59 and 37.66 g m-2 year-1. The peat bogs of the SdEM contain the headwaters of important water bodies in the basins of the Jequitinhonha and San Francisco Rivers and store large amounts of organic carbon and water, which is the reason why the protection and preservation of these soil environments is such an urgent and increasing need.

Iron oxidation on the surface of adventitious roots and its relation to aerenchyma formation in rice genotypes

Establishment of the water layer in an irrigated rice crop leads to consumption of free oxygen in the soil which enters in a chemical reduction process mediated by anaerobic microorganisms, changing the crop environment. To maintain optimal growth in an environment without O2, rice plants develop pore spaces (aerenchyma) that allow O2 transport from air to the roots. Carrying capacity is determined by the rice genome and it may vary among cultivars. Plants that have higher capacity for formation of aerenchyma should theoretically carry more O2 to the roots. However, part of the O2 that reaches the roots is lost due to permeability of the roots and the O2 gradient created between the soil and roots. The O2 that is lost to the outside medium can react with chemically reduced elements present in the soil; one of them is iron, which reacts with oxygen and forms an iron plaque on the outer root surface. Therefore, evaluation of the iron plaque and of the formation of pore spaces on the root can serve as a parameter to differentiate rice cultivars in regard to the volume of O2 transported via aerenchyma. An experiment was thus carried out in a greenhouse with the aim of comparing aerenchyma and iron plaque formation in 13 rice cultivars grown in flooded soils to their formation under growing conditions similar to a normal field, without free oxygen. The results indicated significant differences in the volume of pore spaces in the roots among cultivars and along the root segment in each cultivar, indicating that under flooded conditions the genetic potential of the plant is crucial in induction of cell death and formation of aerenchyma in response to lack of O2. In addition, the amount of Fe accumulated on the root surface was different among genotypes and along the roots. Thus, we concluded that the rice genotypes exhibit different responses for aerenchyma formation, oxygen release by the roots and iron plaque formation, and that there is a direct relationship between porosity and the amount of iron oxidized on the root surface.

Available content, surface runoff and leaching of phosphorus forms in a typic hapludalf treated with organic and mineral nutrient sources

The application of animal manure to soil can increase phosphorus availability to plants and enhance transfer of the nutrient solution drained from the soil surface or leached into the soil profile. The aim of this study was to evaluate the effect of successive applications of organic and mineral nutrient sources on the available content, surface runoff and leaching of P forms in a Typic Hapludalf in no-tillage systems. Experiment 1 was set up in 2004 in the experimental area of UFSM, in Santa Maria (RS, Brazil). The treatments consisted of: control (without nutrient application) and application of pig slurry (PS), pig deep-litter (PL), cattle slurry (CS), and mineral fertilizers (NPK). The rates were determined to meet the N crop requirements of no-tillage black oat and maize, grown in the 2010/2011 growing season. The soil solution was collected after each event (rain + runoff or leaching) and the soluble, particulate and total P contents were measured. In November 2008, soil was collected in 2 cm intervals to a depth of 20 cm, in 5 cm intervals to a depth of 40 cm, and in 10 cm intervals to a depth of 70 cm. The soil was dried and ground, and P determined after extraction by anion exchange resin (AER). In experiment 2, samples collected from the Typic Hapludalf near experiment 1 were incubated for 20, 35, 58, 73 and 123 days after applying the following treatments: soil, soil + PS, soil + PL, soil + CS and soil + NPK. Thereafter, the soil was sampled and P was analyzed by AER. The applications of nutrient sources over the years led to an increase in available P and its migration in the soil profile. This led to P transfer via surface runoff and leaching, with the largest transfer being observed in PS and PL treatments, in which most P was applied. The soil available P and P transfer via surface runoff were correlated with the amounts applied, regardless of the P source. However, P transfer by leaching was not correlated with the applied nutrient amount, but rather with the solution amount leached in the soil profile.

Quality of surface water related to land use: a case study in a catchment with small farms and intensive vegetable crop production in southern Brazil

Water degradation is strongly related to agricultural activity. The aim of this study was to evaluate the influence of land use and some environmental components on surface water quality in the Campestre catchment, located in Colombo, state of Parana, Brazil. Physical and chemical attributes were analyzed (total nitrogen, ammonium, nitrate, total phosphorus, electrical conductivity, pH, temperature, turbidity, total solids, biological oxygen demand, chemical oxygen demand and dissolved oxygen). Monthly samples of the river water were taken over one year at eight monitoring sites, distributed over three sub-basins. Overall, water quality was worse in the sub-basin with a higher percentage of agriculture, and was also affected by a lower percentage of native forest and permanent preservation area, and a larger drainage area. Water quality was also negatively affected by the presence of agriculture in the riparian zone. In the summer season, probably due to higher rainfall and intensive soil use, a higher concentration of total nitrogen and particulate nitrogen was observed, as well as higher electrical conductivity, pH and turbidity. All attributes, except for total phosphorus, were in compliance with Brazilian Conama Resolution Nº 357/2005 for freshwater class 1. However, it should be noted that these results referred to the base flow and did not represent a discharge condition since most of the water samples were not collected at or near the rainfall event.

Soil fertility, nutrition and yield of maize and barley with gypsum application on soil surface in no-till

Annual crop yield and nutrition have shown differentiated responses to modifications in soil chemical properties brought about by gypsum application. The aim of this study was to evaluate the effect of gypsum application rates on the chemical properties of a Latossolo Bruno (Clayey Oxisol), as well as on the nutrition and yield of a maize-barley succession under no-till. The experiment was set up in November 2009 in Guarapuava, Parana, Brazil, applying gypsum rates of 0.0, 1.5, 3.0, 4.5, and 6.0 Mg ha-1 to the soil surface upon sowing maize, with crop succession of barley. Gypsum application decreased the levels of Al3+ and Mg2+ in the 0.0-0.1 m layer and increased soil pH in the layers from 0.2-0.6 m depth. Gypsum application has increased the levels of Ca2+ in all soil layers up to 0.6 m, and the levels of S-SO4(2-) up to 0.8 m. In both crops, the leaf concentrations of Ca and S were increased while Mg concentrations have decreased as a function of gypsum rates. There was also an effect of gypsum rates on grain yield, with a quadratic response of maize and a linear increase for barley. Yield increases were up to 11 and 12 % in relation to control for the maximum technical efficiency (MTE) rates of 3.8 and 6.0 Mg ha-1 of gypsum, respectively. Gypsum application improved soil fertility in the profile, especially in the subsurface, as well as plant nutrition, increasing the yields of maize and barley.

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy

Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

Effects of surface application of calcium-magnesium silicate and gypsum on soil fertility and sugarcane yield

Lime application recommendations for amendment of soil acidity in sugarcane were developed with a burnt cane harvesting system in mind. Sugarcane is now harvested in most areas without burning, and lime application for amendment of soil acidity in this system in which the sugarcane crop residue remains on the ground has been carried out without a scientific basis. The aim of this study was to evaluate the changes in soil acidity and stalk and sugar yield with different rates of surface application of calcium, magnesium silicate, and gypsum in ratoon cane. The experiment was performed after the 3rd harvest of the variety SP 81-3250 in a commercial green sugarcane plantation of the São Luiz Sugar Mill (47º 25' 33" W; 21º 59' 46" S), located in Pirassununga, São Paulo, in southeast Brazil. A factorial arrangement of four Ca-Mg silicate rates (0, 850, 1700, and 3400 kg ha-1) and two gypsum rates (0 and 1700 kg ha-1) was used in the experiment. After 12 months, the experiment was harvested and technological measurements of stalk and sugar yield were made. After harvest, soil samples were taken at the depths of 0.00-0.05, 0.05-0.10, 0.10-0.20, 0.20-0.40, and 0.40-0.60 m in all plots, and the following determinations were made: soil pH in CaCl2, organic matter, P, S, K, Ca, Mg, H+Al, Al, Si, and base saturation. The results show that the application of gypsum reduced the exchangeable Al3+ content and Al saturation below 0.05 m, and increased the Ca2+ concentration in the whole profile, the Mg2+ content below 0.10 m, K+ below 0.4 m, and base saturation below 0.20 m. This contributed to the effect of surface application of silicate on amendment of soil acidity reaching deeper layers. From the results of this study, it may be concluded that the silicate rate recommended may be too low, since the greater rates used in this experiment showed greater reduction in soil acidity, higher levels of nutrients at greater depths and an increase in stalk and sugar yield.