A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazil

Geographical information systems (GIS) are tools that have been recently tested for improving our understanding of the spatial distribution of disease. The objective of this paper was to further develop the GIS technology to model and control schistosomiasis using environmental, social, biological and remote-sensing variables. A final regression model (R² = 0.39) was established, after a variable selection phase, with a set of spatial variables including the presence or absence of Biomphalaria glabrata, winter enhanced vegetation index, summer minimum temperature and percentage of houses with water coming from a spring or well. A regional model was also developed by splitting the state of Minas Gerais (MG) into four regions and establishing a linear regression model for each of the four regions: 1 (R² = 0.97), 2 (R² = 0.60), 3 (R² = 0.63) and 4 (R² = 0.76). Based on these models, a schistosomiasis risk map was built for MG. In this paper, geostatistics was also used to make inferences about the presence of Biomphalaria spp. The result was a map of species and risk areas. The obtained risk map permits the association of uncertainties, which can be used to qualify the inferences and it can be thought of as an auxiliary tool for public health strategies.

Genetic compatibility between Anopheles lesteri from Korea and Anopheles paraliae from Thailand

To assess differentiation and relationships between Anopheles lesteri and Anopheles paraliae we established three and five iso-female lines of An. lesteri from Korea and An. paraliae from Thailand, respectively. These isolines were used to investigate the genetic relationships between the two taxa by crossing experiments and by comparing DNA sequences of ribosomal DNA second internal transcribed spacer (ITS2) and mitochondrial DNA cytochrome c oxidase subunit I (COI) and subunit II (COII). Results of reciprocal and F1-hybrid crosses between An. lesteri and An. paraliae indicated that they were compatible genetically producing viable progenies and complete synaptic salivary gland polytene chromosomes without inversion loops in all chromosome arms. The pairwise genetic distances of ITS2, COI and COII between these morphological species were 0.040, 0.007-0.017 and 0.008-0.011, respectively. The specific species status of An. paraliae in Thailand and/or other parts of the continent are discussed.

The TcI and TcII Trypanosoma cruzi experimental infections induce distinct immune responses and cardiac fibrosis in dogs

Trypanosoma cruzi infection may be caused by different strains with distinct discrete typing units (DTUs) that can result in variable clinical forms of chronic Chagas disease. The present study evaluates the immune response and cardiac lesions in dogs experimentally infected with different T. cruzi strains with distinct DTUs, namely, the Colombian (Col) and Y strains of TcI and TcII DTU, respectively. During infection with the Col strain, increased levels of alanine aminotransferase, erythrocytes, haematocrit and haemoglobin were observed. In addition, CD8+ T-lymphocytes isolated from the peripheral blood produced higher levels of interleukin (IL)-4. The latter suggests that during the acute phase, infection with the Col strain may remain unnoticed by circulating mononuclear cells. In the chronic phase, a significant increase in the number of inflammatory cells was detected in the right atrium. Conversely, infection with the Y strain led to leucopoenia, thrombopoenia, inversion of the ratio of CD4+/CD8+ T-lymphocytes and alterations in monocyte number. The Y strain stimulated the production of interferon-γ by CD4+ and CD8+ T-lymphocytes and IL-4 by CD8+ T-cells. In the chronic phase, significant heart inflammation and fibrosis were observed, demonstrating that strains of different DTUs interact differently with the host.

Anopheles darlingi polytene chromosomes: revised maps including newly described inversions and evidence for population structure in Manaus

Salivary gland polytene chromosomes of 4th instar Anopheles darlingi Root were examined from multiple locations in the Brazilian Amazon. Minor modifications were made to existing polytene photomaps. These included changes to the breakpoint positions of several previously described paracentric inversions and descriptions of four new paracentric inversions, two on the right arm of chromosome 3 and two on the left arm of chromosome 3 that were found in multiple locations. A total of 18 inversions on the X (n = 1) chromosome, chromosome 2 (n = 7) and 3 (n = 11) were scored for 83 individuals from Manaus, Macapá and Porto Velho municipalities. The frequency of 2Ra inversion karyotypes in Manaus shows significant deficiency of heterozygotes (p < 0.0009). No significant linkage disequilibrium was found between inversions on chromosome 2 and 3. We hypothesize that at least two sympatric subpopulations exist within the An. darlingi population at Manaus based on inversion frequencies.

Spatial variability of the chemical, physical and biological properties in lowland cultivated with irrigated rice

In the areas where irrigated rice is grown in the south of Brazil, few studies have been carried out to investigate the spatial variability structure of soil properties and to establish new forms of soil management as well as determine soil corrective and fertilizer applications. In this sense, this study had the objective of evaluating the spatial variability of chemical, physical and biological soil properties in a lowland area under irrigated rice cultivation in the conventional till system. For this purpose, a 10 x 10 m grid of 100 points was established, in an experimental field of the Embrapa Clima Temperado, in the County of Capão do Leão, State of Rio Grande do Sul. The spatial variability structure was evaluated by geostatistical tools and the number of subsamples required to represent each soil property in future studies was calculated using classical statistics. Results showed that the spatial variability structure of sand, silt, SMP index, cation exchange capacity (pH 7.0), Al3+ and total N properties could be detected by geostatistical analysis. A pure nugget effect was observed for the nutrients K, S and B, as well as macroporosity, mean weighted diameter of aggregates, and soil water storage. The cross validation procedure, based on linear regression and the determination coefficient, was more efficient to evaluate the quality of the adjusted mathematical model than the degree of spatial dependence. It was also concluded that the combination of classical with geostatistics can in many cases simplify the soil sampling process without losing information quality.

Spatial variability of soil chemical properties after coffee tree removal

Assessing the spatial variability of soil chemical properties has become an important aspect of soil management strategies with a view to higher crop yields with minimal environmental degradation. This study was carried out at the Centro Experimental of the Instituto Agronomico, in Campinas, São Paulo, Brazil. The aim was to characterize the spatial variability of chemical properties of a Rhodic Hapludox on a recently bulldozer-cleaned area after over 30 years of coffee cultivation. Soil samples were collected in a 20 x 20 m grid with 36 sampling points across a 1 ha area in the layers 0.0-0.2 and 0.2-0.4 m to measure the following chemical properties: pH, organic matter, K+, P, Ca2+, Mg2+, potential acidity, NH4-N, and NO3-N. Descriptive statistics were applied to assess the central tendency and dispersion moments. Geostatistical methods were applied to evaluate and to model the spatial variability of variables by calculating semivariograms and kriging interpolation. Spatial dependence patterns defined by spherical model adjusted semivariograms were made for all cited soil properties. Moderate to strong degrees of spatial dependence were found between 31 and 60 m. It was still possible to map soil spatial variability properties in the layers 0-20 cm and 20-40 cm after plant removal with bulldozers.

Diagnostic techniques applied in geostatistics for agricultural data analysis

The structural modeling of spatial dependence, using a geostatistical approach, is an indispensable tool to determine parameters that define this structure, applied on interpolation of values at unsampled points by kriging techniques. However, the estimation of parameters can be greatly affected by the presence of atypical observations in sampled data. The purpose of this study was to use diagnostic techniques in Gaussian spatial linear models in geostatistics to evaluate the sensitivity of maximum likelihood and restrict maximum likelihood estimators to small perturbations in these data. For this purpose, studies with simulated and experimental data were conducted. Results with simulated data showed that the diagnostic techniques were efficient to identify the perturbation in data. The results with real data indicated that atypical values among the sampled data may have a strong influence on thematic maps, thus changing the spatial dependence structure. The application of diagnostic techniques should be part of any geostatistical analysis, to ensure a better quality of the information from thematic maps.

Spatial and temporal variability of crop yield and some Rhodic Hapludox properties under no-tillage

Soil properties are closely related with crop production and spite of the measures implemented, spatial variation has been repeatedly observed and described. Identifying and describing spatial variations of soil properties and their effects on crop yield can be a powerful decision-making tool in specific land management systems. The objective of this research was to characterize the spatial and temporal variations in crop yield and chemical and physical properties of a Rhodic Hapludox soil under no-tillage. The studied area of 3.42 ha had been cultivated since 1985 under no-tillage crop rotation in summer and winter. Yield and soil property were sampled in a regular 10 x 10 m grid, with 302 sample points. Yields of several crops were analyzed (soybean, maize, triticale, hyacinth bean and castor bean) as well as soil chemical (pH, Soil Organic Matter (SOM), P, Ca2+, Mg2+, H + Al, B, Fe, Mn, Zn, CEC, sum of bases (SB), and base saturation (V %)) and soil physical properties (saturated hydraulic conductivity, texture, density, total porosity, and mechanical penetration resistance). Data were analyzed using geostatistical analysis procedures and maps based on interpolation by kriging. Great variation in crop yields was observed in the years evaluated. The yield values in the Northern region of the study area were high in some years. Crop yields and some physical and soil chemical properties were spatially correlated.

Pedotransfer functions related to spatial variability of water retention attributes for lowland soils

The estimation of non available soil variables through the knowledge of other related measured variables can be achieved through pedotransfer functions (PTF) mainly saving time and reducing cost. Great differences among soils, however, can yield non desirable results when applying this method. This study discusses the application of developed PTFs by several authors using a variety of soils of different characteristics, to evaluate soil water contents of two Brazilian lowland soils. Comparisons are made between PTF evaluated data and field measured data, using statistical and geostatistical tools, like mean error, root mean square error, semivariogram, cross-validation, and regression coefficient. The eight tested PTFs to evaluate gravimetric soil water contents (Ug) at the tensions of 33 kPa and 1,500 kPa presented a tendency to overestimate Ug 33 kPa and underestimate Ug1,500 kPa. The PTFs were ranked according to their performance and also with respect to their potential in describing the structure of the spatial variability of the set of measured values. Although none of the PTFs have changed the distribution pattern of the data, all resulted in mean and variance statistically different from those observed for all measured values. The PTFs that presented the best predictive values of Ug33 kPa and Ug1,500 kPa were not the same that had the best performance to reproduce the structure of spatial variability of these variables.

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.

Multivariate analysis and geostatistics of the fertility of a humic rhodic hapludox under coffee cultivation

The spatial variability of soil and plant properties exerts great influence on the yeld of agricultural crops. This study analyzed the spatial variability of the fertility of a Humic Rhodic Hapludox with Arabic coffee, using principal component analysis, cluster analysis and geostatistics in combination. The experiment was carried out in an area under Coffea arabica L., variety Catucai 20/15 - 479. The soil was sampled at a depth 0.20 m, at 50 points of a sampling grid. The following chemical properties were determined: P, K+, Ca2+, Mg2+, Na+, S, Al3+, pH, H + Al, SB, t, T, V, m, OM, Na saturation index (SSI), remaining phosphorus (P-rem), and micronutrients (Zn, Fe, Mn, Cu and B). The data were analyzed with descriptive statistics, followed by principal component and cluster analyses. Geostatistics were used to check and quantify the degree of spatial dependence of properties, represented by principal components. The principal component analysis allowed a dimensional reduction of the problem, providing interpretable components, with little information loss. Despite the characteristic information loss of principal component analysis, the combination of this technique with geostatistical analysis was efficient for the quantification and determination of the structure of spatial dependence of soil fertility. In general, the availability of soil mineral nutrients was low and the levels of acidity and exchangeable Al were high.

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.

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.

Mineralogy of the clay fraction of Alfisols in two slope curvatures: III - spatial variability

A good knowledge of the spatial distribution of clay minerals in the landscape facilitates the understanding of the influence of relief on the content and crystallographic attributes of soil minerals such as goethite, hematite, kaolinite and gibbsite. This study aimed at describing the relationships between the mineral properties of the clay fraction and landscape shapes by determining the mineral properties of goethite, hematite, kaolinite and gibbsite, and assessing their dependence and spatial variability, in two slope curvatures. To this end, two 100 × 100 m grids were used to establish a total of 121 regularly spaced georeferenced sampling nodes 10 m apart. Samples were collected from the layer 0.0-0.2 m and analysed for iron oxides, and kaolinite and gibbsite in the clay fraction. Minerals in the clay fraction were characterized from their X-ray diffraction (XRD) patterns, which were interpreted and used to calculate the width at half height (WHH) and mean crystallite dimension (MCD) of iron oxides, kaolinite, and gibbsite, as well as aluminium substitution and specific surface area (SSA) in hematite and goethite. Additional calculations included the goethite and hematite contents, and the goethite/(goethite+hematite) [Gt/(Gt+Hm)] and kaolinite/(kaolinite+gibbsite) [Kt/(Kt+Gb)] ratios. Mineral properties were established by statistical analysis of the XRD data, and spatial dependence was assessed geostatistically. Mineralogical properties differed significantly between the convex area and concave area. The geostatistical analysis showed a greater number of mineralogical properties with spatial dependence and a higher range in the convex than in the concave area.

Sugarcane trash management assessed by the interaction of yield with soil properties

Currently, sugarcane plays an important global role, particularly with a view to alternative energy sources. Thus, in a sugarcane field of the mill Vale do Paraná S/A Álcool e Açúcar, Rubineia, São Paulo State, managed under two green cane harvest systems (cane trash left on and cane trash removed from the soil), Pearson and spatial correlations between the sugarcane yield (variety RB855035 in the third cut) and soil physical and chemical properties were studied to identify the property best correlated with stalk yield and the best harvest method. For this purpose, two geostatistical grids (121 sampling points on 1.30 ha) were installed on a eutrophic Red Argisol (homogeneous slope of 0.065 m m-1), in 2011, to determine the properties: stalk yield and sugarcane plant population, and soil resistance to penetration, gravimetric moisture, bulk density, and carbon stock, in the layers 0-0.20 and 0.20-0.40 m. The data were analyzed by descriptive, linear correlation and geostatistical analysis. In both treatments, the property stand density was best correlated with sugarcane yield (r = 0.725 in the trash mulching treatment - TM and r = 0.769 in the trash removal treatment - TR). However, in relation to the soil properties, bulk density (0-0.20 m) was best correlated (r = 0.305 in TM, r = 0.211 in TR). Similarly, from the spatial point of view, stand density was the property that best explained the sugarcane yield. However, in the TM treatment the density (0.20-0.40 m) was the only soil property spatially correlated with stalk yield. The carbon stock in the soil of the TM was 11.5 % higher than in the TR treatment. Results of the TM treatment were best, also with regard to soil management and conservation.