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.

Semivariogram models for estimating fig fly population density throughout the year

The objective of this work was to select semivariogram models to estimate the population density of fig fly (Zaprionus indianus; Diptera: Drosophilidae) throughout the year, using ordinary kriging. Nineteen monitoring sites were demarcated in an area of 8,200 m2, cropped with six fruit tree species: persimmon, citrus, fig, guava, apple, and peach. During a 24 month period, 106 weekly evaluations were done in these sites. The average number of adult fig flies captured weekly per trap, during each month, was subjected to the circular, spherical, pentaspherical, exponential, Gaussian, rational quadratic, hole effect, K-Bessel, J-Bessel, and stable semivariogram models, using ordinary kriging interpolation. The models with the best fit were selected by cross-validation. Each data set (months) has a particular spatial dependence structure, which makes it necessary to define specific models of semivariograms in order to enhance the adjustment to the experimental semivariogram. Therefore, it was not possible to determine a standard semivariogram model; instead, six theoretical models were selected: circular, Gaussian, hole effect, K-Bessel, J-Bessel, and stable.

Spatial variability of the rainfall erosive potential in the State of Mato Grosso do Sul, Brazil

Information about rainfall erosivity is important during soil and water conservation planning. Thus, the spatial variability of rainfall erosivity of the state Mato Grosso do Sul was analyzed using ordinary kriging interpolation. For this, three pluviograph stations were used to obtain the regression equations between the erosivity index and the rainfall coefficient EI30. The equations obtained were applied to 109 pluviometric stations, resulting in EI30 values. These values were analyzed from geostatistical technique, which can be divided into: descriptive statistics, adjust to semivariogram, cross-validation process and implementation of ordinary kriging to generate the erosivity map.Highest erosivity values were found in central and northeast regions of the State, while the lowest values were observed in the southern region. In addition, high annual precipitation values not necessarily produce higher erosivity values.

Soil penetration resistance analysis by multivariate and geostatistical methods

The penetration resistance (PR) is a soil attribute that allows identifies areas with restrictions due to compaction, which results in mechanical impedance for root growth and reduced crop yield. The aim of this study was to characterize the PR of an agricultural soil by geostatistical and multivariate analysis. Sampling was done randomly in 90 points up to 0.60 m depth. It was determined spatial distribution models of PR, and defined areas with mechanical impedance for roots growth. The PR showed a random distribution to 0.55 and 0.60 m depth. PR in other depths analyzed showed spatial dependence, with adjustments to exponential and spherical models. The cluster analysis that considered sampling points allowed establishing areas with compaction problem identified in the maps by kriging interpolation. The analysis with main components identified three soil layers, where the middle layer showed the highest values of PR.

Scaling of semivariograms and the kriging estimation of field-measured properties

Two methods were evaluated for scaling a set of semivariograms into a unified function for kriging estimation of field-measured properties. Scaling is performed using sample variances and sills of individual semivariograms as scale factors. Theoretical developments show that kriging weights are independent of the scaling factor which appears simply as a constant multiplying both sides of the kriging equations. The scaling techniques were applied to four sets of semivariograms representing spatial scales of 30 x 30 m to 600 x 900 km. Experimental semivariograms in each set successfully coalesced into a single curve by variances and sills of individual semivariograms. To evaluate the scaling techniques, kriged estimates derived from scaled semivariogram models were compared with those derived from unscaled models. Differences in kriged estimates of the order of 5% were found for the cases in which the scaling technique was not successful in coalescing the individual semivariograms, which also means that the spatial variability of these properties is different. The proposed scaling techniques enhance interpretation of semivariograms when a variety of measurements are made at the same location. They also reduce computational times for kriging estimations because kriging weights only need to be calculated for one variable. Weights remain unchanged for all other variables in the data set whose semivariograms are scaled.

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.

Optimization of the sampling scheme for maps of physical and chemical properties estimated by kriging

The sampling scheme is essential in the investigation of the spatial variability of soil properties in Soil Science studies. The high costs of sampling schemes optimized with additional sampling points for each physical and chemical soil property, prevent their use in precision agriculture. The purpose of this study was to obtain an optimal sampling scheme for physical and chemical property sets and investigate its effect on the quality of soil sampling. Soil was sampled on a 42-ha area, with 206 geo-referenced points arranged in a regular grid spaced 50 m from each other, in a depth range of 0.00-0.20 m. In order to obtain an optimal sampling scheme for every physical and chemical property, a sample grid, a medium-scale variogram and the extended Spatial Simulated Annealing (SSA) method were used to minimize kriging variance. The optimization procedure was validated by constructing maps of relative improvement comparing the sample configuration before and after the process. A greater concentration of recommended points in specific areas (NW-SE direction) was observed, which also reflects a greater estimate variance at these locations. The addition of optimal samples, for specific regions, increased the accuracy up to 2 % for chemical and 1 % for physical properties. The use of a sample grid and medium-scale variogram, as previous information for the conception of additional sampling schemes, was very promising to determine the locations of these additional points for all physical and chemical soil properties, enhancing the accuracy of kriging estimates of the physical-chemical properties.

Three-dimensional interpolation of soil data: fertility and pedomorphological features in southern Brazil

The graphical representation of spatial soil properties in a digital environment is complex because it requires a conversion of data collected in a discrete form onto a continuous surface. The objective of this study was to apply three-dimension techniques of interpolation and visualization on soil texture and fertility properties and establish relationships with pedogenetic factors and processes in a slope area. The GRASS Geographic Information System was used to generate three-dimensional models and ParaView software to visualize soil volumes. Samples of the A, AB, BA, and B horizons were collected in a regular 122-point grid in an area of 13 ha, in Pinhais, PR, in southern Brazil. Geoprocessing and graphic computing techniques were effective in identifying and delimiting soil volumes of distinct ranges of fertility properties confined within the soil matrix. Both three-dimensional interpolation and the visualization tool facilitated interpretation in a continuous space (volumes) of the cause-effect relationships between soil texture and fertility properties and pedological factors and processes, such as higher clay contents following the drainage lines of the area. The flattest part with more weathered soils (Oxisols) had the highest pH values and lower Al3+ concentrations. These techniques of data interpolation and visualization have great potential for use in diverse areas of soil science, such as identification of soil volumes occurring side-by-side but that exhibit different physical, chemical, and mineralogical conditions for plant root growth, and monitoring of plumes of organic and inorganic pollutants in soils and sediments, among other applications. The methodological details for interpolation and a three-dimensional view of soil data are presented here.

Knowledge management: uncovering risky gaps underlying the criticisms and moving to another perspective

The comments related to the sustainability of knowledge management (KM) have shown signs that it possibly can be a discourse which determines a quick style, but otherwise have also allowed the building of a better understanding about the limits and weaknesses of the knowlege management. In addition to the criticisms, the conceptual bases of knowledge management have been undermined by a contradictory combination of paradigms; there are also contradictions between the theoretical perspective jubjacent to the knwoledge management and its operationality. As a way of minimizing the possibility that the knowledge management may be turned into an umbrella concept and fail, it is suggested that its approaches embody a more interpretative perspective, taking up the role of an instrument which enables and facilitates the processes and practices in building up knowledge and information, enhancing their focus on the support to the establishment of human competences in order to deal intelligently with the present overcharge of information resources and need for building up information in the organizations.

Software for interpolation of vegetative growth of yerba mate plants in 3D

The objective of this work was to build mock-ups of complete yerba mate plants in several stages of development, using the InterpolMate software, and to compute photosynthesis on the interpolated structure. The mock-ups of yerba-mate were first built in the VPlants software for three growth stages. Male and female plants grown in two contrasting environments (monoculture and forest understory) were considered. To model the dynamic 3D architecture of yerba-mate plants during the biennial growth interval between two subsequent prunings, data sets of branch development collected in 38 dates were used. The estimated values obtained from the mock-ups, including leaf photosynthesis and sexual dimorphism, are very close to those observed in the field. However, this similarity was limited to reconstructions that included growth units from original data sets. The modeling of growth dynamics enables the estimation of photosynthesis for the entire yerba mate plant, which is not easily measurable in the field. The InterpolMate software is efficient for building yerba mate mock-ups.

Influence of a multideficient diet from northeastern Brazil on resting blood pressure and baroreflex sensitivity in conscious, freely moving rats

The "regional basic diet" or RBD is a multideficient diet (providing 8% protein) which is known to produce dietary deficiencies in some populations in northeastern Brazil. The present study investigated the effects of RBD-induced malnutrition on resting blood pressure and baroreflex sensitivity in conscious rats. Malnourished rats were obtained by feeding dams the RBD during mating and pregnancy (RBD-1 group) or during nursing and a 10-day period after weaning (RBD-2 group). At 90 days of age, only RBD-2 rats weighed significantly (P<0.001) less than control rats born to dams fed a standard commercial diet (23% protein) during pregnancy and nursing. Baseline mean arterial pressure and heart rate of both RBD-1 and RBD-2 rats were comparable to those of controls. The slopes for both reflex bradycardia and tachycardia (bpm/mmHg) induced by intravenous phenylephrine and sodium nitroprusside, respectively, were unchanged in either RBD-1 (-2.08 ± 0.11 and -3.10 ± 0.43, respectively) or RBD-2 (-2.32 ± 0.30 and -3.73 ± 0.53, respectively) rats, when compared to controls (-2.09 ± 0.10 and -3.17 ± 0.33, respectively). This study shows that, after a prolonged period of nutritional recovery, the patterns of resting blood pressure and baroreflex sensitivity of both pre- and postnatally malnourished rats were similar to those of controls. The decreased body weight and the tendency to increased reflex tachycardia in RBD-2 rats may suggest that this type of maternal malnutrition during lactation is more critical than during pregnancy.

A brain microdialysis study on 5-HT release in freely moving rat lines selectively bred for differential 5-HT1A receptor function

Breeding for high and low hypothermic responses to systemic administration of a serotonin1A (5-HT1A) receptor agonist (8-hydroxy-2-(di-n-propylamino)tetralin, 8-OH-DPAT) has resulted in high DPAT-sensitive (HDS) and low DPAT-sensitive (LDS) lines of rats, respectively. These lines also differ in several behavioral measures associated with stress. In the present microdialysis study we observed that basal 5-HT concentrations in the prefrontal cortex and dorsal hippocampus did not differ significantly between HDS and LDS rats. Thus, behavioral differences between the HDS and LDS lines might not be attributed to differences in basal 5-HT release. However, both lines had lower basal levels of 5-HT release than their randomly bred control group (random DPAT-sensitive, RDS) in the prefrontal cortex (mean ± SEM, pg/20 µl, was 3.0 ± 0.4 for LDS, 3.8 ± 0.3 for HDS and 6.4 ± 0.6 for RDS; F(2,59) = 5.8, P<0.005). The administration of (±)-fenfluramine (10 mg/kg) induced a greater increase in hippocampal 5-HT levels in HDS rats (500%) as compared with LDS (248%) or RDS (243%) rats (P<0.0001). There were no significant differences in the prefrontal cortex among lines, with a fenfluramine-induced 5-HT increase of about 900% in the three groups. This differential response to fenfluramine may be due to functional alterations of hippocampal 5-HT reuptake sites in the HDS line.

Comparative effects of organic and inorganic mercury on in vivo dopamine release in freely moving rats

The present study was carried out in order to compare the effects of administration of organic (methylmercury, MeHg) and inorganic (mercury chloride, HgCl 2 ) forms of mercury on in vivo dopamine (DA) release from rat striatum. Experiments were performed in conscious and freely moving female adult Sprague-Dawley (230-280 g) rats using brain microdialysis coupled to HPLC with electrochemical detection. Perfusion of different concentrations of MeHg or HgCl 2 (2 µL/min for 1 h, N = 5-7/group) into the striatum produced significant increases in the levels of DA. Infusion of 40 µM, 400 µM, or 4 mM MeHg increased DA levels to 907 ± 31, 2324 ± 156, and 9032 ± 70% of basal levels, respectively. The same concentrations of HgCl 2 increased DA levels to 1240 ± 66, 2500 ± 424, and 2658 ± 337% of basal levels, respectively. These increases were associated with significant decreases in levels of dihydroxyphenylacetic acid and homovallinic acid. Intrastriatal administration of MeHg induced a sharp concentration-dependent increase in DA levels with a peak 30 min after injection, whereas HgCl 2 induced a gradual, lower (for 4 mM) and delayed increase in DA levels (75 min after the beginning of perfusion). Comparing the neurochemical profile of the two mercury derivatives to induce increases in DA levels, we observed that the time-course of these increases induced by both mercurials was different and the effect produced by HgCl 2 was not concentration-dependent (the effect was the same for the concentrations of 400 µM and 4 mM HgCl 2 ). These results indicate that HgCl 2 produces increases in extracellular DA levels by a mechanism differing from that of MeHg.

Emerging Latin America

This paper is specially dedicated to the students of management of the world. After outlining the historical, demographic, and physical aspects of Latin America, the authors establish and use a framework to describe and explain the modern economic, social, and political development of this region. The paper is firmly grounded on the historical dimensions of contemporary Latin America. Its background is the context of an exceptionally fast-moving global economy.