Particulate soil organic carbon and stratification ratio increases in response to crop residue decomposition under no-till

In soils under no-tillage (NT), the continuous crop residue input to the surface layer leads to carbon (C) accumulation. This study evaluated a soil under NT in Ponta Grossa (State of Paraná, Brazil) for: 1) the decomposition of black oat (Avena strigosa Schreb.) residues, 2) relation of the biomass decomposition effect with the soil organic carbon (SOC) content, the particulate organic carbon (POC) content, and the soil carbon stratification ratio (SR) of an Inceptisol. The assessments were based on seven samplings (t0 to t6) in a period of 160 days of three transects with six sampling points each. The oat dry biomass was 5.02 Mg ha-1 at t0, however, after 160 days, only 17.8 % of the initial dry biomass was left on the soil surface. The SOC in the 0-5 cm layer varied from 27.56 (t0) to 30.07 g dm-3 (t6). The SR increased from 1.33 to 1.43 in 160 days. There was also an increase in the POC pool in this period, from 8.1 to 10.7 Mg ha-1. The increase in SOC in the 0-5 cm layer in the 160 days was mainly due to the increase of POC derived from oat residue decomposition. The linear relationship between SOC and POC showed that 21 % of SOC was due to the more labile fraction. The results indicated that the continuous input of residues could be intensified to increase the C pool and sequestration in soils under NT.

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.

Wheat yield and physical properties of a brown latosol under no-tillage in south-central Paraná

Soil management influences the chemical and physical properties of soil. Chemical conditions have been thoroughly studied, while the role of soil physical conditions regarding crop yield has been neglected. This study aimed to analyze the wheat yield and its relationship with physical properties of an Oxisol under no-tillage (NT). The study was carried out between 2010 and 2011, in Reserva do Iguaçu, State of Paraná, Brazil, on the Campo Bonito farm, after 25 years of NT management. Based on harvest maps of barley (2006), wheat (2007) and maize (2009) of a plot (150 ha), zones with higher and lower yield potential (Z1 and Z2, respectively) were identified. Sampling grids with 16 units (50 x 50 m) and three sampling points per unit were established. The wheat grain yield (GY) and water infiltration capacity (WIC) were evaluated in 2010. Soil samples with disturbed and undisturbed structure were collected from the 0.00-0.10 and 0.10-0.20 m layers. The former were used to determine soil organic carbon (Corg) levels and the latter to determine soil bulk density (BD), total porosity (TP), macroporosity (Mac), and microporosity (Mic). Soil penetration resistance (PR) and water content (SWC) were also evaluated. The wheat GY of the whole plot was close to the regional average and the yield between the zones differed significantly, i.e. 22 % higher in Z1 than in Z2. No significant variation in Mic was observed between zones, but Z1 had higher Corg levels, SWC, TP and Mac and lower BD than Z2 in both soil layers, as well as a lower PR than Z2 in the 0.00-0.10 m layer. Therefore, soil physical conditions were more restrictive in Z2, in agreement with wheat yield and zone yield potential defined a priori, based on the harvest maps. Soil WIC in Z1 was significantly higher (30 %) than in Z2, in agreement with the results of TP and Mac which were also higher in Z1 in both soil layers. The correlation analysis of data of the two layers showed a positive relationship between wheat GY and the soil properties TP, SWC and WIC.

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.

Evaluation of statistical and geostatistical models of digital soil properties mapping in tropical mountain regions

Soil properties have an enormous impact on economic and environmental aspects of agricultural production. Quantitative relationships between soil properties and the factors that influence their variability are the basis of digital soil mapping. The predictive models of soil properties evaluated in this work are statistical (multiple linear regression-MLR) and geostatistical (ordinary kriging and co-kriging). The study was conducted in the municipality of Bom Jardim, RJ, using a soil database with 208 sampling points. Predictive models were evaluated for sand, silt and clay fractions, pH in water and organic carbon at six depths according to the specifications of the consortium of digital soil mapping at the global level (GlobalSoilMap). Continuous covariates and categorical predictors were used and their contributions to the model assessed. Only the environmental covariates elevation, aspect, stream power index (SPI), soil wetness index (SWI), normalized difference vegetation index (NDVI), and b3/b2 band ratio were significantly correlated with soil properties. The predictive models had a mean coefficient of determination of 0.21. Best results were obtained with the geostatistical predictive models, where the highest coefficient of determination 0.43 was associated with sand properties between 60 to 100 cm deep. The use of a sparse data set of soil properties for digital mapping can explain only part of the spatial variation of these properties. The results may be related to the sampling density and the quantity and quality of the environmental covariates and predictive models used.

Earthworms from Mato Grosso, Brazil, and new records of species from the state

The objective of this work was to undertake a qualitative assessment of earthworm diversity in areas under human influence, in a region of Cerrado-Pantanal-Amazon rainforest transition, in the state of Mato Grosso, Brazil. The earthworms were collected in the municipalities of Barra do Bugres and Arenápolis, and were studied together with species previously identified from other municipalities. Seventeen municipalities, at 29 sampling points of Mato Grosso State, have been sampled. Seven species of earthworms were collected and identified in Barra do Bugres: Goiascolex vanzolinii, Pontoscolex (Pontoscolex) corethrurus, Opisthodrillus borellii borellii, Opisthodrillus sp., Dichogaster (Diplothecodrilus) gracilis, Dichogaster sp. and a species of the Criodrilidae family. Four species of earthworms were identified in Arenápolis: Pontoscolex (Pontoscolex) corethrurus, Dichogaster (Diplothecodrilus) gracilis, Dichogaster (Diplothecodrilus) affinis and Dichogaster sp. In total, 32 earthworm species/subspecies are known from Mato Grosso, 22 native and 10 exotic.

Distribuição de compostos organoclorados nas águas e sedimentos da bacia do rio Piracicaba/SP - Brasil

The great utilization of synthetic and persistent xenobiotic cumulative compounds is the main causes of the deterioration of aquatic ecosystems. The one of objective of this work was the determination of the organochlorine levels in the Piracicaba river basin, situated at the center of São Paulo state. Four PCBs congeners, PCP and HCB were determined by GC-ECD in two different matrices: water and sediments. The pattern of the compound distribution indicated a dominance of PCP, HCB and PCB-200. The results indicated contamination in the sampling points located in Campinas, Piracicaba, Santa Bárbara d'Oeste and Sumaré cities.

Diagnóstico espaço-temporal da ocorrência de herbicidas nas águas superficiais e sedimentos do Rio Corumbataí e principais afluentes

Residues of herbicides from sugarcane were monitored in waters and sediments of Corumbataí River and tributaries. Ametryne, atrazine, simazine, hexazinone, glyphosate, and clomazone were detected in water samples, with negligible levels of ametryne and glyphosate in sediment samples. The area of recharge of the Guarani aquifer presented the highest triazine and clomazone levels. The triazines were detected at higher levels, with atrazine above Brazil's potability and quality standards. Total herbicide levels at some sampling points were 13 times higher than the European Community potability limit. There is no Brazilian standard for ametryne, although the risk is larger due to ametryne's higher toxicity for the aquatic biota.

Avaliação da qualidade do corpo hídrico do rio Tibagi na região de Ponta Grossa utilizando análise de componentes principais (PCA)

The aim of this paper was to evaluate alterations in the quality of the water of the Tibagi River caused by the urban and industrial activities in the region of Ponta Grossa. The study involved the monitoring of physico-chemical and microbiological parameters of the water body, which were evaluated by a principal components analysis routine. Sample collections were carried out monthly during one year (October of 2005 to September of 2006), at 3 sampling points: upstream and downstream of the industrial district and downstream from the city of Ponta Grossa. The principal components analysis showed the effect of point sources associated with industrial activity, which contribute to the rise of total concentration of amoniacal nitrogen and the reduction of dissolved oxygen in the studied region.

Perfil espacial e temporal de poluentes nas águas da represa municipal de São José do Rio Preto, São Paulo, Brasil

In this manuscript, seasonal and spatial trends of water collected from two sampling places in the Preto River in the Turvo-Grande watershed were evaluated. Water samples were collected during June/07 to July/08 and parameters sulphate, total organic carbon, ammonia, conductivity, dissolved oxygen, temperature, dissolved total solids and nitrate were quantified. Seasonal trend indicated sanitary effluents as a point source of contamination in both sampling points. Vertical trends demonstrated that the Municipal Dam was not stratified and received a diffuse source of pollutants from flooding and agriculture runoffs. It was also verified that there is relatively fast ammonia consumption kinetics having a half-life time of 1.43 h which can explain the low ammonia concentrations found in these aquatic bodies.

Composição química das águas pluviais e deposição atmosférica anual na bacia do Alto Sorocaba (SP)

Two sampling points were chosen and forty samples were collected between January and December 2006 at Alto Sorocaba basin. The rainwater pH varied from 5.46 to 6.36 (Ibiúna) and 5.26 to 6.81 (Itupararanga), being Ca2+ the main ion responsible for controlling the rainwater pH. The ionic concentrations decreased in the following order: Ca2 +>Na+> Mg2+>K+ for cations and SO4(2-)>HCO3->NO 3->Cl- >PO4(3-) for anions. The annual atmospheric deposition appeared to be controlled mostly by following sources: mining activities and cement factories (Ca2+ and HCO3-), natural soil dust (Na+, Mg2+ and HCO3-), fossil fuel burning (SO4(2-)) and agriculture activities (K+, NO3- and PO4(3-)).

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.

Soybean yield maps using regular and optimized sample with different configurations by simulated annealing

ABSTRACT This study aimed to compare thematic maps of soybean yield for different sampling grids, using geostatistical methods (semivariance function and kriging). The analysis was performed with soybean yield data in t ha-1 in a commercial area with regular grids with distances between points of 25x25 m, 50x50 m, 75x75 m, 100x100 m, with 549, 188, 66 and 44 sampling points respectively; and data obtained by yield monitors. Optimized sampling schemes were also generated with the algorithm called Simulated Annealing, using maximization of the overall accuracy measure as a criterion for optimization. The results showed that sample size and sample density influenced the description of the spatial distribution of soybean yield. When the sample size was increased, there was an increased efficiency of thematic maps used to describe the spatial variability of soybean yield (higher values of accuracy indices and lower values for the sum of squared estimation error). In addition, more accurate maps were obtained, especially considering the optimized sample configurations with 188 and 549 sample points.

A multidisciplinary approach to diagnose naturally occurring bovine tuberculosis in Brazil

A herd infected naturally with tuberculosis was investigated by different diagnostic methods. Ninety days after a screening test that identified 21 cows as skin test positive, a Comparative Intradermal Tuberculin Test (CITT) was performed in those 21 cows and in 29 other randomly selected skin test negative cows. Milk samples and nasal swabs were collected prior to the CITT for bacteriological culture and PCR, while blood samples were collected for IFN release and antibody responses to MPB70 and MPB83, at three time points post tuberculin injection. Animals positive by CITT were slaughtered and disease confirmation undertaken. Based on the Kappa test, IFN was comparable to the standard tests (culture, PCR and CITT) at all three sampling points. Results from both antibody ELISAs were similar but were not comparable to the standard tests. T-test analysis of the CITT, IFN and ELISAs demonstrated that their performances were not correlated. There is increasing recognition that individually, available diagnostic tests do not detect all infected cattle. Therefore, a comprehensive strategy for the diagnosis of bovine TB should include test results for the detection of both cellular and humoral immune responses where there may be animals at different stages of infection.

Prediction of soil orders with high spatial resolution: response of different classifiers to sampling density

The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission errors, overall accuracy, and quantity and allocation disagreement. The decision tree was less sensitive to sampling density and had the highest accuracy and consistence. The SOM was the less sensitive and most consistent network. The MLP had a critical minimum and showed high inconsistency, whereas fuzzy ARTMap was more sensitive and less accurate. Results indicate that sampling densities used in conventional soil surveys can serve as a reference to predict soil orders in Serra Gaúcha.