Occurrence and composition of class 1 and class 2 integrons in clinical and environmental O1 and non-O1/non-O139 Vibrio cholerae strains from the Brazilian Amazon

This study identified and characterised class 1 and 2 integrons in clinical and environmental Vibrio cholerae O1 and non-O1/non-O139 strains isolated from the Brazilian Amazon. The aadA2 and aadA7 gene cassettes were found in class 1 integrons in two genotypes of environmental V. cholerae non-O1/non-O139. Empty integrons were found in strains from the Brazilian cholera epidemic. A class 2 integron was detected in one strain from the V. cholerae Amazonia lineage harbouring sat1 and aadA1 genes. All isolates were resistant to aminoglycosides, indicating aadA functionality. These findings suggest that environmental bacteria act as cassette reservoirs that favour the emergence of resistant pathogens.

Association analysis of human leukocyte antigen class II (DRB1) alleles with leprosy in individuals from São Luís, state of Maranhão, Brazil

Epidemiological studies have demonstrated that the variability of the clinical response to infection caused by Mycobacterium leprae is associated with host genetic factors. The present study investigated the frequency of human leukocyte antigen (HLA) class II (DRB1) alleles in patients with leprosy from São Luís, Maranhão, Brazil. A case-control study was performed in 85 individuals with leprosy and 85 healthy subjects. All samples were analysed via polymerase chain reaction-sequence specific oligonucleotide probes. The HLA-DRB1*16 allele showed a higher frequency in the group with leprosy [(9.41% vs. 4.12%) odds ratio (OR) = 2.41 95% confidence interval (CI) (0.96-6.08) p = 0.05], whereas the HLA-DRB1*11 allele was less frequent in the group with leprosy [(6.47% vs. 11.76%) OR = 0.51 95% CI (0.23-1.12) p = 0.09]. The frequency of HLA-DRB1* alleles between the control group and leprosy patient subgroups presenting different forms of the disease showed that the HLA-DRB1*16 (16.13% vs. 8.24%, OR = 4.10, CI = 1.27-13.27, p = 0.010) and HLA-DRB1*14 (5% vs. 3.53%, OR = 4.63, CI = 1.00-21.08, p = 0.032) alleles were significantly more frequent in patients with different clinical subtypes of leprosy. The sample size was a limitation in this study. Nevertheless, the results demonstrated the existence of a genetic susceptibility associated with the clinical forms of leprosy. The low frequency of the HLA-DRB1*11 allele should be further studied to investigate the possible protective effect of this allele.

Tegumentar glands associated to foveae in the second metasomal tergum of Panurgillus Moure (Apoidea, Andrenidae, Panurginae)

Panurginae have a pair of cuticular depressions in the second metasomal tergum, recognized as lateral foveae of the T2. These structures have been used as systematic and taxonomic characters, although their functions are yet unknown. We aimed a morphological analysis at lateral foveae of three species of Panurgillus Moure, 1998: P. vagabundus (Cockerell, 1918), P. reticulatus Schlindwein & Moure, 1998 e P. flavitarsis Schlindwein & Moure, 1998. The study of the external morphology showed that the lateral foveae of the T2 are evident among females, but in males they are undistinguishable or absent. The surface of the foveae is micropunctuated in all species. The histological analysis has shown that the region of the lateral foveae of the T2, of female and male of the three species, presented tegumentar specializations. The inner part showed an evident secretory epithelium recognized as Class I gland. The height of this secretory epithelium was not uniform, although the cellular features are similar independent of sex. We have not found any previous information regarding the presence of glands related to abdominal foveae in Panurginae species.

Relationships between soil class and nutritional status of coffee plantations

Farm planning requires an assessment of the soil class. Research suggest that the Diagnosis and Recommendation Integrated System (DRIS) has the capacity to evaluate the nutritional status of coffee plantations, regardless of environmental conditions. Additionally, the use of DRIS could reduce the costs for farm planning. This study evaluated the relationship between the soil class and nutritional status of coffee plants (Coffea canephora Pierre) using the Critical Level (CL) and DRIS methods, based on two multivariate statistical methods (discriminant and multidimensional scaling analyses). During three consecutive years, yield and foliar concentration of nutrients (N, P, K, Ca, Mg, S, B, Zn, Mn, Fe and Cu) were obtained from coffee plantations cultivated in Espírito Santo state. Discriminant analysis showed that the soil class was an important factor determining the nutritional status of the coffee plants. The grouping separation by the CL method was not as effective as the DRIS one. The bidimensional analysis of Euclidean distances did not show the same relationship between plant nutritional status and soil class. Multidimensional scaling analysis by the CL method indicated that 93.3 % of the crops grouped into one cluster, whereas the DRIS method split the fields more evenly into three clusters. The DRIS method thus proved to be more consistent than the CL method for grouping coffee plantations by soil class.

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.

Pedotransfer functions to estimate proctor test parameters under different tillage systems

The Proctor test is time-consuming and requires sampling of several kilograms of soil. Proctor test parameters were predicted in Mollisols, Entisols and Vertisols of the Pampean region of Argentina under different management systems. They were estimated from a minimum number of readily available soil properties (soil texture, total organic C) and management (training data set; n = 73). The results were used to generate a soil compaction susceptibility model, which was subsequently validated using a second group of independent data (test data set; n = 24). Soil maximum bulk density was estimated as follows: Maximum bulk density (Mg m-3) = 1.4756 - 0.00599 total organic C (g kg-1) + 0.0000275 sand (g kg-1) + 0.0539 management. Management was equal to 0 for uncropped and untilled soils and 1 for conventionally tilled soils. The established models predicted the Proctor test parameters reasonably well, based on readily available soil properties. Tillage systems induced changes in the maximum bulk density regardless of total organic matter content or soil texture. The lower maximum apparent bulk density values under no-tillage require a revision of the relative compaction thresholds for different no-tillage crops.

Pedotransfer functions to estimate retention and availability of water in soils of the state of Santa Catarina, Brazil

Studies on water retention and availability are scarce for subtropical or humid temperate climate regions of the southern hemisphere. The aims of this study were to evaluate the relations of the soil physical, chemical, and mineralogical properties with water retention and availability for the generation and validation of continuous point pedotransfer functions (PTFs) for soils of the State of Santa Catarina (SC) in the South of Brazil. Horizons of 44 profiles were sampled in areas under different cover crops and regions of SC, to determine: field capacity (FC, 10 kPa), permanent wilting point (PWP, 1,500 kPa), available water content (AW, by difference), saturated hydraulic conductivity, bulk density, aggregate stability, particle size distribution (seven classes), organic matter content, and particle density. Chemical and mineralogical properties were obtained from the literature. Spearman's rank correlation analysis and path analysis were used in the statistical analyses. The point PTFs for estimation of FC, PWP and AW were generated for the soil surface and subsurface through multiple regression analysis, followed by robust regression analysis, using two sets of predictive variables. Soils with finer texture and/or greater organic matter content retain more moisture, and organic matter is the property that mainly controls the water availability to plants in soil surface horizons. Path analysis was useful in understanding the relationships between soil properties for FC, PWP and AW. The predictive power of the generated PTFs to estimate FC and PWP was good for all horizons, while AW was best estimated by more complex models with better prediction for the surface horizons of soils in Santa Catarina.

Assessment of pedotransfer functions for estimating soil water retention curves for the amazon region

Knowledge of the soil water retention curve (SWRC) is essential for understanding and modeling hydraulic processes in the soil. However, direct determination of the SWRC is time consuming and costly. In addition, it requires a large number of samples, due to the high spatial and temporal variability of soil hydraulic properties. An alternative is the use of models, called pedotransfer functions (PTFs), which estimate the SWRC from easy-to-measure properties. The aim of this paper was to test the accuracy of 16 point or parametric PTFs reported in the literature on different soils from the south and southeast of the State of Pará, Brazil. The PTFs tested were proposed by Pidgeon (1972), Lal (1979), Aina & Periaswamy (1985), Arruda et al. (1987), Dijkerman (1988), Vereecken et al. (1989), Batjes (1996), van den Berg et al. (1997), Tomasella et al. (2000), Hodnett & Tomasella (2002), Oliveira et al. (2002), and Barros (2010). We used a database that includes soil texture (sand, silt, and clay), bulk density, soil organic carbon, soil pH, cation exchange capacity, and the SWRC. Most of the PTFs tested did not show good performance in estimating the SWRC. The parametric PTFs, however, performed better than the point PTFs in assessing the SWRC in the tested region. Among the parametric PTFs, those proposed by Tomasella et al. (2000) achieved the best accuracy in estimating the empirical parameters of the van Genuchten (1980) model, especially when tested in the top soil layer.

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.

Revisiting Field Capacity (FC): variation of definition of FC and its estimation from pedotransfer functions

Taking into account the nature of the hydrological processes involved in in situ measurement of Field Capacity (FC), this study proposes a variation of the definition of FC aiming not only at minimizing the inadequacies of its determination, but also at maintaining its original, practical meaning. Analysis of FC data for 22 Brazilian soils and additional FC data from the literature, all measured according to the proposed definition, which is based on a 48-h drainage time after infiltration by shallow ponding, indicates a weak dependency on the amount of infiltrated water, antecedent moisture level, soil morphology, and the level of the groundwater table, but a strong dependency on basic soil properties. The dependence on basic soil properties allowed determination of FC of the 22 soil profiles by pedotransfer functions (PTFs) using the input variables usually adopted in prediction of soil water retention. Among the input variables, soil moisture content θ (6 kPa) had the greatest impact. Indeed, a linear PTF based only on it resulted in an FC with a root mean squared residue less than 0.04 m³ m-3 for most soils individually. Such a PTF proved to be a better FC predictor than the traditional method of using moisture content at an arbitrary suction. Our FC data were compatible with an equivalent and broader USA database found in the literature, mainly for medium-texture soil samples. One reason for differences between FCs of the two data sets of fine-textured soils is due to their different drainage times. Thus, a standardized procedure for in situ determination of FC is recommended.

PEDO-TRANSFER FUNCTIONS FOR ESTIMATING SOIL BULK DENSITY IN CENTRAL AMAZONIA

Under field conditions in the Amazon forest, soil bulk density is difficult to measure. Rigorous methodological criteria must be applied to obtain reliable inventories of C stocks and soil nutrients, making this process expensive and sometimes unfeasible. This study aimed to generate models to estimate soil bulk density based on parameters that can be easily and reliably measured in the field and that are available in many soil-related inventories. Stepwise regression models to predict bulk density were developed using data on soil C content, clay content and pH in water from 140 permanent plots in terra firme (upland) forests near Manaus, Amazonas State, Brazil. The model results were interpreted according to the coefficient of determination (R2) and Akaike information criterion (AIC) and were validated with a dataset consisting of 125 plots different from those used to generate the models. The model with best performance in estimating soil bulk density under the conditions of this study included clay content and pH in water as independent variables and had R2 = 0.73 and AIC = -250.29. The performance of this model for predicting soil density was compared with that of models from the literature. The results showed that the locally calibrated equation was the most accurate for estimating soil bulk density for upland forests in the Manaus region.

Pineapple yield and fruit quality effected by NPK fertilization in a tropical soil

There is a lack of information about fertilization of pineapple grown in the State of São Paulo, Brazil. So a field experiment with pineapple 'Smooth Cayenne' was carried out to study the effects of NPK rates on yield and fruit quality. The trial was located on an Alfisol in the central part of the State of São Paulo (Agudos county). The experimental design was an incomplete NPK factorial, with 32 treatments set up in two blocks. The P was applied only at planting, at the rates of 0; 80; 160 and 320 kg/ha of P2 0(5), as superphosphate. The N and K2O rates were 0; 175; 350, and 700 kg/ha, applied as urea and potassium chloride, respectively, divided in four applications during the growth period. Response functions were adjusted to yield or to fruit characteristics in order to estimate the nutrient rates required to reach maximum values. The results showed quadratic effects of N and K on yield and a maximum of 72 t/ha of fresh fruit was attained with rates of 498 and 394 kg/ha, respectively of N and K2O. In order to reach the maximum fruit size, and to improve the percentage of first class fruit (mass greater than 2.6 kg), were necessary rates of N and K respectively 11 and 43 % higher than those for maximum yield. No effect of P rates was observed on pineapple plant growth, despite the low availability of this nutrient in the soil. The effect of N rates was negative on total soluble solids and total acidity while the opposite occurred with K, which increased also the content of vitamin C. High yield and fruit size were closely related to N and K concentrations in the leaves.