Diallel analysis for grain yield and mineral absorption rate of soybeans grown in acid brazilian savannah soil

High available aluminium and low levels of calcium below the ploughed zone of the soil are limiting factors for agricultural sustainability in the Brazilian Cerrados (Savannahs). The mineral stresses compound with dry spells effect by preventing deep root growth of cultivated plants and causes yield instability. The mode of inheritance for grain yield and mineral absorption ratio of a diallel cross in soybeans [Glycine max (L.) Merrill] grown in high and low Al areas was identified. Differences among the genotypes for grain yield were more evident in the high Al, by grouping tolerant and non-tolerant genotypes for their respective arrays in the hybrids. A large proportion of genetic variance was additive for grain yield and mineral absorption ratio in both environments. High heritability values suggest that soybeans can be improved by crosses among Al-tolerant genotypes, using modified pedigree, early generation and recurrent selection schemes.

Phosphorus analysis in soil under herbaceous perennial leguminous cover by nuclear magnetic spectroscopy

The availability and the reserves of organic phosphorus are controlled by its mineralization rate and are also influenced by changes in soil management. The objective of this study was to evaluate the influence of soil covering with different leguminous plant on soil organic P by 31P-NMR spectroscopy. Alkaline soil extracts were obtained from two depths (0-5 and 5-10 cm) of an Ultisol cultivated with herbaceous perennial leguminous plants (Arachis pintoi, Pueraria phaseoloides, Macroptilium atropurpureum). In an adjacent area, samples of the same soil cover with a secondary tropical forest and grass (Panicum maximum) were also collected. The leguminous management was divided into with removal and without removal of shoot parts after cut on soil surface. Phosphate monoesters are the dominant P species in all soil samples and P diesters accumulated on the superficial layer of secondary forest soil. The P amount of this fraction is higher for the legume covered soil when compared with the grass covered soil. The permanence of leguminous plants on the topsoil after the cut promoted an increase in P diester/P monoester ratios. These findings can be accounted for an enhancement of P availability to plants in soils cultivated with leguminous plants.

Bacterial diversity of soil under eucalyptus assessed by 16S rDNA sequencing analysis

Studies on the impact of Eucalyptus spp. on Brazilian soils have focused on soil chemical properties and isolating interesting microbial organisms. Few studies have focused on microbial diversity and ecology in Brazil due to limited coverage of traditional cultivation and isolation methods. Molecular microbial ecology methods based on PCR amplified 16S rDNA have enriched the knowledge of soils microbial biodiversity. The objective of this work was to compare and estimate the bacterial diversity of sympatric communities within soils from two areas, a native forest (NFA) and an eucalyptus arboretum (EAA). PCR primers, whose target soil metagenomic 16S rDNA were used to amplify soil DNA, were cloned using pGEM-T and sequenced to determine bacterial diversity. From the NFA soil 134 clones were analyzed, while 116 clones were analyzed from the EAA soil samples. The sequences were compared with those online at the GenBank. Phylogenetic analyses revealed differences between the soil types and high diversity in both communities. Soil from the Eucalyptus spp. arboretum was found to have a greater bacterial diversity than the soil investigated from the native forest area.

Analysis of sensitivity with respect to a compositional parameter : A comment on 'Local sensitivity analysis for compositional data with application to soil texture in hydrologic modelling' by L. Loosvelt and co-authors

A comment about the article “Local sensitivity analysis for compositional data with application to soil texture in hydrologic modelling” writen by L. Loosvelt and co-authors. The present comment is centered in three specific points. The first one is related to the fact that the authors avoid the use of ilr-coordinates. The second one refers to some generalization of sensitivity analysis when input parameters are compositional. The third tries to show that the role of the Dirichlet distribution in the sensitivity analysis is irrelevant

Soil quality assessment through a multi-approach analysis in soils of abandoned terraced land in NE Spain

The abandonment of agricultural land in mountainous areas has been an outstanding problem along the last century and has captured the attention of scientists, technicians and administrations, for the dramatic consequences sometimes occurred due to soil instability, steep slopes, rainfall regimes and wildfires. Hidromorfological and pedological alterations causing exceptional floods and accelerated erosion processes has therefore been studied, identifying the cause in the loss of landscape heterogeneity. Through the disappearance of agricultural works and drainage maintenance, slope stability has resulted severely affected. The mechanization of agriculture has caused the displacement of vines, olives and corks trees cultivation in terraced areas along the Mediterranean catchment towards more economically suitable areas. On the one hand, land use and management changes have implicated sociological changes as well, transforming areas inhabited by agricultural communities into deserted areas where the colonization of disorganized spontaneous vegetation has buried a valuable rural patrimony. On the other hand, lacking of planning and management of the abandoned areas has produced badlands and infertile soils due to wildfire and high erosion rates strongly degrading the whole ecosystems. In other cases, after land abandonment a process of soil regeneration has been recorded. Investigations have been conducted in a part of NE Spain where extended areas of terraced soils previously cultivated have been abandoned in the last century. The selected environments were semi-abandoned vineyards, semi-abandoned olive groves, abandoned stands of cork trees, abandoned stands of pine trees, scrubland of Cistaceaea, scrubland of Ericaceaea, and pasture. The research work was focused on the study of most relevant physical, chemical and biological soil properties, as well as runoff and erosion under soils with different plant cover to establish the abandonment effect on soil quality, due to the peculiarity and vulnerability of these soils with a much reduced depth. The period of observation was carried out from autumn 2009 to autumn 2010. The sediment concentration of soil erosion under vines was recorded as 34.52 g/l while under pasture it was 4.66 g/l. In addition, the soil under vines showed the least amount of organic matter, which was 12 times lower than all other soil environments. The carbon dioxide (CO2) and total glomalin (TG) ratio to soil organic carbon (SOC) in this soil was 0.11 and 0.31 respectively. However, the soil under pasture contained a higher amount of organic matter and showed that the CO2 and TG ratio to SOC was 0.02 and 0.11 respectively indicating that the soil under pasture better preserves the soil carbon pool. A similar trend was found in the intermediate soils in the sequence of land use change and abandonment. Soil structural stability increased in the two soil fractions investigated (0.25-2.00 mm, 2.0-5.6 mm) especially in those soils that did not undergo periodical perturbations like wildfires. Soil quality indexes were obtained by using relevant physical and chemical soil parameters. Factor analysis carried out to study the relationship between all soil parameters allowed to related variables and environments and identify those areas that better contribute to soil quality towards others that may need more attention to avoid further degradation processes

Epidemiological analysis of clones and cultivars of potato in soil naturally infested with Ralstonia solanacearum biovar 2

The objectives of this study were to evaluate the progress of Ralstonia solanacearum bacterial potato wilt biovar 2 (race 3) in 14 potato (Solanum tuberosum L.) cultivars or clones, the resistance of potato clone MB 03 (selected in Brasília, Brazil) to race 1 of R. solanacearum, and the occurrence of the pathogen in tubers harvested from asymptomatic potato plants. During the spring (September to the end of November in the southern hemisphere) of 1999 and 2000, 14 cultivars or clones were grown in a field naturally infested with R. solanacearum biovar 2, in Caxias do Sul, RS. The number of wilted potato plants was recorded each week and a disease progress curve plotted, the resistance of the potato genotypes to bacterial wilt being evaluated by determining the area under the curve. Various models were evaluated to fit the curves, with the logistic model being the best fit. At the end of each growing season tubers produced by asymptomatic plants were harvested and stored until budding and then tested for the presence of R. solanacearum. Cultivar Cruza 148 and clone MB 03 were the most resistant but both showed tubers with latent infections. The epidemiological implications of the incidence of R. solanacearum biovar 2 (race 3) in potato crops, as well as the resistance of certain genotypes that may harbor latent infections, are important aspects to be considered in the integrated management of bacterial wilt.

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.

A REVIEW OF SOIL CONSTITUTIVE MODELS FOR SOIL STRUCTURE INTEREACTION ANALYSIS

Soils are multiphase materials comprised of mineral grains, air voids and water. Soils are not linearly elastic or perfectly plastic for external loading. Various constitutive models are available to describe the various aspects of soil behaviour. But no single soil model can completely describe the behaviour of real soil under all conditions. This paper attempts to compare various soil models and suggest a suitable model for the Soil Structure Interaction analysis especially for Kochi marine clay.

Multi-site time-trend analysis of soil fertility management effects on crop production in sub-Saharan West Africa

Soil fertility constraints to crop production have been recognized widely as a major obstacle to food security and agro-ecosystem sustainability in sub-Saharan West Africa. As such, they have led to a multitude of research projects and policy debates on how best they should be overcome. Conclusions, based on long-term multi-site experiments, are lacking with respect to a regional assessment of phosphorus and nitrogen fertilizer effects, surface mulched crop residues, and legume rotations on total dry matter of cereals in this region. A mixed model time-trend analysis was used to investigate the effects of four nitrogen and phosphorus rates, annually applied crop residue dry matter at 500 and 2000 kg ha^-1, and cereal-legume rotation versus continuous cereal cropping on the total dry matter of cereals and legumes. The multi-factorial experiment was conducted over four years at eight locations, with annual rainfall ranging from 510 to 1300 mm, in Niger, Burkina Faso, and Togo. With the exception of phosphorus, treatment effects on legume growth were marginal. At most locations, except for typical Sudanian sites with very low base saturation and high rainfall, phosphorus effects on cereal total dry matter were much lower with rock phosphate than with soluble phosphorus, unless the rock phosphate was combined with an annual seed-placement of 4 kg ha^-1 phosphorus. Across all other treatments, nitrogen effects were negligible at 500 mm annual rainfall but at 900 mm, the highest nitrogen rate led to total dry matter increases of up to 77% and, at 1300 mm, to 183%. Mulch-induced increases in cereal total dry matter were larger with lower base saturation, reaching 45% on typical acid sandy Sahelian soils. Legume rotation effects tended to increase over time but were strongly species-dependent.

A geostatistical analysis of the spatial variation of soil mineral nitrogen and potentially available nitrogen within an arable field.

The technology for site-specific applications of nitrogen (N) fertilizer has exposed a gap in our knowledge about the spatial variation of soil mineral N, and that which will become available during the growing season within arable fields. Spring mineral N and potentially available N were measured in an arable field together with gravimetric water content, loss on ignition, crop yield, percentages of sand, silt, and clay, and elevation to describe their spatial variation geostatistically. The areas with a larger clay content had larger values of mineral N, potentially available N, loss on ignition and gravimetric water content, and the converse was true for the areas with more sandy soil. The results suggest that the spatial relations between mineral N and loss on ignition, gravimetric water content, soil texture, elevation and crop yield, and between potentially available N and loss on ignition and silt content could be used to indicate their spatial patterns. Variable-rate nitrogen fertilizer application would be feasible in this field because of the spatial structure and the magnitude of variation of mineral N and potentially available N.

The analysis of ranked observations of soil structure using indicator geostatistics

Structure is an important physical feature of the soil that is associated with water movement, the soil atmosphere, microorganism activity and nutrient uptake. A soil without any obvious organisation of its components is known as apedal and this state can have marked effects on several soil processes. Accurate maps of topsoil and subsoil structure are desirable for a wide range of models that aim to predict erosion, solute transport, or flow of water through the soil. Also such maps would be useful to precision farmers when deciding how to apply nutrients and pesticides in a site-specific way, and to target subsoiling and soil structure stabilization procedures. Typically, soil structure is inferred from bulk density or penetrometer resistance measurements and more recently from soil resistivity and conductivity surveys. To measure the former is both time-consuming and costly, whereas observations made by the latter methods can be made automatically and swiftly using a vehicle-mounted penetrometer or resistivity and conductivity sensors. The results of each of these methods, however, are affected by other soil properties, in particular moisture content at the time of sampling, texture, and the presence of stones. Traditional methods of observing soil structure identify the type of ped and its degree of development. Methods of ranking such observations from good to poor for different soil textures have been developed. Indicator variograms can be computed for each category or rank of structure and these can be summed to give the sum of indicator variograms (SIV). Observations of the topsoil and subsoil structure were made at four field sites where the soil had developed on different parent materials. The observations were ranked by four methods and indicator and the sum of indicator variograms were computed and modelled for each method of ranking. The individual indicators were then kriged with the parameters of the appropriate indicator variogram model to map the probability of encountering soil with the structure represented by that indicator. The model parameters of the SIVs for each ranking system were used with the data to krige the soil structure classes, and the results are compared with those for the individual indicators. The relations between maps of soil structure and selected wavebands from aerial photographs are examined as basis for planning surveys of soil structure. (C) 2007 Elsevier B.V. All rights reserved.

The Representative Soil Sampling Scheme of England and Wales: a statistical analysis of topsoil nutrient status and pH between 1971 and 2001

The Representative Soil Sampling Scheme of England and Wales has recorded information on the soil of agricultural land in England and Wales since 1969. It is a valuable source of information about the soil in the context of monitoring for sustainable agricultural development. Changes in soil nutrient status and pH were examined over the period 1971-2001. Several methods of statistical analysis were applied to data from the surveys during this period. The main focus here is on the data for 1971, 1981, 1991 and 2001. The results of examining change over time in general show that levels of potassium in the soil have increased, those of magnesium have remained fairly constant, those of phosphorus have declined and pH has changed little. Future sampling needs have been assessed in the context of monitoring, to determine the mean at a given level of confidence and tolerable error and to detect change in the mean over time at these same levels over periods of 5 and 10 years. The results of a non-hierarchical multivariate classification suggest that England and Wales could be stratified to optimize future sampling and analysis. To monitor soil quality and health more generally than for agriculture, more of the country should be sampled and a wider range of properties recorded.

Estimating the spatial scale of herbicide and soil interactions by nested sampling, hierarchical analysis of variance and residual maximum likelihood

An unbalanced nested sampling design was used to investigate the spatial scale of soil and herbicide interactions at the field scale. A hierarchical analysis of variance based on residual maximum likelihood (REML) was used to analyse the data and provide a first estimate of the variogram. Soil samples were taken at 108 locations at a range of separating distances in a 9 ha field to explore small and medium scale spatial variation. Soil organic matter content, pH, particle size distribution, microbial biomass and the degradation and sorption of the herbicide, isoproturon, were determined for each soil sample. A large proportion of the spatial variation in isoproturon degradation and sorption occurred at sampling intervals less than 60 m, however, the sampling design did not resolve the variation present at scales greater than this. A sampling interval of 20-25 m should ensure that the main spatial structures are identified for isoproturon degradation rate and sorption without too great a loss of information in this field.

Spatial analysis of the error in a model of soil nitrogen

Models of the dynamics of nitrogen in soil (soil-N) can be used to aid the fertilizer management of a crop. The predictions of soil-N models can be validated by comparison with observed data. Validation generally involves calculating non-spatial statistics of the observations and predictions, such as their means, their mean squared-difference, and their correlation. However, when the model predictions are spatially distributed across a landscape the model requires validation with spatial statistics. There are three reasons for this: (i) the model may be more or less successful at reproducing the variance of the observations at different spatial scales; (ii) the correlation of the predictions with the observations may be different at different spatial scales; (iii) the spatial pattern of model error may be informative. In this study we used a model, parameterized with spatially variable input information about the soil, to predict the mineral-N content of soil in an arable field, and compared the results with observed data. We validated the performance of the N model spatially with a linear mixed model of the observations and model predictions, estimated by residual maximum likelihood. This novel approach allowed us to describe the joint variation of the observations and predictions as: (i) independent random variation that occurred at a fine spatial scale; (ii) correlated random variation that occurred at a coarse spatial scale; (iii) systematic variation associated with a spatial trend. The linear mixed model revealed that, in general, the performance of the N model changed depending on the spatial scale of interest. At the scales associated with random variation, the N model underestimated the variance of the observations, and the predictions were correlated poorly with the observations. At the scale of the trend, the predictions and observations shared a common surface. The spatial pattern of the error of the N model suggested that the observations were affected by the local soil condition, but this was not accounted for by the N model. In summary, the N model would be well-suited to field-scale management of soil nitrogen, but suited poorly to management at finer spatial scales. This information was not apparent with a non-spatial validation. (c),2007 Elsevier B.V. All rights reserved.