Effect of environmental conditions on the N uptake route of soil microorganisms and adaption of a method to determine amino acid oxidase in soil

Soil microorganisms have evolved two possible mechanisms for their uptake of organic N: the direct route and the mobilization-immobilization-turnover (MIT) route. In the direct route, simple organic molecules are taken up via various mechanisms directly into the cell. In the MIT route, the deamination occurs outside the cell and all N is mineralized to NH4+ before assimilation. A better understanding of the mechanisms controlling the different uptake routes of soil microorganisms under different environmental conditions is crucial for understanding mineralization processes of organic material in soil. For the first experiment we incubated soil samples from the long term trial in Bad Lauchstädt with corn residues with different C to N ratios and inorganic N for 21 days at 20 °C. Under the assumption that all added amino acids were taken up or mineralized, the direct uptake route was more important in soil amended with corn residues with a wide C to N ratio. After 21 days of incubation the direct uptake of added amino acids increased in the order addition of corn residue with a: “C to N ratio of 40 & (NH4)2SO4 and no addition (control)” (69% and 68%, respectively) < “C to N ratio of 20” (73%) < “C to N ratio of 40” (95%). In all treatments the proportion of the added amino acids that were mineralized increased with time, indicating that the MIT route became more important over time. To investigate the effects of soil depth on the N uptake route of soil microorganisms (experiment II), soil samples in two soil depths (0-5 cm; 30-40 cm) were incubated with corn residues with different C to N ratios and inorganic N for 21 days at 20 °C and 60% (WHC). The addition of corn residue resulted in a marked increase of protease activity in both depths due to the induction from the added substrate. Addition of corn residue with a wide C to N ratio resulted in a significantly greater part of the direct uptake (97% and 94%) than without the addition of residues (85% and 80%) or addition of residue with a small C to N ratio (90% and 84%) or inorganic N (91% and 79% in the surface soil and subsoil, respectively), suggesting that under conditions of sufficient mineralizable N (C to N ratio of 20) or increased concentrations of NH4+, the enzyme system involved in the direct uptake is slightly repressed. Substrate additions resulted in an initially significantly higher increase of the direct uptake in the surface soil than in the subsoil. As a large proportion of the organic N input into soil is in form of proteinaceous material, the deamination of amino acids is a key reaction of the MIT route. Therefore the enzyme amino acid oxidase contribute to the extracellular N mineralization in soil. The objective of experiment III was to adapt a method to determine amino acid oxidase in soil. The detection via synthetic fluorescent Lucifer Yellow derivatives of the amino acid lysine is possible in soil. However, it was not possible to find the substrate concentration at which the reaction rate is independent of substrate concentration and therefore we were not able to develop a valid soil enzyme assay.

Characterization and efficacy of bacterial strains for biological control of soil-borne diseases caused by Phytophthora cactorum and Meloidogyne javanica on Rosaceous plants

S'avaluaren 58 soques de Pseudomonas fluorescens i Pantoea agglomerans per la seva eficàcia en el biocontrol de la malaltia causada per l'oomicet Phytophthora cactorum en maduixera i pel nematode formador de gal·les Meloidogyne javanica en el portaempelt GF-677. Es desenvolupà un mètode ex vivo d'inoculació de fulla amb l'objectiu de seleccionar soques bacterianes com a agents de control biològic de P. cactorum en maduixera. Tres soques de P. fluorescens es seleccionaren com a soques eficaces en el biocontrol del patogen en fulles i en la reducció de la malaltia en plantes de maduixera. La combinació de soques semblà millorar la consistència del biocontrol en comparació amb les soques aplicades individualment. Tres soques de P. fluorescens es seleccionaren per la seva eficàcia en la reducció de la infecció de M. javanica en portaempelts GF-677. La combinació d'aquestes soques no incrementà l'eficàcia del biocontrol, però semblà reduir la seva variabilitat.

An integrated model of soil-canopy spectral radiances, photosynthesis, fluorescence, temperature and energy balance

This paper presents the model SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes), which is a vertical (1-D) integrated radiative transfer and energy balance model. The model links visible to thermal infrared radiance spectra (0.4 to 50 μm) as observed above the canopy to the fluxes of water, heat and carbon dioxide, as a function of vegetation structure, and the vertical profiles of temperature. Output of the model is the spectrum of outgoing radiation in the viewing direction and the turbulent heat fluxes, photosynthesis and chlorophyll fluorescence. A special routine is dedicated to the calculation of photosynthesis rate and chlorophyll fluorescence at the leaf level as a function of net radiation and leaf temperature. The fluorescence contributions from individual leaves are integrated over the canopy layer to calculate top-of-canopy fluorescence. The calculation of radiative transfer and the energy balance is fully integrated, allowing for feedback between leaf temperatures, leaf chlorophyll fluorescence and radiative fluxes. Leaf temperatures are calculated on the basis of energy balance closure. Model simulations were evaluated against observations reported in the literature and against data collected during field campaigns. These evaluations showed that SCOPE is able to reproduce realistic radiance spectra, directional radiance and energy balance fluxes. The model may be applied for the design of algorithms for the retrieval of evapotranspiration from optical and thermal earth observation data, for validation of existing methods to monitor vegetation functioning, to help interpret canopy fluorescence measurements, and to study the relationships between synoptic observations with diurnally integrated quantities. The model has been implemented in Matlab and has a modular design, thus allowing for great flexibility and scalability.

Assessment of soil particle redistribution on two contrasting cultivated hillslopes

The particle size distributions of surface soils from two cultivated silty fields (Moorfield and Railway South) in Herefordshire, UK, were assessed by sampling on 20-m grids across the fields. Moorfield (8 ha) had a uniform landscape sloping mainly in a North-South direction while Railway South (12 ha) had complex undulating landscape characteristics. Samples from 3 surficial layers were also taken at 3 landscape positions at Moorfield to investigate recent (within-season) soil particle redistribution. Size fractions were determined using chemical dispersion, wet sieving (to separate the sand fractions) and laser gramilometry (for the finer fractions). The distribution of various fractions and the relationships between elevation and the various fractions suggest preferential detachment and movement of coarse to very coarse silt fractions (16-63 mu m), which were found mostly at downslope or depositional areas. Upper slope samples had higher clay to fine silt (< 16 mu m) contents than bottom slope samples. The upslope-downslope patterns of size fractions, particularly on uniformly sloping areas, of the 2 fields were similar and their deposited sediments were dominated by coarse silt fractions. Samples from 3 landscape positions at Moorfield became coarser from the less eroded summit, through the eroding side-slope to the bottom-slope depositional area. Within each of these landscape positions the top 0-2.5 cm layers were more enriched in coarse silt fractions than the bottom layers. The spatial patterns of soil particle size distributions in the 2 fields may be a result of sediment detachment and deposition caused by water erosion and tillage operations. (c) 2005 Elsevier B.V. All rights reserved.

The spatial prediction of soil mineral N and potentially available N using elevation

The precision farmer wants to manage the variation in soil nutrient status continuously, which requires reliable predictions at places between sampling sites. Ordinary kriging can be used for prediction if the data are spatially dependent and there is a suitable variogram model. However, even if data are spatially correlated, there are often few soil sampling sites in relation to the area to be managed. If intensive ancillary data are available and these are coregionalized with the sparse soil data, they could be used to increase the accuracy of predictions of the soil properties by methods such as cokriging, kriging with external drift and regression kriging. This paper compares the accuracy of predictions of the plant available N properties (mineral N and potentially available N) for two arable fields in Bedfordshire, United Kingdom, from ordinary kriging, cokriging, kriging with external drift and regression kriging. For the last three, intensive elevation data were used with the soil data. The mean squared errors of prediction from these methods of kriging were determined at validation sites where the values were known. Kriging with external drift resulted in the smallest mean squared error for two of the three properties examined, and cokriging for the other. The results suggest that the use of intensive ancillary data can increase the accuracy of predictions of soil properties in arable fields provided that the variables are related spatially. (c) 2005 Elsevier B.V. All rights reserved.

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.

Simulating the spatial variation of soil mineral N within fields using the model SUNDIAL

Variable rate applications of nitrogen (N) are of environmental and economic interest. Regular measurements of soil N supply are difficult to achieve practically. Therefore accurate model simulations of soil N supply might provide a practical solution for site-specific management of N. Mineral N, an estimate of N supply, was simulated by the model SUNDIAL (Simulation of Nitrogen Dynamics In Arable Land) at more than 100 locations within three arable fields in Bedfordshire, UK. The results were compared with actual measurements. The outcomes showed that the spatial patterns of the simulations of mineral N corresponded to the measurements but the range of values was underestimated.

Effects of sub-pixel heterogeneity on the retrieval of soil moisture from passive microwave radiometry

A simple formulation relating the L-band microwave brightness temperature detected by a passive microwave radiometer to the near surface soil moisture was developed using MICRO-SWEAT, a coupled microwave emission model and soil-vegetation-atmosphere-transfer (SVAT) scheme. This simple model provides an ideal tool with which to explore the impact of sub-pixel heterogeneity on the retrieval of soil moisture from microwave brightness temperatures. In the case of a bare soil pixel, the relationship between apparent emissivity and surface soil moisture is approximately linear, with the clay content of the soil influencing just the intercept of this relationship. It is shown that there are no errors in the retrieved soil moisture from a bare soil pixel that is heterogeneous in soil moisture and texture. However, in the case of a vegetated pixel, the slope of the relationship between apparent emissivity and surface soil moisture decreases with increasing vegetation. Therefore for a pixel that is heterogeneous in vegetation and soil moisture, errors can be introduced into the retrieved soil moisture. Generally, under moderate conditions, the retrieved soil moisture is within 3% of the actual soil moisture. Examples illustrating this discussion use data collected during the Southern Great Plains '97 Experiment (SGP97).

Identifying management zones in agricultural fields using spatially constrained classification of soil and ancillary data

Site-specific management requires accurate knowledge of the spatial variation in a range of soil properties within fields. This involves considerable sampling effort, which is costly. Ancillary data, such as crop yield, elevation and apparent electrical conductivity (ECa) of the soil, can provide insight into the spatial variation of some soil properties. A multivariate classification with spatial constraint imposed by the variogram was used to classify data from two arable crop fields. The yield data comprised 5 years of crop yield, and the ancillary data 3 years of yield data, elevation and ECa. Information on soil chemical and physical properties was provided by intensive surveys of the soil. Multivariate variograms computed from these data were used to constrain sites spatially within classes to increase their contiguity. The constrained classifications resulted in coherent classes, and those based on the ancillary data were similar to those from the soil properties. The ancillary data seemed to identify areas in the field where the soil is reasonably homogeneous. The results of targeted sampling showed that these classes could be used as a basis for management and to guide future sampling of the soil.

Comparing sampling needs for variograms of soil properties computed by the method of moments and residual maximum likelihood

It has been generally accepted that the method of moments (MoM) variogram, which has been widely applied in soil science, requires about 100 sites at an appropriate interval apart to describe the variation adequately. This sample size is often larger than can be afforded for soil surveys of agricultural fields or contaminated sites. Furthermore, it might be a much larger sample size than is needed where the scale of variation is large. A possible alternative in such situations is the residual maximum likelihood (REML) variogram because fewer data appear to be required. The REML method is parametric and is considered reliable where there is trend in the data because it is based on generalized increments that filter trend out and only the covariance parameters are estimated. Previous research has suggested that fewer data are needed to compute a reliable variogram using a maximum likelihood approach such as REML, however, the results can vary according to the nature of the spatial variation. There remain issues to examine: how many fewer data can be used, how should the sampling sites be distributed over the site of interest, and how do different degrees of spatial variation affect the data requirements? The soil of four field sites of different size, physiography, parent material and soil type was sampled intensively, and MoM and REML variograms were calculated for clay content. The data were then sub-sampled to give different sample sizes and distributions of sites and the variograms were computed again. The model parameters for the sets of variograms for each site were used for cross-validation. Predictions based on REML variograms were generally more accurate than those from MoM variograms with fewer than 100 sampling sites. A sample size of around 50 sites at an appropriate distance apart, possibly determined from variograms of ancillary data, appears adequate to compute REML variograms for kriging soil properties for precision agriculture and contaminated sites. (C) 2007 Elsevier B.V. All rights reserved.

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.