954 resultados para Soil physical attributes


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Soil data and reliable soil maps are imperative for environmental management. conservation and policy. Data from historical point surveys, e.g. experiment site data and farmers fields can serve this purpose. However, legacy soil information is not necessarily collected for spatial analysis and mapping such that the data may not have immediately useful geo-references. Methods are required to utilise these historical soil databases so that we can produce quantitative maps of soil propel-ties to assess spatial and temporal trends but also to assess where future sampling is required. This paper discusses two such databases: the Representative Soil Sampling Scheme which has monitored the agricultural soil in England and Wales from 1969 to 2003 (between 400 and 900 bulked soil samples were taken annually from different agricultural fields); and the former State Chemistry Laboratory, Victoria, Australia where between 1973 and 1994 approximately 80,000 soil samples were submitted for analysis by farmers. Previous statistical analyses have been performed using administrative regions (with sharp boundaries) for both databases, which are largely unrelated to natural features. For a more detailed spatial analysis that call be linked to climate and terrain attributes, gradual variation of these soil properties should be described. Geostatistical techniques such as ordinary kriging are suited to this. This paper describes the format of the databases and initial approaches as to how they can be used for digital soil mapping. For this paper we have selected soil pH to illustrate the analyses for both databases.

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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.

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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.

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In this paper we pledge that physically based equations should be combined with remote sensing techniques to enable a more theoretically rigorous estimation of area-average soil heat flux, G. A standard physical equation (i.e. the analytical or exact method) for the estimation of G, in combination with a simple, but theoretically derived, equation for soil thermal inertia (F), provides the basis for a more transparent and readily interpretable method for the estimation of G; without the requirement for in situ instrumentation. Moreover, such an approach ensures a more universally applicable method than those derived from purely empirical studies (employing vegetation indices and albedo, for example). Hence, a new equation for the estimation of Gamma(for homogeneous soils) is discussed in this paper which only requires knowledge of soil type, which is readily obtainable from extant soil databases and surveys, in combination with a coarse estimate of moisture status. This approach can be used to obtain area-averaged estimates of Gamma(and thus G, as explained in paper II) which is important for large-scale energy balance studies that employ aircraft or satellite data. Furthermore, this method also relaxes the instrumental demand for studies at the plot and field scale (no requirement for in situ soil temperature sensors, soil heat flux plates and/or thermal conductivity sensors). In addition, this equation can be incorporated in soil-vegetation-atmosphere-transfer models that use the force restore method to update surface temperatures (such as the well-known ISBA model), to replace the thermal inertia coefficient.

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There are currently concerns within some sugar industries that long-term monoculture has led to soil degradation and consequent yield decline. An investigation was conducted in Swaziland to assess the effects of fallowing and green manuring practices, over a seven-month period, on sugarcane yields and the physical properties of a poorly draining clay soil. In the subsequent first sugarcane crop after planting, yields were improved from 129 t ha(-1) under continuous sugarcane to 141-144 t ha(-1) after fallowing and green manuring, but there were no significant responses in the first and second ratoon crops. Also, in the first crop after planting, root length index increased from 3.5 km m(-2) under continuous sugarcane to 5.2-6.8 km m(-2) after fallowing, and improved rooting was still evident in the first ratoon crop where there had been soil drying during the fallow period. Soil bulk density, total porosity and water-holding capacity were not affected by the fallowing practices. However, air-filled porosity increased from 11% under continuous sugarcane to 16% after fallowing, and steady state ponded infiltration rates were increased from 0.61 mm h(-1) to 1.34 mm h(-1), but these improvements were no longer evident after a year back under sugarcane. Levels of soil organic matter were reduced in all cases, probably as a result of the tillage operations involved. In the plant crop, root length was well correlated with air-filled porosity, indicating the importance of improving belowground air supply for crop production on poorly draining clay soils.

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Reclaimed water provides an important contribution to the water balance in water-scarce Jordan, but the quality of this water presents both benefits and challenges. Careful management of reclaimed water is required to maximize the nutrient benefits while minimizing the salinity risks. This work uses a multi-disciplinary research approach to show that soil response to irrigation with reclaimed water is a function of the management strategies adopted on the farm by the water user. The adoption of management methods to maintain soil productivity can be seen to be a result of farmers’ awareness to potentially plant-toxic ions in the irrigation water (70% of Jordan Valley farmers identified salinization as a hazard from irrigation with reclaimed water). However, the work also suggests that farmers’ management capacity is affected by the institutional management of water. About a third (35%) of farmers in the Jordan Valley claimed that their ability to manage salinization was limited by water shortages. Organizational interviews revealed that institutional awareness of soil management challenges was quite high (34% of interviewees described salinization as a risk from water reuse), but strategies to address this challenge at the institutional level require greater development.

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We present here an indicator of soil quality that evaluates soil ecosystem services through a set of 5 subindicators, and further combines them into a single general Indicator of Soil Quality (GISQ). We used information derived from 54 properties commonly used to describe the multifaceted aspects of soil quality. The design and calculation of the indicators were based on sequences of multivariate analyses. Subindicators evaluated the physical quality, chemical fertility, organic matter stocks, aggregation and morphology of the upper 5 cm of soil and the biodiversity of soil macrofauna. A GISQ combined the different subindicators providing a global assessment of soil quality. Research was conducted in two hillside regions of Colombia and Nicaragua, with similar types of land use and socio-economic context. However, soil and climatic conditions differed significantly. In Nicaragua, soil quality was assessed at 61 points regularly distributed 200 m apart on a regular grid across the landscape. In Colombia, 8 plots representing different types of land use were arbitrarily chosen in the landscape and intensively sampled. Indicators that were designed in the Nicaragua site were further applied to the Colombian site to test for their applicability. In Nicaragua, coffee plantations, fallows, pastures and forest had the highest values of GISQ (1.00; 0.80; 0.78 and 0.77, respectively) while maize crops and eroded soils (0.19 and 0.10) had the lowest values. Examination of subindicator values allowed the separate evaluation of different aspects of soil quality: subindicators of organic matter, aggregation and morphology and biodiversity of macrofauna had the maximum values in coffee plantations (0.89; 0.72 and 0.56, respectively on average) while eroded soils had the lowest values for these indicators (0.10; 0.31 and 0.33, respectively). Indicator formulae derived from information gained at the Nicaraguan sites were not applicable to the Colombian situation and site-specific constants were calculated. This indicator allows the evaluation of soil quality and facilitates the identification of problem areas through the individual values of each subindicator. It allows monitoring of change through time and can guide the implementation of soil restoration technologies. Although GISQ formulae computed on a set of data were only valid at a regional scale, the methodology used to create these indices can be applied everywhere.

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Physical, cultural and biological methods for weed control have developed largely independently and are often concerned with weed control in different systems: physical and cultural control in annual crops and biocontrol in extensive grasslands. We discuss the strengths and limitations of four physical and cultural methods for weed control: mechanical, thermal, cutting, and intercropping, and the advantages and disadvantages of combining biological control with them. These physical and cultural control methods may increase soil nitrogen levels and alter microclimate at soil level; this may be of benefit to biocontrol agents, although physical disturbance to the soil and plant damage may be detrimental. Some weeds escape control by these methods; we suggest that these weeds may be controlled by biocontrol agents. It will be easiest to combine biological control with. re and cutting in grasslands; within arable systems it would be most promising to combine biological control (especially using seed predators and foliar pathogens) with cover-cropping, and mechanical weeding combined with foliar bacterial and possibly foliar fungal pathogens. We stress the need to consider the timing of application of combined control methods in order to cause least damage to the biocontrol agent, along with maximum damage to the weed and to consider the wider implications of these different weed control methods.

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Recent studies have illustrated the effects of cis-9, trans-11 conjugated linoleic acid (CLA) on human health. Ruminant-derived meat, milk and dairy products are the predominant sources of cis-9, trans-11 CLA in the human diet. This study evaluated the processing properties, texture, storage characteristics, and organoleptic properties of UHT milk, Caerphilly cheese, and butter produced from a milk enriched to a level of cis-9, trans-11 CLA that has been shown to have biological effects in humans. Forty-nine early-lactation Holstein-British Friesian cows were fed total mixed rations containing 0 (control) or 45 g/kg ( on dry matter basis) of a mixture (1:2 wt/wt) of fish oil and sunflower oil during two consecutive 7-d periods to produce a control and CLA-enhanced milk, respectively. Milk produced from cows fed the control and fish and sunflower oil diets contained 0.54 and 4.68 g of total CLA/100 g of fatty acids, respectively. Enrichment of CLA in raw milk from the fish and sunflower oil diet was also accompanied by substantial increases in trans C18:1 levels, lowered C18: 0, cis-C18:1, and total saturated fatty acid concentrations, and small increases in n-3 polyunsaturated fatty acid content. The CLA-enriched milk was used for the manufacture of UHT milk, butter, and cheese. Both the CLA-enhanced butter and cheese were less firm than control products. Although the sensory profiles of the CLA-enriched milk, butter, and cheese differed from those of the control products with respect to some attributes, the overall impression and flavor did not differ. In conclusion, it is feasible to produce CLA-enriched dairy products with acceptable storage and sensory characteristics.

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The spatial variability of soil nitrogen (N) mineralisation has not been extensively studied, which limits our capacity to make N fertiliser recommendations. Even less attention has been paid to the scale-dependence of the variation. The objective of this research was to investigate the scale-dependence of variation of mineral N (MinN, N–NO3− plus N–NH4+) at within-field scales. The study was based on the spatial dependence of the labile fractions of SOM, the key fractions for N mineralisation. Soils were sampled in an unbalanced nested design in a 4-ha arable field to examine the distribution of the variation of SOM at 30, 10, 1, and 0.12 m. Organic matter in free and intra-aggregate light fractions (FLF and IALF) was extracted by physical fractionation. The variation occurred entirely within 0.12 m for FLF and at 10 m for IALF. A subsequent sampling on a 5-m grid was undertaken to link the status of the SOM fractions to MinN, which showed uncorrelated spatial dependence. A uniform application of N fertiliser would be suitable in this case. The failure of SOM fractions to identify any spatial dependence of MinN suggests that other soil variables, or crop indicators, should be tested to see if they can identify different N supply areas within the field for a more efficient and environmentally friendly N management.

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During the last twenty years, consumer choice in high income countries is no longer merely dictated by price and the organoleptic characteristics of a product, but also by other features some of which are not patently tangible. The growing importance of such attributes in the process of consumer choice is not only due to income increase, but also to changes in lifestyle such as migrations from the countryside, a generalized urbanization and consequential city life style, female emancipation and work outside the domestic walls for women, the drastic decrease in hard physical labor and the process of internationalization. The present survey study aims to explore the importance that Italian consumers give to fresh cut buying attributes and which of these attributes should be taken into consideration by industries in order to satisfy the needs of the most critical shoppers. Where possible, market and survey data for fresh cut products will be compared with those for cooked products and before presenting the results and conclusions of the study, the technical issues of processing will be highlighted owing to the fact that they affect the marketing of these products, the recent market situation with regard to consumption will be illustrated and the methodology used will be described.

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Soil organic matter (SOM) is one of the main global carbon pools. It is a measure of soil quality as its presence increases carbon sequestration and improves physical and chemical soil properties. The determination and characterisation of humic substances gives essential information of the maturity and stresses of soils as well as of their health. However, the determination of the exact nature and molecular structure of these substances has been proven difficult. Several complex techniques exist to characterise SOM and mineralisation and humification processes. One of the more widely accepted for its accuracy is nuclear magnetic resonance (NMR) spectroscopy. Despite its efficacy, NMR needs significant economic resources, equipment, material and time. Proxy measures like the fluorescence index (FI), cold and hot-water extractable carbon (CWC and HWC) and SUVA-254 have the potential to characterise SOM and, in combination, provide qualitative and quantitative data of SOM and its processes. Spanish and British agricultural cambisols were used to measure SOM quality and determine whether similarities were found between optical techniques and 1H NMR results in these two regions with contrasting climatic conditions. High correlations (p < 0.001) were found between the specific aromatic fraction measured with 1H NMR and SUVA-254 (Rs = 0.95) and HWC (Rs = 0.90), which could be described using a linear model. A high correlation between FI and the aromatics fraction measured with 1H NMR (Rs = −0.976) was also observed. In view of our results, optical measures have a potential, in combination, to predict the aromatic fraction of SOM without the need of expensive and time consuming techniques.

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Archived soils could represent a valuable resource for the spatio-temporal inventory of soil carbon stability. However, archived soils are usually air-dried before storage and the impact of a drying pretreatment on physically and chemically-defined C fractions has not yet been fully assessed. Through the comparison of field-moist and corresponding air-dried (at 25oC for 2 weeks) forest soil samples, we examined the effect of air-drying on: a) the quantity and the quality of cold- (CWEC) and hot-water (HWEC) extractable C and b) the concentration of C in physically isolated fractions (free- and intra-aggregate light and organo-mineral). Soil samples were collected from the organic (O) and mineral (A and B) horizons of three different forest soils from southeastern England: (i) Cambisol under Pine (Pinus nigra); (ii) Cambisol under Beech (Fagus sylvatica) and (iii) Gleysol under oak (Quercus robur). CWEC concentrations for dry samples were up to 2 times greater than for corresponding field moist samples and had significantly (p < 0.001) higher phenolic content. However, the effect of drying pretreatment on HWEC, its phenolic content was not significant (p > 0.05) for most samples. Dried soils had significantly (p < 0.001) higher concentrations of free light-C while having lower concentrations of intra-aggregate-C when compared to moist samples (p < 0.001). However, fine silt and clay fractions were not significantly affected by the drying pretreatment (p=0.789). Therefore, based on the results obtained from gleysol and cambisol forest soils studied here, C contents in hot-water extractions and fine particle size physical fractions (< 25µm) seem to be robust measurements for evaluating C fractions in dried stored forest soils. Further soil types should be tested to evaluate the wider generality of these findings.

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The determination of the amount of sample units that will compose the sample express the optimization of the workforce, and reduce errors inherent in the report of recommendation and evaluation of soil fertility. This study aimed to determine in three systems use and soil management, the numbers of units samples design, needed to form the composed sample, for evaluation of soil fertility. It was concluded that the number of sample units needed to compose the composed sample to determination the attributes of organic matter, pH, P, K, Ca, Mg, Al and H+Al and base saturation of soil vary by use and soil management and error acceptable to the mean estimate. For the same depth of collected, increasing the number of sample units, reduced the percentage error in estimating the average, allowing the recommendation of 14, 14 and 11 sample in management with native vegetation, pasture cultivation and corn, respectively, for a error 20% on the mean estimate.

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Microwave remote sensing has high potential for soil moisture retrieval. However, the efficient retrieval of soil moisture depends on optimally choosing the soil moisture retrieval parameters. In this study first the initial evaluation of SMOS L2 product is performed and then four approaches regarding soil moisture retrieval from SMOS brightness temperature are reported. The radiative transfer equation based tau-omega rationale is used in this study for the soil moisture retrievals. The single channel algorithms (SCA) using H polarisation is implemented with modifications, which includes the effective temperatures simulated from ECMWF (downscaled using WRF-NOAH Land Surface Model (LSM)) and MODIS. The retrieved soil moisture is then utilized for soil moisture deficit (SMD) estimation using empirical relationships with Probability Distributed Model based SMD as a benchmark. The square of correlation during the calibration indicates a value of R2 =0.359 for approach 4 (WRF-NOAH LSM based LST with optimized roughness parameters) followed by the approach 2 (optimized roughness parameters and MODIS based LST) (R2 =0.293), approach 3 (WRF-NOAH LSM based LST with no optimization) (R2 =0.267) and approach 1(MODIS based LST with no optimization) (R2 =0.163). Similarly, during the validation a highest performance is reported by approach 4. The other approaches are also following a similar trend as calibration. All the performances are depicted through Taylor diagram which indicates that the H polarisation using ECMWF based LST is giving a better performance for SMD estimation than the original SMOS L2 products at a catchment scale.