975 resultados para Soil Science


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The most biological diversity on this planet is probably harbored in soils. Understanding the diversity and function of the microbiological component of soil poses great challenges that are being overcome by the application of molecular biological approaches. This review covers one of many approaches being used: separation of polymerase chain reaction (PCR) amplicons using denaturing gradient gel electrophoresis (DGGE). Extraction of nucleic acids directly from soils allows the examination of a community without the limitation posed by cultivation. Polymerase chain reaction provides a means to increase the numbers of a target for its detection on gels. Using the rRNA genes as a target for PCR provides phylogenetic information on populations comprising communities. Fingerprints produced by this method have allowed spatial and temporal comparisons of soil communities within and between locations or among treatments. Numerous samples can be compared because of the rapid high throughput nature of this method. Scientists now have the means to begin addressing complex ecological questions about the spatial, temporal, and nutritional interactions faced by microbes in the soil environment.

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Terminal restriction fragment length polymorphism (T-RFLP) analysis is a polymerase chain reaction (PCR)-fingerprinting method that is commonly used for comparative microbial community analysis. The method can be used to analyze communities of bacteria, archaea, fungi, other phylogenetic groups or subgroups, as well as functional genes. The method is rapid, highly reproducible, and often yields a higher number of operational taxonomic units than other, commonly used PCR-fingerprinting methods. Sizing of terminal restriction fragments (T-RFs) can now be done using capillary sequencing technology allowing samples contained in 96- or 384-well plates to be sized in an overnight run. Many multivariate statistical approaches have been used to interpret and compare T-RFLP fingerprints derived from different communities. Detrended correspondence analysis and the additive main effects with multiplicative interaction model are particularly useful for revealing trends in T-RFLP data. Due to biases inherent in the method, linking the size of T-RFs derived from complex communities to existing sequence databases to infer their taxonomic position is not very robust. This approach has been used successfully, however, to identify and follow the dynamics of members within very simple or model communities. The T-RFLP approach has been used successfully to analyze the composition of microbial communities in soil, water, marine, and lacustrine sediments, biofilms, feces, in and on plant tissues, and in the digestive tracts of insects and mammals. The T-RFLP method is a user-friendly molecular approach to microbial community analysis that is adding significant information to studies of microbial populations in many environments.

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National Natural Science Foundation of China [30590381]; Knowledge Innovation Program of the Chinese Academy of Sciences [KZCX2YW-432]; International Partnership Project

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National Science Fund for Distinguished Young Scholars of China [40225004]; National Natural Science Foundation of China [40471048]

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In addition to classical methods, namely kriging, Inverse Distance Weighting (IDW) and splines, which have been frequently used for interpolating the spatial patterns of soil properties, a relatively more accurate surface modelling technique is being developed in recent years, namely high accuracy surface modelling (HASM). It has been used in the numerical tests, DEM construction and the interpolation of climate and ecosystem changes. In this paper, HASM was applied to interpolate soil pH for assessing its feasibility of soil property interpolation in a red soil region of Jiangxi Province, China. Soil pH was measured on 150 samples of topsoil (0-20 cm) for the interpolation and comparing the performance of HASM, kriging. IDW and splines. The mean errors (MEs) of interpolations indicate little bias of interpolation for soil pH by the four techniques. HASM has less mean absolute error (MAE) and root mean square error (RMSE) than kriging, IDW and splines. HASM is still the most accurate one when we use the mean rank and the standard deviation of the ranks to avoid the outlier effects in assessing the prediction performance of the four methods. Therefore, HASM can be considered as an alternative and accurate method for interpolating soil properties. Further researches of HASM are needed to combine HASM with ancillary variables to improve the interpolation performance and develop a user-friendly algorithm that can be implemented in a GIS package. (C) 2009 Elsevier B.V. All rights reserved.