Depth wise variation of microbial load in the soils of midland region of Kerala: a function of important soil physicochemical characteristics and nutrients

Soil microorganisms play a main part in organic matter decomposition and are consequently necessary to soil ecosystem processes maintaining primary productivity of plants. In light of current concerns about the impact of cultivation and climate change on biodiversity and ecosystem performance, it is vital to expand a complete understanding of the microbial community ecology in our soils. In the present study we measured the depth wise profile of microbial load in relation with important soil physicochemical characteristics (soil temperature, soil pH, moisture content, organic carbon and available NPK) of the soil samples collected from Mahatma Gandhi University Campus, Kottayam (midland region of Kerala). Soil cores (30 cm deep) were taken and the cores were separated into three 10-cm depths to examine depth wise distribution. In the present study, bacterial load ranged from 141×105 to 271×105 CFU/g (10cm depth), from 80×105 to 131×105 CFU/g (20cm depth) and from 260×104 to 47×105 CFU/g (30cm depth). Fungal load varies from 124×103 to 27×104 CFU/g, from 61×103 to110×103 CFU/g and from 16×103 to 49×103 CFU/g at 10, 20 and 30 cm respectively. Actinomycetes count ranged from 129×103 to 60×104 CFU/g (10cm), from 70×103 to 31×104 CFU/g (20cm) and from 14×103 to 66×103 CFU/g (30cm). The study revealed that there was a significant difference in the depthwise distribution of microbial load and soil physico-chemical properties. Bacterial, fungal and actinomycetes load showed a decreasing trend with increasing depth at all the sites. Except pH all other physicochemical properties showed decreasing trend with increasing depth. The vertical profile of total microbial load was well matched with the depthwise profiles of soil nutrients and organic carbon that is microbial load was highest at the soil surface where organics and nutrients were highest

Significance of soil microorganisms with special reference to climate change

There are a large number of agronomic-ecological interactions that occur in a world with increasing levels of CO2, higher temperatures and a more variable climate. Climate change and the associated severe problems will alter soil microbial populations and diversity. Soils supply many atmospheric green house gases by performing as sources or sinks. The most important of these gases include CH4, CO2 and N2O. Most of the green house gases production and consumption processes in soil are probably due to microorganisms. There is strong inquisitiveness to store carbon (C) in soils to balance global climate change. Microorganisms are vital to C sequestration by mediating putrefaction and controlling the paneling of plant residue-C between CO2 respiration losses or storage in semi-permanent soil-C pools. Microbial population groups and utility can be manipulated or distorted in the course of disturbance and C inputs to either support or edge the retention of C. Fungi play a significant role in decomposition and appear to produce organic matter that is more recalcitrant and favor long-term C storage and thus are key functional group to focus on in developing C sequestration systems. Plant residue chemistry can influence microbial communities and C loss or flow into soil C pools. Therefore, as research takings to maximize C sequestration for agricultural and forest ecosystems - moreover plant biomass production, similar studies should be conducted on microbial communities that considers the environmental situations

Content-Based Image Retrieval of Axial Brain Slices Using a Novel LBP with a Ternary Encoding

Retrieval of similar anatomical structures of brain MR images across patients would help the expert in diagnosis of diseases. In this paper, modified local binary pattern with ternary encoding called modified local ternary pattern (MOD-LTP) is introduced, which is more discriminant and less sensitive to noise in near-uniform regions, to locate slices belonging to the same level from the brain MR image database. The ternary encoding depends on a threshold, which is a user-specified one or calculated locally, based on the variance of the pixel intensities in each window. The variancebased local threshold makes the MOD-LTP more robust to noise and global illumination changes. The retrieval performance is shown to improve by taking region-based moment features of MODLTP and iteratively reweighting the moment features of MOD-LTP based on the user’s feedback. The average rank obtained using iterated and weighted moment features of MOD-LTP with a local variance-based threshold, is one to two times better than rotational invariant LBP (Unay, D., Ekin, A. and Jasinschi, R.S. (2010) Local structure-based region-of-interest retrieval in brain MR images. IEEE Trans. Inf. Technol. Biomed., 14, 897–903.) in retrieving the first 10 relevant images

A structural investigation relating to the pozzolanic activity of rice husk ashes

Various factors determine the applicability of rice husk ash (RHA) as a pozzolanic material. The amount and accessibility of reactive sites is thought to be a key factor. A structural study of RHA samples in relation to their reactivity has been performed; Silica in RHA formed by burning rice husk in a laboratory furnace under continuous supply of air have been characterized as a function of incineration temperature, time and cooling regime. The characterization methods included chemical analyses, conductivity measurements, microscopic analysis, X-ray diffraction (XRD) and 29Si magic-angle spinning (MAS) nuclear magnetic resonance (NMR). In line with earlier observations, the analyses show that the highest amounts of amorphous silica occur in samples burnt in the range of 500 °C–700 °C. The 29Si NMR data allow direct identification of the reactive silanol sites in the RHA samples. De-convolution of the NMR spectra clearly shows that the quickly cooled RHA resulting from burning rice husk for 12 h at 500 °C has the highest amount of silanol groups. This sample also induced the largest drop in conductivity when added to a saturated calcium hydroxide solution giving an indication of its reactivity towards lime. Therefore, this RHA is the favorable sample to be used as pozzolanic cement additive