Land use change detection along the Pravara River basin in Maharashtra, using remote sensing and GIS techniques

In the past few decades there has been an increasing pressure of population all over the world,especially in India, resulting in the utilization of every available patch of available land fromwoodlands to badlands. The study area represents a basin which is economically growing fast byconverting the fallow lands, badlands and woodlands to agricultural land for the past few decades.IRS (Indian Remote sensing Satellites) 1 C – LISS III and IRS 1 C PAN and IRS P6 – LISS III andIRS 1 D PAN Images were merged to generate imageries with resolution matching to the landscapeprocesses operating in the area. The images of the year 1997, 2000, 2004 and 2007 were analyzed todetect the changes in the landuse and landcover in the past ten years. The analysis reveals that therehas been 20% increase in the agricultural area over the past ten years. Built up area also has increasedfrom 1.35% to 6.36% of the area and dense vegetation also has marginally increased. The remarkableincrease in the agricultural area occurs owing to the reclaim of the natural ravines and fallow lands.Presently the area looks promising, but it is necessary to understand the sedimentological andgeomorphological characteristics of the area before massive invasion on any such landscapes becausethe benefit may be short lived

Studies on the effect of post harvest treatments on shelf life and quality of mango [Mangifera indica l.] cv. Amrapali

he physicochemical characteristics and shelf life of mango[Mangifera indica L.] fruits treated with calci- um chloride (CaCl2-1%, 2%), calcium nitrate (Ca(NO3)2-1%, 2%), potassium nitrate (KNO3-1%, 2%) and carboxyl methyl cellulose (CMC - 0.5, 1%) were studied. Untreated fruits served as the control. All tested treatments indicated a significant delay in the change of weight loss (16.84%), ripening (51.66%), decaying percentage (46.66) and retained firmness (3.23 kg/cm2) of fruits and biochemical qualities viz., total soluble solids(22.33Brix), sugar accumulation (18.17%) and tritratable acidity on 16th day in mango fruits compared to control. The significant (5%) impact of treatment is found on the least decay percentage in the order of fruits treated with calcium nitrate (2%) followed by 1% Ca(NO3)2, 2% CaCl2 and 1% CaCl2. Hence, it could be concluded that post harvest chemical treatment with calcium nitrate, calcium chloride (1%, 2%) has the potential to control spoilage, prolong the storage life and preserve valuable attributes of post harvest quality of mango, presumably because of its effect on inhibition of ripening and senescence processes by lowering the respiration rate

Improvement in Quality of Wine by Blending White and Coloured Grapes

Blending of juices from four white grape varieties viz., Thompson Seedless, Chenin Blanc, Sauvignon Blanc and Italia with three coloured varieties, viz., Shiraz, Ruby Red and Bangalore Blue, was done in 2:1 and 3:1 ratios to assess the effect of blending on wine quality. White varieties blended with Bangalore Blue recorded maximum titratable acidity (1.23%), while those blended with Ruby Red showed the least acidity (0.42%), Alcohol content in the wine ranged from 8.11% (Italia + Ruby Red, 2:1) to 12.04% (Chenin Blanc + Shiraz, 2:1). The range of values for tannin content (0.007% to 0.044 %) and total phenol content (228mg/l to 571mg/l) indicated that white varieties blended with the coloured cv. Shiraz had the lowest content of tannins and total phenols in wine, while, those blended with cv. Ruby Red showed highest content of these in the blended wines. Hence, among different blends, Chenin Blanc, Thompson Seedless, Sauvignon Blanc and Italia blended with the coloured variety Shiraz, in 2:1 ratio, produced good quality wine

Estimating soil loss from a watershed in Western Deccan, India, using Revised Universal Soil Loss Equation

USLE (Universal Soil Loss Equation) is the original and the most widely accepted soil loss estimation technique till date which has evolved from a design tool for conservation planning to a research methodology all across the globe. The equation has been revised and modified over the years and became a foundation for several new soil loss models developed all around the world. The equation has been revised as RUSLE by Renard et al. (1991) and is computed in GIS environment. The Revised equation is landuse independent which makes it a useful technique to apply in a variety of environment. The present paper is an attempt to estimate soil loss from a semi-arid watershed in Western Deccan, India by employing RUSLE. The region is a rocky terrain and sediments are restricted to only a few localities. The result indicates that the region is at the threshold of soil tolerance limit

Validation of the Kidney Disease Quality of Life-Short Form: a cross-sectional study of a dialysis-targeted health measure in Singapore

<p>Abstract</p> <p>Background</p> <p>In Singapore, the prevalence of end-stage renal disease (ESRD) and the number of people on dialysis is increasing. The impact of ESRD on patient quality of life has been recognized as an important outcome measure. The Kidney Disease Quality Of Life-Short Form (KDQOL-SF™) has been validated and is widely used as a measure of quality of life in dialysis patients in many countries, but not in Singapore. We aimed to determine the reliability and validity of the KDQOL-SF™ for haemodialysis patients in Singapore.</p> <p>Methods</p> <p>From December 2006 through January 2007, this cross-sectional study gathered data on patients ≥21 years old, who were undergoing haemodialysis at National Kidney Foundation in Singapore. We used exploratory factor analysis to determine construct validity of the eight KDQOL-SF™ sub-scales, Cronbach's alpha coefficient to determine internal consistency reliability, correlation of the overall health rating with kidney disease-targeted scales to confirm validity, and correlation of the eight sub-scales with age, income and education to determine convergent and divergent validity.</p> <p>Results</p> <p>Of 1980 haemodialysis patients, 1180 (59%) completed the KDQOL-SF™. Full information was available for 980 participants, with a mean age of 56 years. The sample was representative of the total dialysis population in Singapore, except Indian ethnicity that was over-represented. The instrument designers' proposed eight sub-scales were confirmed, which together accounted for 68.4% of the variance. All sub-scales had a Cronbach's α above the recommended minimum value of 0.7 to indicate good reliability (range: 0.72 to 0.95), except for Social function (0.66). Correlation of items within subscales was higher than correlation of items outside subscales in 90% of the cases. The overall health rating positively correlated with kidney disease-targeted scales, confirming validity. General health subscales were found to have significant associations with age, income and education, confirming convergent and divergent validity.</p> <p>Conclusions</p> <p>The psychometric properties of the KDQOL-SF™ resulting from this first-time administration of the instrument support the validity and reliability of the KDQOL-SF™ as a measure of quality of life of haemodialysis patients in Singapore. It is, however, necessary to determine the test-retest reliability of the KDQOL-SF™ among the haemodialysis population of Singapore.</p

A framework for human microbiome research

A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies

Structure, function and diversity of the healthy human microbiome

Author Posting. © The Authors, 2012. This article is posted here by permission of Nature Publishing Group. The definitive version was published in Nature 486 (2012): 207-214, doi:10.1038/nature11234.Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.This research was supported in part by National Institutes of Health grants U54HG004969 to B.W.B.; U54HG003273 to R.A.G.; U54HG004973 to R.A.G., S.K.H. and J.F.P.; U54HG003067 to E.S.Lander; U54AI084844 to K.E.N.; N01AI30071 to R.L.Strausberg; U54HG004968 to G.M.W.; U01HG004866 to O.R.W.; U54HG003079 to R.K.W.; R01HG005969 to C.H.; R01HG004872 to R.K.; R01HG004885 to M.P.; R01HG005975 to P.D.S.; R01HG004908 to Y.Y.; R01HG004900 to M.K.Cho and P. Sankar; R01HG005171 to D.E.H.; R01HG004853 to A.L.M.; R01HG004856 to R.R.; R01HG004877 to R.R.S. and R.F.; R01HG005172 to P. Spicer.; R01HG004857 to M.P.; R01HG004906 to T.M.S.; R21HG005811 to E.A.V.; M.J.B. was supported by UH2AR057506; G.A.B. was supported by UH2AI083263 and UH3AI083263 (G.A.B., C. N. Cornelissen, L. K. Eaves and J. F. Strauss); S.M.H. was supported by UH3DK083993 (V. B. Young, E. B. Chang, F. Meyer, T. M. S., M. L. Sogin, J. M. Tiedje); K.P.R. was supported by UH2DK083990 (J. V.); J.A.S. and H.H.K. were supported by UH2AR057504 and UH3AR057504 (J.A.S.); DP2OD001500 to K.M.A.; N01HG62088 to the Coriell Institute for Medical Research; U01DE016937 to F.E.D.; S.K.H. was supported by RC1DE0202098 and R01DE021574 (S.K.H. and H. Li); J.I. was supported by R21CA139193 (J.I. and D. S. Michaud); K.P.L. was supported by P30DE020751 (D. J. Smith); Army Research Office grant W911NF-11-1-0473 to C.H.; National Science Foundation grants NSF DBI-1053486 to C.H. and NSF IIS-0812111 to M.P.; The Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231 for P.S. C.; LANL Laboratory-Directed Research and Development grant 20100034DR and the US Defense Threat Reduction Agency grants B104153I and B084531I to P.S.C.; Research Foundation - Flanders (FWO) grant to K.F. and J.Raes; R.K. is an HHMI Early Career Scientist; Gordon&BettyMoore Foundation funding and institutional funding fromthe J. David Gladstone Institutes to K.S.P.; A.M.S. was supported by fellowships provided by the Rackham Graduate School and the NIH Molecular Mechanisms in Microbial Pathogenesis Training Grant T32AI007528; a Crohn’s and Colitis Foundation of Canada Grant in Aid of Research to E.A.V.; 2010 IBM Faculty Award to K.C.W.; analysis of the HMPdata was performed using National Energy Research Scientific Computing resources, the BluBioU Computational Resource at Rice University