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Not AvailableThe spatial and temporal inconsistency of rainfall has increased during the recent decade, particularly in rainfed regions of the country. The rainfed areas face deficit and surplus distribution of rainfall during critical stages of crop growth. Therefore, planning of different agricultural activities consistent with these changes and specific crop is envisaged as key to safe guard against crop failure. In this study, analysis of 36 years (1980-2016) rainfall data using Markov chain model is used to find initial, conditional and consecutive dry and wet week probability and rainfall at different probability levels using incomplete gamma distribution. The forward and backward accumulation of rainfall is used for assessment of onset and withdrawal of rainy season. The weekly water balance for water deficit and surplus is carried using Thornthwaite method and best fit frequency distribution is identified for annual water deficit using chi square test. The average annual rainfall of Mirzapur district is found to be 1022.17 mm with 21.6% coefficient of variation. The onset and withdrawal of rainy season starts effectively from 24th week (11-17 June) and under delayed condition, rainy season starts by 26th week (25 June-01 July). Under normal conditions, the rainy season starts by 25th week (18-24 June). The rainy season ends at earliest by 42th week (18-24 October) and under delayed condition rainy season may end by 50th week (11- 16 December). Under normal condition rainy season ends by 46th week (10-16 November).The Gumbel distribution is found suitable for predicting annual water deficit based on Chi-square test.Not Availabl

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Not AvailableThe information regarding the period and magnitude of water deficit is critical so that advance actions can be taken to avoid moisture stress to the crops. A method for predicting the weekly dynamics of water consumption deficit in agricultural crops using three decades (1984-2013) of meteorological data is developed for Mirzapur, District (Uttar Pradesh) in Vindhya Zone of Indo-Gangetic Plains. The turning point test shows that the weekly water deficit is identically distributed and Kendall's rank correlation test show that there is no definite trend of weekly water deficit. The auto correlation function analyzed using Fourier series shows that the periodicity is observed in weekly water deficit. The significant harmonics is also identified and statistical properties of the generated weekly water deficit series is compared with the observed weekly water deficit. The developed stochastic model is validated by predicting weekly water deficit for the next two years and compared with the observed water deficit. The mean weekly water deficit varied from minimum 0.34 mm in starting of August (32 SMW) to maximum 40.17 mm in middle of June (22 SMW). The mean water deficit for Mirzapur district is 12.38 mm week-1. The coefficient of correlation of observed and simulated weekly water deficit is 0.89. The simulated weekly water deficit using developed model can be used for forecasting of weekly water deficit and optimization of life saving irrigation for different crops at Mirzapur district as drought mitigation strategy under climate change scenario.Not Availabl

Assessment of Eco-Environmental Vulnerability Using Remote Sensing and GIS Tools in Maharashtra Region, India

Maharashtra region is prone to various disasters such as drought, floods, cyclones and earthquake and has been exposed to extreme weather events like dry spells. Communities within these dry lands are poor and face extreme conditions of water stress. This study has been carried out to analyze and quantify climatic and anthropogenic effect on eco-environmental vulnerability dynamic change. To achieve that a numerical model is set up, consisting of eight factors that are elevation, land use, drought, slope, NDVI, soil-type, soil erosion (water), and population density index & has been evaluated using the method of spatial principle component analysis (SPCA) on Remote Sensing and GIS platform. The integrated eco-environmental vulnerability index (EVI) of study area is estimated to analyse spatial-temporal dynamic vulnerability changes in the 11 years gap from 2000 and 2011. The results show that the study area has become eco-environmental vulnerable slightly (about 80% of the region) with an increased eco-environmental vulnerability integrated index (EVSI) value by more than 50% (i.e., about 74%) and the driving force of dynamic change is mainly caused by socio-economic activities. In addition the estimation has been regionalized into thirty-four districts to serve as a base for decision-making for eco-environmental recovering and rebuilding. It is found that the most vulnerable district in 2011 is Ratnagiri and the least one is Sangli. There are nine districts which shows more than 100% increase in EVSI value, with the highest increase in Hingoli(100.65%), indicating that the districts have become most environmental vulnerable in the study-period. The research concludes that the method, supported by G.I.S using SPCA can’t only represent distinctly the input spatial distribution of plain-mountain-belt feature, but also respect the whole river-valley as a single unit

Identification of Soil Erosion Prone Areas of Madhya Pradesh using USLE/RUSLE

Soil erosion is caused due to the dynamic action of erosive agents, mainly water, and is a major threat to the environment. Primary aim of the present study was to study the soil loss dynamics, and identify the environmental hotspots in Madhya Pradesh to aid decision-makers to plan and prioritize appropriate conservation measures. Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE) models were applied for erosion rate estimation by generating thematic maps of R (Rainfall erosivity factor), K (Soil erodibility factor), LS (Topographic factor), C (Cover and management factor), and P (Support practice factor) factors by using several input parameters in QGIS software. Subsequently, the different classes of soil erosion and percentage area under these classes were identified. The average annual soil erosion for the entire state as obtained from the USLE and RUSLE model were 5.80 t.ha-1.yr-1 and 6.64 t.ha-1.yr-1, respectively. The areas under severe risk were 1.09 % and 1.80 %, and very severe risk areas were 1.57 % and 1.83 % as estimated by USLE and RUSLE model, respectively. As compared to RUSLE model, USLE model underestimated rate of soil erosion for most river basins of the state as well as for the entire state

Evaluation of Class-A Pan Coefficient Models for Estimation of Reference Crop Evapotranspiration for Dry Sub-humid Climates

Evaporation and evapotranspiration are important parameters for various agricultural activities, which may be estimated using a pan coefficient value obtained from several models. It is a function of wind speed, temperature, relative humidity and fetch length. For dry sub-humid climate of Varanasi, Snyder model was found to be best for estimating the pan coefficient with an average value of 0.79, which closely agreed with pan coefficient value estimated by the standard FAO-56 model. The maximum and minimum average daily pan evaporation for the region was 8.8 mm.day-1 and 2.5 mm.day-1, respectively, in the month of May and December. The reference evapotranspiration estimated using pan coefficient obtained from Snyder method showed lowest MAE of 0.24, RMSE of 0.30, agreement Index of 0.99, percentage error of estimate of 6.51 % and efficiency of 96 per cent. The Mann-Kendall’s non-parametric test used for identifying trend showed an increasing trend for pan coefficient data series, and a decreasing trend for pan evaporation data series at 5 % significance level. Tempoal variation in pan coefficient may be computed for Varanasi meteorological station to estimate reference evapotranspiration

Elucidation of Antiviral and Antioxidant Potential of C-Phycocyanin against HIV-1 Infection through In Silico and In Vitro Approaches

Antiretroviral therapy is the single existing therapy for patients infected with HIV; however, it has drawbacks in terms of toxicity and resistance. Thus, there is a continuous need to explore safe and efficacious anti-retroviral agents. C-Phycocyanin (C-PC) is a phycobiliprotein, which has been known for various biological properties; however, its effect on HIV-1 replication needs revelation. This study aimed to identify the inhibitory effects of C-PC on HIV-1 using in vitro and in silico approaches and to assess its role in the generation of mitochondrial reactive oxygen species (ROS) during HIV-1 infection. In vitro anti-HIV-1 activity of C-PC was assessed on TZM-bl cells through luciferase gene assay against four different clades of HIV-1 strains in a dose-dependent manner. Results were confirmed in PBMCs, using the HIV-1 p24 antigen assay. Strong associations between C-PC and HIV-1 proteins were observed through in silico molecular simulation-based interactions, and the in vitro mechanistic study confirmed its target by inhibition of reverse transcriptase and protease enzymes. Additionally, the generation of mitochondrial ROS was detected by the MitoSOX and DCF-DA probe through confocal microscopy. Furthermore, our results confirmed that C-PC treatment notably subdued the fluorescence in the presence of the virus, thus reduction of ROS and the activation of caspase-3/7 in HIV-1-infected cells. Overall, our study suggests C-PC as a potent and broad in vitro antiviral and antioxidant agent against HIV-1 infection

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Not AvailableThis study presents the application of analytical hierarchical process based multicriteria decision support tool for prioritization of critical areas of Andhiyarkhore catchment for soil and water conservation (SWC) and management works. Fourteen different soil and water management parameters were calculated for each of the fiftyone delineated watersheds in Andhiyarkhore catchment. The normalized values of these parameters were arranged in a comparison matrix to assess corresponding weights to prioritize the watersheds. The average annual soil loss had highest weight of 0.23 and elongation ratio the minimum weight of 0.01 at 9.66% consistency ratio (within 10% limit). The highest priority for the SWC measures was obtained for SW-7 watershed and lowest for SW-47 watershed. The average annual groundwater recharge estimated in the Andhiyarkhore catchment was only 4.13% of average annual rainfall, which envisages need for SWC works in Andhiyarkhore catchment. Nine watersheds having 325.7 km2 of the catchment have very high priority for undertaking SWC works.Not Availabl