Impact of Climatic Variability and Drought on Crop Yields in Kerala

In the present investigation, the impacts of the variability of the climatic parameters on the yields of major crops grown in the State are analyzed. In particular, the effects of rainfall variability on the water balances of the different regions in the State have been studied. Through this analysis the drought climatology of the region has been studied along with an overview of the climatic shifts involved in individual years. The relationship between weather parameters and crop yields over the State has been analyzed with case studies of two crops- coconut and paddy. Crop-weather models for forecasting coconut and paddy yields have been developed, which could be used for planning purposes

Spatio-temporal Variability of Atmospheric Ozone over Indian Subcontinent and its Relation to Meteorological Parameters

Ozone present in the atmosphere not only absorbs the biologically harmful ultraviolet radiation but also is an important ingredient of the climate system. The radiative absorption properties of ozone make it a determining factor in the structure of the atmosphere. Ozone in the troposphere has many negative impacts on humans and other living beings. Another significant aspect is the absorption of outgoing infrared radiation by ozone thus acting as a greenhouse gas. The variability of ozone in the atmosphere involves many interconnections with the incoming and outgoing radiation, temperature circulation etc. Hence ozone forms an important part of chemistry-climate as well as radiative transfer models. This aspect also makes the quantification of ozone more important. The discovery of Antarctic ozone hole and the role of anthropogenic activities in causing it made it possible to plan and implement necessary preventive measures. Continuous monitoring of ozone is also necessary to identify the effect of these preventive steps. The reactions involving the formation and destruction of ozone are influenced significantly by the temperature fluctuations of the atmosphere. On the other hand the variations in ozone can change the temperature structure of the atmosphere. Indian subcontinent is a region having large weather and climate variability which is evident from the large interannual variability of monsoon system over the region. Nearly half of Indian region comprises the tropical region. Most of ozone is formed in the tropical region and transported to higher latitudes. The formation and transport of ozone can be influenced by changes in solar radiation and various atmospheric circulation features. Besides industrial activities and vehicular traffic is more due to its large population. This may give rise to an increase in the production of tropospheric ozone which is greenhouse gas. Hence it becomes necessary to monitor the atmospheric ozone over this region. This study probes into the spatial distribution and temporal evolution of ozone over Indian subcontinent and discusses the contributing atmospheric parameters.

Thermohaline variability in the upper layers of the Arabian Sea

The Arabian Sea is an area of complex air-sea interaction processes with seasonal reversing monsoons. The associated thermohaline variability in the upper layers appears to control the large scale monsoon flow which is not yet completely understood. The variability in the thermohaline fields is known to occur in temporal domain ranging from intra-diurnal to inter-annual time scales and on spatial domains of few tens of kilometers to few thousands of kilometers. In the Arabian Sea though the surface temperature was routinely measured by both conventional measurements and satellites, the corresponding information on the subsurface thermohaline field is very sparse due to the lack cw adequate measurements. In such cases the numerical models offer promise in providing information on the subsurface features given an initial thermohaline field and surface heat flux boundary conditions. This thesis is an outcome of investigations carried out on the various aspects of the thermohaline variability on different time scales. In addition to the description of the mean annual cycle. the one dimensional numerical models of Miller (1976) and Price et a1 (1986) are utilised to simulate the observed mixed layer characteristics at selected locations in the Arabian Sea on time scales ranging from intra-diurnal to synoptic scales under variable atmospheric forcing.

Rainfall Climatology over Middle East Region and its Variability

A better understanding of the rainfall climatology of the Middle East region identifying the mechanisms responsible for the rain producing systems is essential for effective utilization of the water resources over the arid region. A comprehensive analysis on the rainfall climatology of the Middle East region is carried out to bring out the spatial and temporal variation of rainfall and mechanisms responsible for the rain events. The study was carried out utilizing rainfall, OLR, wind and humidity data sets procured from TRMM, NOAA and NCEP-NCAR. Climatology of annual rainfall brings out two areas of alarmingly low rainfall in the Middle East region: one in Egypt, Jordan and adjoining areas and the other in the southern part of Saudi Arabia. Daily rainfall analysis indicates that northern region gets rainfall mainly during winter and spring associated with the passage of Mediterranean low pressure systems whereas rain over the southern region is caused mainly by the monsoon organized convection, cross equatorial flow and remnants of low pressure systems associated with the monsoon during the summer season. Thermodynamic structure of the atmosphere reveals that the region does not have frequent local convection due to insufficient moisture content. The sinking motion associated with the sub tropic high pressure system and subsidence associated with the Walker circulation are responsible for maintaining warm and dry air over the region.

Spatial Variability and Contamination of Heavy Metals in the Inter-tidal Systems of a Tropical Environment

Heavy metals in the surface sediments of the two coastal ecosystems of Cochin, southwest India were assessed. The study intends to evaluate the degree of anthropogenic influence on heavy metal concentration in the sediments of the mangrove and adjacent estuarine stations using enrichment factor and geoaccumulation index. The inverse relationship of Cd and Zn with texture in the mangrove sediments suggested the anthropogenic enrichment of these metals in the mangrove systems. In the estuarine sediments, the absence of any significant correlation of the heavy metals with other sedimentary parameters and their strong interdependence revealed the possibility that the input is not through the natural weathering processes. The analysis of enrichment factor indicated a minor enrichment for Pb and Zn in mangrove sediments. While, extremely severe enrichment for Cd, moderate enrichment for Zn and minor enrichment of Pb were observed in estuarine system. The geo accumulation index exhibited very low values for all metals except Zn, indicating the sediments of the mangrove ecosystem are unpolluted to moderately polluted by anthropogenic activities. However, very strongly polluted condition for Cd and a moderately polluted condition for Zn were evident in estuarine sediments

Seasonal Variability Of Dissolved Nutrients In Mangrove Ecosystems Along South West Coast Of Kerala, India

The mangroves of Kerala are fast disappearing due to developmental activities.There are very few studies conducted in the chemical aspects of these ecosystems.The main objective of this study is to assess the spatial and seasonal variation of hydrographical as well as nutrients in mangrove ecosystems along Kerala coast. Five sampling sites least intervened by industries were selected for the study. Sampling was done for a period of six months in monthly intervals. A monsoonal hike of dissolved nutrients was observed in all ecosystems except in the constructed mangrove wetland. The constructed wetland exhibited a different hydrography and nutrient level in all seasons. The mangrove forest in this area consists of the species Bruguiera gymnorrhiza which has been planted since forty years.

Soft Computing Approach for Optimization of siRNA Efficiency Prediction for Post-transcriptional Gene Silencing

Post-transcriptional gene silencing by RNA interference is mediated by small interfering RNA called siRNA. This gene silencing mechanism can be exploited therapeutically to a wide variety of disease-associated targets, especially in AIDS, neurodegenerative diseases, cholesterol and cancer on mice with the hope of extending these approaches to treat humans. Over the recent past, a significant amount of work has been undertaken to understand the gene silencing mediated by exogenous siRNA. The design of efficient exogenous siRNA sequences is challenging because of many issues related to siRNA. While designing efficient siRNA, target mRNAs must be selected such that their corresponding siRNAs are likely to be efficient against that target and unlikely to accidentally silence other transcripts due to sequence similarity. So before doing gene silencing by siRNAs, it is essential to analyze their off-target effects in addition to their inhibition efficiency against a particular target. Hence designing exogenous siRNA with good knock-down efficiency and target specificity is an area of concern to be addressed. Some methods have been developed already by considering both inhibition efficiency and off-target possibility of siRNA against agene. Out of these methods, only a few have achieved good inhibition efficiency, specificity and sensitivity. The main focus of this thesis is to develop computational methods to optimize the efficiency of siRNA in terms of “inhibition capacity and off-target possibility” against target mRNAs with improved efficacy, which may be useful in the area of gene silencing and drug design for tumor development. This study aims to investigate the currently available siRNA prediction approaches and to devise a better computational approach to tackle the problem of siRNA efficacy by inhibition capacity and off-target possibility. The strength and limitations of the available approaches are investigated and taken into consideration for making improved solution. Thus the approaches proposed in this study extend some of the good scoring previous state of the art techniques by incorporating machine learning and statistical approaches and thermodynamic features like whole stacking energy to improve the prediction accuracy, inhibition efficiency, sensitivity and specificity. Here, we propose one Support Vector Machine (SVM) model, and two Artificial Neural Network (ANN) models for siRNA efficiency prediction. In SVM model, the classification property is used to classify whether the siRNA is efficient or inefficient in silencing a target gene. The first ANNmodel, named siRNA Designer, is used for optimizing the inhibition efficiency of siRNA against target genes. The second ANN model, named Optimized siRNA Designer, OpsiD, produces efficient siRNAs with high inhibition efficiency to degrade target genes with improved sensitivity-specificity, and identifies the off-target knockdown possibility of siRNA against non-target genes. The models are trained and tested against a large data set of siRNA sequences. The validations are conducted using Pearson Correlation Coefficient, Mathews Correlation Coefficient, Receiver Operating Characteristic analysis, Accuracy of prediction, Sensitivity and Specificity. It is found that the approach, OpsiD, is capable of predicting the inhibition capacity of siRNA against a target mRNA with improved results over the state of the art techniques. Also we are able to understand the influence of whole stacking energy on efficiency of siRNA. The model is further improved by including the ability to identify the “off-target possibility” of predicted siRNA on non-target genes. Thus the proposed model, OpsiD, can predict optimized siRNA by considering both “inhibition efficiency on target genes and off-target possibility on non-target genes”, with improved inhibition efficiency, specificity and sensitivity. Since we have taken efforts to optimize the siRNA efficacy in terms of “inhibition efficiency and offtarget possibility”, we hope that the risk of “off-target effect” while doing gene silencing in various bioinformatics fields can be overcome to a great extent. These findings may provide new insights into cancer diagnosis, prognosis and therapy by gene silencing. The approach may be found useful for designing exogenous siRNA for therapeutic applications and gene silencing techniques in different areas of bioinformatics.