Government of India

About: Government of India is a government organization based out in New Delhi, India. It is known for research contribution in the topics: Population & Government. The organization has 2945 authors who have published 2999 publications receiving 44942 citations. The organization is also known as: Union Government & Central Government.

Differential responses of photosynthetic parameters and its influence on carbohydrate metabolism in some contrasting rice (Oryza sativa L.) genotypes under arsenate stress.

Abstract: Influence of arsenic (As) in As tolerant and sensitive rice genotypes based chloroplastic pigments, leaf gas exchange attributes and their influence on carbohydrate metabolism were investigated in the present study As retards growth of crop plants and increase several health ailments by contaminating food chain Photosynthetic inhibition is known to be the prime target of As toxicity due to over-production of ROS Hydroponically grown rice seedlings of twelve cultivars were exposed to 25, 50, and 75 μM arsenate (AsV) that exerted negative impact on plastidial pigments content and resulted into inhibition of Hill activity Internal CO2 concentration lowered gradually due to interference of As with stomatal conductance and transpiration rate that subsequently led to drop in net photosynthesis Twelve contrasting rice genotypes responded differentially to As(V) stress Present study evaluated As tolerant and sensitive rice cultivars with respect to As(V) imposed alterations in pigments content, photosynthetic attributes along with sugar metabolism Starch contents, the principle carbohydrate storage declined differentially among As(V) stressed test cultivars, being more pronounced in cvs Swarnadhan, Tulaipanji, Pusa basmati, Badshabhog, Tulsibhog and IR-20 compared to cvs Bhutmuri, Kumargore, Binni, Vijaya, TN-1 and IR-64 Therefore, the six former cultivars tried to adapt defensive mechanisms by accumulating higher levels of reducing and non-reducing sugars to carry out basal metabolism to withstand As(V) induced alterations in photosynthesis This study could help to screen As tolerant and sensitive rice genotypes based on their photosynthetic efficiency in As polluted agricultural fields to reduce As contamination assisted ecotoxicological risk

Evaluation of performance of seasonal precipitation prediction at regional scale over India

Abstract: The seasonal scale precipitation amount is an important ingredient in planning most of the agricultural practices (such as a type of crops, and showing and harvesting schedules). India being an agroeconomic country, the seasonal scale prediction of precipitation is directly linked to the socioeconomic growth of the nation. At present, seasonal precipitation prediction at regional scale is a challenging task for the scientific community. In the present study, an attempt is made to develop multi-model dynamical-statistical approach for seasonal precipitation prediction at the regional scale (meteorological subdivisions) over India for four prominent seasons which are winter (from December to February; DJF), pre-monsoon (from March to May; MAM), summer monsoon (from June to September; JJAS), and post-monsoon (from October to December; OND). The present prediction approach is referred as extended range forecast system (ERFS). For this purpose, precipitation predictions from ten general circulation models (GCMs) are used along with the India Meteorological Department (IMD) rainfall analysis data from 1982 to 2008 for evaluation of the performance of the GCMs, bias correction of the model results, and development of the ERFS. An extensive evaluation of the performance of the ERFS is carried out with dependent data (1982–2008) as well as independent predictions for the period 2009–2014. In general, the skill of the ERFS is reasonably better and consistent for all the seasons and different regions over India as compared to the GCMs and their simple mean. The GCM products failed to explain the extreme precipitation years, whereas the bias-corrected GCM mean and the ERFS improved the prediction and well represented the extremes in the hindcast period. The peak intensity, as well as regions of maximum precipitation, is better represented by the ERFS than the individual GCMs. The study highlights the improvement of forecast skill of the ERFS over 34 meteorological subdivisions as well as India as a whole during all the four seasons.

Artificial intelligence in the pharmaceutical sector: current scene and future prospect

Abstract: Recently, artificial intelligence is growing rapidly in the pharmaceutical sector as well as the healthcare system. This new system showed its potential benefits in different pharmaceutical sectors like drug discovery, continuous manufacturing, dosage form design, quality control, and many more. This book chapter discusses different artificial intelligence tools and different applications of artificial intelligence in the pharmaceutical sector. Moreover, it also gives an idea about the implementation of artificial intelligence in the healthcare system and its potential benefits for the community. Lastly, it evokes some challenges and hurdles that are associated with the implementation of artificial intelligence in the pharmaceutical sector.

An inventory of salt-affected soils and waterlogged areas in the Nagarjunsagar Canal Command Area of southern India, using space-borne multispectral data

Abstract: Information is presented on the nature, extent and spatial distribution of waterlogged areas and salt-affected soils, derived through systematic visual interpretation of standard false colour composite (FCC) prints on a 1:100 000 scale generated from the Indian Remote Sensing Satellite (IRS-1B) Linear Imaging Self-scanning Sensor (LISS-I) and Landsat–Thematic Mapper (TM) data for the Nagarjunsagar Right Bank Canal Command Area, Andhra Pradesh. A total of 1710 ha of land in the coastal region has been found to be waterlogged. Salt-affected soils cover an area of 42 800 ha, with saline–sodic soils covering 28 480 ha emerging as the dominant category. To make optimal use of these lands and to prevent further degradation both preventive and ameliorative measures have been advocated. © 1998 John Wiley & Sons, Ltd.