- Ambalika Ghosh
- B. K. Mahapatra
- A. D. Upadhyay
- Narendra Kumar Varma
- A. Saha
- R. P. Singh
- R. M. Sinha
- Subir Datta
- J. P. Mishra
- Minati Roy
- P. S. Parihar
- P. Kaushal
- Sharmishtha Paul
- Saurabh Saxena
- K. K. Dwivedi
- Mridul Chakraborti
- A. Radhakrishna
- D. R. Malaviya
- Meeti Punetha
- H. M. Ajithakumar
- Irshad Ahmed Para
- Deepanshu Gupta
- Mahendra Singh
- Jaya Bharati
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Roy, A. K.
- An Indepth Study on Fishery Resources and Scope of Utilization for Enhanced Production and Rural Employment Generation in West Bengal
Authors
1 ICAR-Central Institute of Fisheries Education (Deemed University), Kolkata Centre, 32 GN Block, Sector-V, Salt Lake, Kolkata-700 91, IN
Source
Journal of Environment and Sociobiology, Vol 12, No Sp Iss (2015), Pagination: 52-52Abstract
West Bengal is rich in both Marine and Inland fisheries resources. Marine fisheries resources include coast line (158 km) and continental shelf (17000 sq km). Inland fishery resources comprise of inland water bodies (5.45 lakh ha), rivers and canals (2,526 km), reservoirs (0.17 lakh ha), tanks and ponds (2.76 lakh ha), flood plain lakes/derelict waters (0.42 lakh ha) and brackish water (2.10 lakh ha). An in-depth study on distribution of district-wise inland fishery resources reveals that South and North 24 Parganas, Murshidabad, Burdwan, Purba and Paschim Medinipur are dominant in impounded freshwater areas. The districts of Purulia, Bankura, and Birbhum constitute 41.07% and 33.57% of total reservoir and bund areas of 28049.85 ha. Damodar, Subarnarekha, Teesta, Atreyee and Mahananda are the major riverine resources.
From 6th Five Year Plan to 11th Five Year Plan there is an increase from 4.025 lakh ton to 14.72 lakh ton of fish production registering an increase of 3.66 times. From 2004-05 to 2011-12 inland and marine sectors registered an increase in fish production of 1.21 and 1.13 times respectively. Catch, marketing and distribution of fish production is undertaken through the 3066 fishing crafts,17348 mechanised boats, 59 fish landing centers and spread across 188 fishing villages involving 76,981 fishermen families comprising of 3,80,138 fisher-folk population. Attention is herein drawn to the policy planners for allocation of resources to the respective districts rich either in ponds and tanks or reservoirs/ bunds or riverine wetlands for sustainable enhanced production for rural employment generation. Trend of fish production in relation to cause-effect variables and potential for enhanced production and are also highlighted in this communication.
- Outlook on Fish Seed and Fish Production and their Interrelationship at Uttar Pradesh
Authors
1 Department of Fisheries Economics and Statistics, College of Fisheries, Central Agricultural University, Lembuhcerra, Tripura West - 799210, IN
Source
Journal of Environment and Sociobiology, Vol 12, No Sp Iss (2015), Pagination: 55-56Abstract
Uttar Pradesh is India's most populous state with enough fisheries resources in the form of ponds, tanks, with dominance of rivers and man made reservoirs. Fish production in the state was only 325.95 thousand tones (2007-08) and it is less than national average. In this study trend of fish seed production and fish production and also their interrelationship was analyzed. The time series data analysis for period 1994-2008 reveals that both fish seed production and fish production in the state are increasing over the years. The regression equation of fish seed production and fish production is established (Yest= 0.275X-16.16; R2=0.971). This result clearly indicates a very good fit of the empirical data suggesting the fact that 97.1 % of the variability in fish production is explained by the seed production alone. A strong significant relation between two variables (R= 0.97) justifies the need of quality seed production for enhanced sustainable fish production.- Outlook on Fish Seed and Fish Production and their Interrelationship at Uttar Pradesh, India
Authors
1 Department of Fisheries Economics and Statistics, College of Fisheries, Central Agricultural University, Lembuhcerra, Tripura West-799210, IN
Source
Journal of Environment and Sociobiology, Vol 12, No 1 (2015), Pagination: 15-21Abstract
Uttar Pradesh is the India's most populous state with enough fisheries resources in the form of ponds, tanks, rivers and manmade reservoirs. Fish production in the State was only 325.95 thousand tones (2007-08) and it was less than national average. In this study trend of fish seed production and fish production, and also their inter relationships were analyzed. The time series data analysis for period 1994-2008 reveals that both fish seed production and fi sh production in the state have been increasing over the years. The regression equation of fish seed production and fish production is established (Yest = 0.275X-16.16; R2=0.971). This result clearly indicates a very good fit of the empherical data suggesting the fact that 97.1% of the variability in fish production is explained by the seed production alone. A strong significant relation between two variables (r=0.97) justifies the need of quality seed production for enhanced sustainable fish production.Keywords
Uttar Pradesh, Fish and Seed Production, Trend Analysis, Growth Rate.References
- Box, G. E. P., Jenkins, G. M. and Reinsel, G. C. 2007. Times-Series Analysis: Forecasting and Control. 3rd edition. Pearson Education, India 2006.
- Cook, R. M., Kunzlik, P. A. and Fryer, R. J. 1991. On the quality of North Sea cod stock forecasts. ICES J. Mar. Sci., 48: 1-13.
- Fox, W. W. 1975. Fitting the generalized stock production model by least-squares and equilibrium approximation. U.S. Fish Bull., 73: 23-36.
- Hanson, J. M. and Leggett, W. C. 1982. Empirical prediction of fish biomass and yield. Can. J. Fish. Aquat. Sci., 39: 257-263.
- Jensen, A. L. 1976. Time series analysis and forecasting of Atlantic menhaden catch. Chesapeake Science, 17: 305-307.
- Jensen, A. L. 1985. Time series analysis and the forecasting of menhaden catch and CPUE. N. Am. J. Fish. Manage., 5: 78-85.
- Katiha, P. K. 2000. Freshwater aquaculture in India: Status, potential and constraints: 98-108. In : Krishnam, M. and Birthal, P. S. (Eds) Aquacultural Development of India: Problems and Prospects. Workshop Proceedings-7, NCAP, New Delhi.
- Liu, L. M. and Hanssens, D. M. 1982. Identification of multiple-input transfer function models. Communication in Statistics-Theory and Methods, 11(3): 297-314.
- Mendelssohn, R. 1981. Using Box-Jenkins models to forecasting fishery dynamic: Identification, estimation and checking. U.S. Fish. Bull., 78: 887-896.
- Paul, R. K. and Das, M. K. 2010. Statistical modeling of inland and fish production in India. J. Inland Fish. Soc. India, 42(2): 1-7.
- Pella, J. J. and Tomlinson, R. K. 1969. A generalized stock production model. Bull. Inter-Amer. Trop. Tuna. Commn., 13: 421-496.
- Prepas, E. E. 1983. Total dissolved solids as a predictor of Lake Biomass and productivity. Can. J. Fish. Aquat. Sci., 40: 92-95.
- Roy, Ajit Kumar and Upadhyay, Anil, 2014. Fisheries Resource and Production Statistics of NE States of India - An Analytical Value Added Presentation.
- Narendra Publishing House, 1417, Kishan Dutt Street, Maliwara, DELHI - 110006, India (ISBN: 978-93-80428-95-6), 313pp.
- Roy. A. K., Panda, N. and Rath, D. P. 2008. Forecasting of culture fisheries production in India. J. Inland Fish. Soc. India, 40 (Spl.1): 54-59.
- Roy, A. K. and Sarangi, N. 2009. Modeling, Forecasting, Artificial Neural Network and Expert system in Fisheries and Aquaculture, Daya Publishing House, New Delhi, xv+239pp. (ISBN:1081-7035-571-0).
- Roy, A. K. 2009. Modeling in aquaculture. In: Modeling, Forecasting, Artificial Neural Network and Expert system in Fisheries and Aquaculture. (Eds. A. K. Roy and N. Sarangi). Daya Publishing House, New Delhi, pp. 67-86.
- Saila, S. B., Wigbout, M. and Lermit, R. J. 1979. Comparison of some time series models for the analysis of fisheries data. J. Cons. int. Explor. Mer. 39: 44-52.
- Schaefer, M. B. 1957. A study of the dynamics of the fishery for yellow fin in the eastern tropical Pacific Ocean. Bull. Inter-Amer. Trop. Tuna Comm., 2: 245-285.
- Stergiou, K. I. 1989. Modeling and forecasting the fishery for pilchard (Sardina pilchardus) in Greek waters using ARIMATIME SERES MODELS. J. Cons. int. Explor. Mer., 46: 16-23.
- Stergiou, K. I. 1990. Prediction of the Mullidae fishery in the eastern Mediterranean 24 months in advance. Fish. Res., 9: 67-74.
- Stergiou, K. I., 1991. Describing and forecasting the sardine-anchovy complex in the eastern Mediterranean using vector autoregressions. Fish. Res., 11: 127-141.
- William, E. G., 1986. Systems analysis and simulation in wildlife and fisheries science. John Wiley and Sons, New York, NY, 338 pp.
- http://www.fisheries.up.nic.in (website of Department of Fisheries, Govt. of Uttar Pradesh).
- Application of Soil Radon and Trace Element Geochemistry for Uranium Exploration at Kuchanapalle, Guntur District, Andhra Pradesh
Authors
1 Atomic Minerals Directorate for Exploration and Research, New Delhi, IN
2 Atomic Minerals Directorate for Exploration and Research Jamshedpur, IN
3 Atomic Minerals Directorate for Exploration and Research, Hyderabad-16, IN
Source
Journal of Geological Society of India (Online archive from Vol 1 to Vol 78), Vol 56, No 1 (2000), Pagination: 89-96Abstract
A radioactive fault breccia zone trending N30°E is exposed intermittently within the puru granite dome, near Kuchanapalle village in the NE margin of Cuddapah basin. A major part of the fault zone is under soil cover. Within this fault zone, a dark coloured ferruginous and uraniferous fault breccia is exposed over an area of 150m x 2.5m. In order to trace the continuity of the concealed fault zone, the uraniferous breccia zone was tested by closed circuit soil-gas radon (CCT) measurement, solid state nuclear track detection (SSNTD) survey, and trace element analysis of augur-hole soil samples. Radon levels in 164 auger holes vary from 9 to 863 per 50 sec. The alpha track density on cellulose nitrate films used in SSNTD surveys varies from 27 to 820 per sq. mm. The iso-alpha track density map has confirmed the anomalous patterns obtained by the soil-radon survey.Trace element data of soil samples have been processed using R-mode factor analysis of correlation matrix. These data along with radon and SSNTD surveys have thus been found to be very effective in delineating the extension of the radioactive breccia zone under soil cover, up to 1200 m towards north.
Keywords
Economic Geology, Exploration Geochemistry, Soil Radon Surveys, Uranium, Cuddapah Basin, Andhra Pradesh.- Modified Speed Sensor-less Grid Connected DFIG based WECS
Authors
1 Department of Electrical Engineering, Mizoram University, Aizawl, Mizoram - 7960 04, IN
2 Department of Electrical Engineering, National Institute of Technology, Silchar - 788 010, IN
Source
Indian Journal of Science and Technology, Vol 8, No 16 (2015), Pagination:Abstract
This paper presents a new Phase Locked Loop (PLL) based slip speed estimator for speed sensor less field oriented vector control operation of variable speed grid connected Wind Energy Conversion System (WECS). Three phase rotor current is used to design a PLL based slip estimator for speed sensor-less vector control operation of rotor side converter. The proposed speed sensor-less grid connected Double Fed Induction Generator (DFIG) based WECS is used for decoupled control of stator active and reactive power to ensure maximizing the power generation at unity power factor under varying wind speed. The speed sensor-less Vector control scheme is also incorporated with an optimal speed tracking controller for maximum energy capture in the rated wind speed range and restrict the mechanical output power to the rated value using pitch angle control when the wind velocity crosses rated limit to prevent overloading and outage of the wind turbine. The proposed method does not require the information of rotor speed or position for speed sensor less DFIG based WECS unlike other published methods. Simulation has been carried out in MATLAB/Simulink environment and results have been analyzed. Results show that the proposed speed sensor-less DFIG system can operate at its optimum energy level for a wide range of wind speed and is capable for satisfactory operation of the variable speed WECS.Keywords
DFIG, PLL, Slip Speed Estimator, Speed Sensor-Less, WECS- Radioactive Carbonaceous Material within the Fractured Bundelkhand Granite of Gwalior Basin at Dursendi, Gwalior District, Madhya Pradesh - A Petrographic Revelation
Authors
1 AMD, Department of Atomic Energy, Northern Region, New Delhi-110066, IN
2 AMD, Department of Atomic Energy, F-1149, Chittaranjan Park, New Delhi (Ex AMD, NR, New Delhi), IN
3 AMD, Department of Atomic Energy, Head Quarter, Hyderabad-500016, IN
Source
Journal of Geological Society of India (Online archive from Vol 1 to Vol 78), Vol 72, No 4 (2008), Pagination: 479-483Abstract
Radioactive carbonaceous matter, possibly of organic origin, with coffinite inclusions {U(SiO4)1_x(OH)4x} are reported for the first time in the fractures within the core samples of highly deformed Bundelkhand granitoids in the Gwalior Basin. Intense hydrothermal alterations along these fractures are manifested in the form of silicification, argillic alteration (clay formation), chlontisation, ferruginisation and by sulphide formation. The globular radioactive carbonaceous matter is of organic origin and generally associated with silica rich veins. Globular nature of this carbonaceous matter indicates their formation from coagulation of smaller colloids in a low temperature hydrotherm. Mixing of descending oxidizing hydrotherm derived from basinal fluid rich in heavy metals, uranium, organic matter and ascending reducing fluid (hydrotherm) rich in H2S and Si in these fracture zones has resulted in the precipitation of sulphides, secondary quartz, carbonaceous material and coffinite.Keywords
Radioactive Material, Bundelkhand Granite, Gwalior Basin, Madhya Pradesh.- Generating Higher Ploidies (7x and 11x) in Guinea Grass (Panicum maximum Jacq.) Utilizing Reproductive Diversity and Uncoupled Apomixis Components
Authors
1 Crop Improvement Division, Indian Grassland and Fodder Research Institute, Jhansi 284 003, IN
Source
Current Science, Vol 109, No 8 (2015), Pagination: 1392-1395Abstract
No Abstract.- Role of Groundwater in National Economy
Authors
1 Geological Survey of India, IN
Source
Journal of the Association of Engineers, India, Vol 46, No 4 (1971), Pagination: 247-250Abstract
Water plays a very vital role in our national economy. It is a very important natural resource which not only sustains life but provides a very essential input for agriculture, industry and community use. Groundwater forms a major source of water supply. Groundwater as a resource has inherent characteristics which render its development rather problematic in comparison to other natural sources.- The Role of the Technologists and Geohydrologists in the Green Revolution of India
Authors
1 Geological Survey of India, IN
Source
Journal of the Association of Engineers, India, Vol 45, No SPL (1970), Pagination: 9-12Abstract
In the literal sense, technologists are primarily concerned with designing and improvement of the methodology of various technological systems. However, here it is intended to use the term more broadly to those group of scientists who are actively applying scientific knowledge in the service of humanity, to improve the standards of the social environment. To this group belongs the geohydrologist, who compounds the field concepts of geology and the mathematical concepts of hydrology to assist the community in harnessing the available water resources, with proper emphasis on its conservation and rational utilisation. The geohydrologist represents a compendium of scientific and technological knowledge of various disciplines in the realm of the water science.- Immunomodulatory Effects of Probiotics and Prilled Fat Supplementation on Immune Genes Expression and Lymphocyte Proliferation of Transition Stage Karan Fries Cows
Authors
1 Division of Animal Physiology, National Dairy Research Institute, Karnal - 132 001, Haryana, IN
2 Division of Physiology and Climatology, Indian Veterinary Research Institute, Izzatnagar - 243 122, Bareilly, Uttar Pradesh, IN
Source
Veterinary World, Vol 11, No 2 (2018), Pagination: 209-214Abstract
Background and Aim: Probiotics are the living microorganism which when administered improves the digestion and health of the animal. Saccharomyces cerevisiae (SC) improves the humoral and innate immunity of the animal. Prilled fat is a hydrogenated palm oil triglyceride which has been reported to promote the release of cytokines from macrophages. The aim of the study was to evaluate the immunomodulatory effect of probiotic and prilled fat during transition stage in Karan Fries (KF) cows.
Materials and Methods: A total of 12 KF cows at 21 days prepartum were selected and divided into two groups of six animals each. The control group was fed as per the standard feeding practices and the supplemented group cows were supplemented daily with prilled fat at 100 g/cow, SC at 25 g/cow, and sweetener at 1 g/cow in addition to the standard feeding practices from −30 days of prepartum to 21 days of lactation. The sweetener was added to improve the palatability of the feed. The natural sweetener of an African plant leave had 105 times more sweetness than glucose with good aroma. The dry matter intake of the animal was recorded. Plasma samples were collected weekly from all cows for the analysis of blood metabolite beta-hydroxybutyric acid (BHBA). Lymphocytes were isolated from the blood for studying the expression of tumor necrosis factor alpha (TNF-α) and interleukin-1β (IL-1β) and for estimating lymphocyte proliferation index (LPI).
Results: The upregulated IL-1β and TNF-α around calving might be possibly associated to the metabolic changes occurring during the transition period and suggest a higher degree of inflammation around parturition. High concentrations of BHBA caused increased expression and synthesis of the pro-inflammatory factors such as TNF-α and IL-1β in supplemented group in primary calf hepatocytes. The LPI was higher in supplemented group as compared to control which suggests a stimulatory effect of unsaturated fatty acids on mitogen-stimulated T-cell proliferation.
Conclusion: Dietary supplementation of probiotics, prilled fat, and sweetener alleviated negative energy balance by stimulating feed intake and modulating hepatic lipid metabolism; and both of these additives improved the postpartum health (antioxidant status and immune function) of transition dairy cows.
Keywords
Beta-Hydroxybutyric Acid, Crossbred Cows, Dry Matter Intake, Interleukin-1β, Lymphocyte Proliferation Index, Prilled Fat, Saccharomyces cerevisiae, Tumor Necrosis Factor Alpha.- Engineering Apomixis in Rice
Authors
1 ICAR-National Institute of Biotic Stress Management, Raipur 493 225, IN
2 ICAR-Indian Grassland and Fodder Research Institute, Jhansi 284 003, IN
3 ICAR-Indian Institute of Sugarcane Research, Lucknow 226 002, IN
Source
Current Science, Vol 121, No 12 (2021), Pagination: 1535-1537Abstract
No Abstract.Keywords
No Keywords.References
- Hand, M. L. and Koltunow, A. M. G., Genetics, 2014, 197, 441–450.
- Conner, J. A. and Ozias-Akins, P., Methods Mol. Biol., 2017, 1669, 17–34.
- Kaushal, P., Zadoo, S. N., Malaviya, D. R. and Roy, A. K., Curr. Sci., 2005, 89, 1092–1096.
- Koltunow, A. M. and Grossniklaus, U., Annu. Rev. Plant Biol., 2003, 54, 547– 574.
- Pupilli, F. and Barcaccia, G., J. Biotechnol., 2012, 159, 291–311.
- Schmidt, A., Schmid, M. W. and Grossniklaus, U., Development, 2015, 142, 229–241.
- Brukhin, V., Russ. J. Genet., 2017, 53, 943–964.
- Marimuthu, M. P. et al., Science, 2011, 331, 876.
- Kaushal, P., Malaviya, D. R. and Roy, A. K., Curr. Sci., 2004, 87, 292–296.
- Gaafer, R. M., El Shanshoury, A. R., El Hisseiwy, A. A., AbdAlhak, M. A., Omar, A. F., El Wahab, M. M. A. and Nofal, R. S., Ann. Agric. Sci., 2017, 62, 51–60.
- Khanday, I., Skinner, D., Yang, B., Mercier, R. and Sundaresan, V., Nature, 2019, 565, 91–95.
- Boutilier, K. et al., Plant Cell, 2002, 14, 1737–1749.
- d’Erfurth, I., Jolivet, S., Froger, N., Catrice, O., Novatchkova, M. and Mercier, R., PLoS Biol., 2009, 7, e1000124.
- Mieulet, D. et al., Cell Res., 2016, 26, 1242–1254.
- Ravi, M., Marimuthu, M. P. A. and Siddiqi, I., Nature, 2008, 451, 1121–1124.
- Kirioukhova, O. et al., Sci. Rep., 2018, 8, 10626.
- Kaushal, P. et al., Euphytica, 2018, 214, 152–173.
- Conner, J. A., Podio, M. and Ozias-Akins, P., Plant Reprod., 2017, 30, 41–52.
- Horst, N. A., Katz, A., Pereman, I., Decker, E. L., Ohad, N. and Reski, R., Nature Plants, 2016, 2, 15209.
- Ravi, M. and Chan, S. W. L., Nature, 2010, 464, 615–618.
- Kaushal, P., Dwivedi, K. K., Radhakrishna, A., Srivastava, M. K., Kumar, V., Roy, A. K. and Malaviya, D. R., Front. Plant Sci., 2019, 10, 256.
- Henderson, S. T., Johnson, S. D., Eichmann, J. and Koltunow, A. M. G., Ann. Bot., 2017, 119, 1001–1010.
- Paul, P., Awasthi, A., Kumar, S., Verma, S. K., Prasad, R. and Dhaliwal, H. S., Plant Cell Rep., 2012, 31, 1779–1787.
- Michel, M. R. et al., In Maize Germplasm – Characterization and Genetic Approaches for Crop Improvement, 2018; http://dx.doi.org/10.5772/intechopen.70549.
- Maheshwari, S. C., Maheshwari, N., Khurana, J. P. and Sopory, S. K., Curr. Sci., 1998, 75, 1141–1147.