Journal of Environment and Sociobiology

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Outlook on Fish Seed and Fish Production and their Interrelationship at Uttar Pradesh, India


Affiliations
1 Department of Fisheries Economics and Statistics, College of Fisheries, Central Agricultural University, Lembuhcerra, Tripura West-799210, India
     

   Subscribe/Renew Journal


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.
Subscription Login to verify subscription
User
Notifications
Font Size


  • 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).


Abstract Views: 431

PDF Views: 1




  • Outlook on Fish Seed and Fish Production and their Interrelationship at Uttar Pradesh, India

Abstract Views: 431  |  PDF Views: 1

Authors

A. K. Roy
Department of Fisheries Economics and Statistics, College of Fisheries, Central Agricultural University, Lembuhcerra, Tripura West-799210, India
A. D. Upadhyay
Department of Fisheries Economics and Statistics, College of Fisheries, Central Agricultural University, Lembuhcerra, Tripura West-799210, India
Narendra Kumar Varma
Department of Fisheries Economics and Statistics, College of Fisheries, Central Agricultural University, Lembuhcerra, Tripura West-799210, India

Abstract


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