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Saxena, A. K.
- Economic Analysis of Post-Harvest Loss and Marketing Efficiency in Guava (cv. Allahabad safeda) in Karnataka
Abstract Views :192 |
PDF Views:106
Authors
T. M. Gajanana
1,
D. Sreenivasa Murthy
1,
A. K. Saxena
2,
D. V. Sudhakar Rao
3,
M. Sudha
1,
V. Dakshinamoorthy
1
Affiliations
1 Section of Economics and Statistics, ICAR-Indian Institute of Horticultural Research, Hesaraghatta Lake Post, Bengaluru – 560 089, IN
2 Division of Plant Pathology, ICAR-Indian Institute of Horticultural Research, Hesaraghatta Lake Post, Bengaluru – 560 089, Karnataka, IN
3 Division of Post Harvest Technology, ICAR-Indian Institute of Horticultural Research, Hesaraghatta Lake Post, Bengaluru – 560 089, Karnataka, IN
1 Section of Economics and Statistics, ICAR-Indian Institute of Horticultural Research, Hesaraghatta Lake Post, Bengaluru – 560 089, IN
2 Division of Plant Pathology, ICAR-Indian Institute of Horticultural Research, Hesaraghatta Lake Post, Bengaluru – 560 089, Karnataka, IN
3 Division of Post Harvest Technology, ICAR-Indian Institute of Horticultural Research, Hesaraghatta Lake Post, Bengaluru – 560 089, Karnataka, IN
Source
Journal of Horticultural Sciences, Vol 10, No 1 (2015), Pagination: 70-73Abstract
Post-harvest losses (PHL) in guava (cv. Allahabad safeda) were estimated at the field and retail levels in Karnataka, and impact of this loss on marketing efficiency was studied. Results indicated that the total PHL was 13.29% consisting of field-level loss (9.17%) and retail level loss (4.12%). The producer's share was 51.52% and PHL, when included as an item of cost, reduced the share to 45.80%. PHL also reduced marketing efficiency index from 1.06 to 0.88, thereby indicating the importance of PHL and scope for minimizing it to improve the efficiency of the marketing system in guava.Keywords
Guava, Post-Harvest Losses, Allahabad Safeda, Economic Analysis, Marketing Efficiency.Full Text
References
- Acharya, S.S. and Agarwal, N.L. 2001. Agricultural marketing in India, Third Edition, Oxford & IBH Publishing Company, New Delhi
- Gajanana, T.M., Sreenivasa Murthy, D. and Sudha, M. 2011. Post harvest losses in fruits and vegetables in South India – A review of concepts and quantification of losses. Indian Food Packer, 65:178-187
- Jagtap, K.B. and Katrodia, J.S. 1998. Post harvest losses in packaging and transportation of sapota, Indian J. Hort., 55:48-51
- Sreenivasa Murthy, D., Gajanana T.M. and Sudha, M. 2004. Post harvest loss and its impact on marketing cost, margin and efficiency: a study on grapes in Karnataka, Indian J. Agril. Econ., 59:772-786
- Srinivas, R.N., Venkatesha Reddy, T., Ravi, P.C., Lalith Achoth and Chinnappa Reddy, B.V. 1997. Post Harvest Losses Assessment in Totapuri and Alphonso Mangoes. J of Food Sci. and Tech., XXXIV:70-71
- Wanjari,V., Ladaniya, M.S. and Gajanana, T.M. 2002. Marketing and Post harvest losses of acid lime in Andhra Pradesh, Indian J. Agril. Marketing, 16:32-39
- A Statistical Model for Ascertaining the Influence and Reliability of Weather Parameters on Incidence of Blossom Blight in Mango (Mangifera indica L.)
Abstract Views :315 |
PDF Views:156
Authors
Affiliations
1 Section of Economics and Statistics, Indian Institute of Horticultural Research, Hessaraghatta Lake Post, Bangalore-560 089, IN
2 Division of Plant Pathology, Indian Institute of Horticultural Research, Hessaraghatta Lake Post, Bangalore-560 089, IN
1 Section of Economics and Statistics, Indian Institute of Horticultural Research, Hessaraghatta Lake Post, Bangalore-560 089, IN
2 Division of Plant Pathology, Indian Institute of Horticultural Research, Hessaraghatta Lake Post, Bangalore-560 089, IN
Source
Journal of Horticultural Sciences, Vol 1, No 1 (2006), Pagination: 64-67Abstract
A statistical model was developed to study the influence and reliability of weatlier parameters on incidence of blossom blight in Mango (Mangifera indica) and subsequently to predict their incidence. Results showed that preceding week's weather variables viz., maximum and minimum temperature, evaporation, rainfall, morning and evening relative humidity and wind speed were found to collectively predict blossom blight incidence to the extent of 94.3 per cent. Further, as a measure of goodness-of-fit, the coefficient of determination (R2) and mean squared error were used to evaluate the empirical model developed by using above variables. Validation test showed that the model developed using relative humidity at 07.30 h (X3), evaporation (X5) and wind speed (X6) (Y = 883.4 - 8.065 X3-11.506 X5 -33.619 X6) could predict the incidence to the extent of 75.7%. This model is useful in determining the role of climatic factors in disease appearance and progression and devising suitable management strategy.Keywords
Blossom Blight, Mango, Coefficient of Determination, Climatic Factors, Model.Full Text