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Role of Modelling in Plant Disease Management
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Indian’s economy is agricultural based. Agriculture provides maximum employment in the country. Unfortunately, crop production is heavily affected by the pests and diseases. In addition to refinement in the existing management practices, there is a need for simulation models to assess the potential of emerging pathogens for a given crop production system and also shift in pathogen populations/fitness that may demand modifications in current production systems. Forecasting models which allows investigating multiple scenarios and interactions simultaneously has become most important for disease prediction, impact assessment and application of disease management measures. Many weather driven epidemiological models have been developed and used to predict plant disease epidemics under variable climate. Most forecasting models are meant for tactical and strategic decisions. Similarly, the Mill’s Table also had been modified for Apple scab epidemic under H.P conditions. Moreover, remote sensing and image analysis have been used in plant diseases epidemiology to forecast the plant diseases. These epidemiological tools have been designed to help the farmers in enhancing the efficiency and adequacy of disease management. A complete knowledge of these epidemiological tools provide quick, fast and accurate prediction of disease and helps in timely disease control.
Keywords
Epidemic, Forecasting, Modelling, Simulation.
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- Agrios, G.N. (2005). Plant pathology. 5th Ed., Elsevier Academic Press, London, United Kingdom.
- Bhattacharyya, S.K., Phadatare, S.G., Khanna, R.N., Srivastava, D.S. and Prasad, B. (1983). Efficacy of some fungicides in controlling late blight of potato in India. Indian J. Agric. Sci., 53: 153-157.
- Campbell, C.L. and Madden, L.V. (1990). Introduction to plant disease epidemiology. John Wiley & Sons, New York, NY, USA.
- Grunwald, N.J., Cadena Hinojosa, M.A., Rubio Covarrubias, O.A., Rivera Peña, A., Niederhauser, J.A. and Fry, W.E. (2002). Potato cultivars from the Mexican national program: sources and durability of resistance against late blight. Phytopathology, 92 : 688-693.
- Jeger, M.J. and Viljanen-Rollinson, S.L.H. (2001). The use of the area under disease-progress curve (AUDPC) to assess quantitative disease resistance in crop cultivars. Theor. Appl. Genet., 102: 32-40.
- Jeger, M.J. (2004). Analysis of disease progress as a basis for evaluating disease management practices. Annual Rev. Phytopathol., 42: 61-82.
- Kranz, J., Mogk, M. and Stumpf, A. (1973). EPIVEN: ein Simulator fur Apfelschorf. Z Pflanzenkr, 80: 181-187.
- Krause, R.A., Messie, L.B. and Hyre, R.A. (1975). BLIGHTCAST: Computerized forecast of potato late blight. Plant Disease Reporter, 59: 95.
- Madden, L.V. (2006). Botanical epidemiology: Some key advances and its continuing role in disease management. European J. Plant Pathol., 115: 3-23.
- Nutter, F.W. Jr (1997). Quantifying the temporal dynamics of plant virus epidemics: Areview. Crop Prot.,16: 603–618. doi: 10.1016/S0261-2194 (97) 00055-0.
- Nutter, F.W. Jr. and Parker, S.K. (1997). Fitting disease progress curves EPIMODEL. In: Exercises in plant disease epidemiology. Francl, LJ and Neher DA (eds). APS Press, St. Paul, MN, USA, pp. 24-28.
- Nutter, F.W. Jr. (2007). The role of plant disease epidemiology in developing successful integrated disease management programmes. pp. 45-79. In: General concepts in integrated pest and disease management. A. Ciancio and K.G. Mukerji, Ed. Springer-Verlag, Dordrecht, The Netherlands.
- Rossi, V., Racca, P., Giosue, S., Pancaldi, D. and Alberti, I. (1997). Simulation model for the development of brown rust epidemics in winter wheat. European J. Plant Pathol., 103: 453–465.
- Runno, E. and Koppel, M. (2002). Use of potato late blight control system Negfry in Estonian conditions. Research for rural development 2002. International Scientific Conference Proceedings, Jelgava.pp. 61-64.
- Segarra, J., Jeger, M. andVan den Bosch, F. (2001). Epidemic patterns and dynamics of plant disease. Phytopathology, 91: 1001–1010.
- Singh, B.P., Islam Ahmed, Sharma, V.C. and Shekhawat, G.S. (2000). JHULSACAST: A computerized forecast of potato late blight in Western Uttar Pradesh. J. Indian Potato Assoc., 27: 25-34.
- Thakur, V.S., Verma, N. and Verma, S. (2005). Effect of meteorological factors on the development of lesion density in apple scab epidemic in Himachal Pradesh.Hort. J., 18(1): 4-9.
- Thind, T.S., Bala, Anju, Mukerjee, J., Jolly, R.K., Kumar, Pradeep, Singh, Amarjeet and Sekhon, P.S.(2013). Development of a web-based decision support system for late blight of potato. Plant Disease Res.,28 (1): 66-70.
- Van der Plank, J. E. (1963). Plant diseases. Epidemics and Control. Academic Press, New York, U.S.A.
- Van Maanen, A. and Xu, X.M. (2003). Modelling plant disease epidemics. European J. Plant Pathol., 109: 669-682.
- Xu, X. (2006). Modelling and interpreting disease progress in time. In:The epidemiology of plant disease. Cooke BM, Gareth Jones D and Kaye B (eds) Springer, Dordrecht, The Netherlands, pp. 215-238.
- Zadoks, J. C. and Schein, R. D. (1979). Epidemiology and plant disease management. Oxford University Press, New York, U.S.A.
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