Abstract
Weather based prediction models for leaf rust were developed using disease severity and weather data recorded at four locations viz. Ludhiana, Kanpur, Faizabad and Sabour of the All India Wheat and Barley Improvement Project. Weeks 7–9 of the crop growing season at Ludhiana, Faizabad and Sabour and weeks 10–12 at Kanpur were identified as critical periods for relating weather variables to disease. Highly significant correlation coefficients were found between disease severity and a greater number of weather variables in these critical 3-week periods than at other times. The correlation coefficients were greatest for the Humid Thermal Ratio (HTR), Maximum Temperature (MXT) and Special Humid Thermal Ratio (SHTR), and these three weather variables were selected as predictor variables. Linear regressions with these predictor variables (individually) during the critical periods, and a multiple regression with MXT and relative humidity (RH), serve as four disease prediction models, with sufficient lead-time to take control measures. Validation of these prediction models with independent disease severity data showed that the regression equation with MXT (Model-1) was the best among the prediction models, with four out of six simulations matching observed disease severity classes and also having lowest residual sum of squares (SSE) value of 2727. Models 4 (multiple regression), 2 (HTR) and 3 (SHTR) with SSE values of 2881, 3092 and 3732, respectively are in order of decreasing accuracy of prediction. The model using MXT can be used to predict the disease severity in the Indo-Gangetic Plains and provide the basis for efficient disease control.
Similar content being viewed by others
Abbreviations
- MXT:
-
Maximum temperature
- HTR:
-
Humid thermal ratio
- SHTR:
-
Special humid thermal ratio
- RH:
-
Relative humidity
- SSE:
-
Residual sum of squares
- IGP:
-
Indo gangetic plains
- HTI:
-
Humid thermal index
- MNT:
-
Minimum temperature
- AVRH:
-
Average relative humidity
References
Allen, T. W., & Jones, D. C. (2009). Application of the humid thermal index for relating bunted kernel incidence to soil borne tilletia indica teliospores in an Arizona durum wheat field. Plant Disease, 93(7), 713–719.
Anonymous. (2005). Managing stripe rust and leaf rust of wheat, farm note no. 43. Western Australia: Department of Agriculture.
Audsley, E., Milne, A., & Audsley, N. (2005). A foliar disease model for use in wheat disease management decision support systems. Annals of Applied Biology, 147, 161–172.
Baker, R. H. A., Sansford, C. E., Gioli, B., Migletta, F., Porter, J. R., & Ewert, F. (2005). Combining a disease model with crop phenology model to assess and map pest risk: Karnal bunt disease (Tilletia indica) of wheat in Europe. In: Plant Protection and Plant Health in Europe: Introduction and spread of invasive species, Symposium Proceedings No. 81(pp.89-94). British crop protection council, Alton Hampshire, UK.
Basandrai, A. K., Sharma, B. K., & Basandrai, D. (2014). Efficacy of triazole fungicides for the integrated management of yellow rust, leaf rust and powdery mildew of wheat. Plant Disease Research, 28(2), 135–139.
Burleigh, J. R., Eversmeyer, M. G., & Roelfs, A. P. (1972). Development of linear equations for predicting wheat leaf rust. Phytopathology, 62, 947–953.
Byerlee, D., & Moya, P. (1993). Impacts of international wheat breeding research in the developing world, 1966–90. Mexico: CIMMYT.
Coakley, S. M., & Line, R. F. (1982). Prediction of stripe rust epidemics on winter wheat using statistical models. Phytopathology, 72, 1006.
Coakley, S. M., McDaniel, L. R., & Shaner, G. (1985). Model for predicting severity of Septoria tritici blotch on winter wheat. Phytopathology, 75, 1245–1251.
Coakley, S. M., Line, R. F., & McDaniel, L. R. (1988a). Predicting stripe rust severity on winter wheat using an improved method for analyzing meteorological and rust data. Phytopathology, 78, 543–550.
Coakley, S. M., McDaniel, L. R., & Line, R. F. (1988b). Quantifying how climatic factors affect variation in plant disease severity: a general method using a new way to analyze meteorological data. Climatic Change, 12, 57–75.
Dirks, V. A., & Roming, R. W. (1970). Linear models applied to variation in numbers of cereal rust urediospores. Phytopathology, 60, 246–251.
Eversmeyer, M. G., & Burleigh, J. R. (1970). A method of predicting epidemic development of wheat leaf rust. Phytopathology, 60, 805–811.
Eversmeyer, M. G., & Kramer, C. L. (1995). Survival of Puccinia recondita and P. Graminis urediniospores exposed to temperatures from subfreezing to 35°C. Phytopathology, 85, 161–164.
Eversmeyer, M. G., & Kramer, C. L. (1998). Models of early spring survival of wheat leaf rust in the central Great Plains. Plant Disease, 82, 987–991.
Gardner, B. (2007). Linear regression Analysis-3 common causes of multi-colinearity and what to do about them, Club par excellence/student life and news.
Hansen, J. G., Secher, B. J. M., Jorgensen, L. N., & Welling, B. (1994). Thresholds of control of Septoria spp.in winter wheat based on precipitation and growth stage. Plant Pathology, 43, 183–189.
Honrao, B. K., Misra, S. C., Nayar, S. K., Dixit, R. N., Chavan, A. M., & Rao, V. S. (2005). New sources of leaf rust resistance in Indian local durum wheat. Wheat Information Service, 99, 63–64.
Huber, L., & Gillespie, T. J. (1992). Modeling leaf wetness in relation to plant disease epidemiology. Annual Review of Phytopathology, 30, 553–577.
Jhorar, O. P., Mavi, H. S., Sharma, I., Mahi, G. S., Mathauda, S. S., & Singh, G. (1992). A biometeorological model for forecasting karnal bunt disease of wheat. Plant Disease Research, 7, 204–209.
Jhorar, O. P., Mathauda, S. S., Singh, G., Butler, D. R., & Mavi, H. S. (1997). Relationships between climatic variables and Ascochyta blight of chickpea in Punjab (India). Agricultural and Forest Meteorology, 87, 171–177.
Joshi, L. M., Srivastava, K. D., & Singh, D. V. (1985). Monitoring of wheat rusts in the Indian sub-continent. Proceedings of Indian Academy of Sciences (Plant Science), 94, 387–406.
Joshi, L. M., Singh, D. V., & Srivastava, K. D. (1986). Wheat and wheat disease in India. In L. M. Joshi, D. V. Singh, & K. D. Srivastava (Eds.), Problems and progress of wheat pathology in South Asia (pp. 1–19). New Delhi: Malhotra publishing House.
Kaundal, R., Kapoor, A. S., & Raghava, G. P. S. (2006). Machine learning techniques in disease forecasting: a case study on rice blast prediction. BMC Bioinformatics, 7, 485.
Khan, M. A., & Trevathan, L. E. (1999). Polynomial regression models to characterize environmental conditions conducive for leaf rust development on winter wheat in Mississippi. Pakistan Journal of Biological Sciences, 2, 113–120.
Lovell, D. J., Powers, S. J., Welham, S. J., & Parker, S. R. (2004). A perspective on the measurement of time in plant disease epidemiology. Plant Pathology, 53, 705–712.
Magarey, R., & Borchert, D. (2003). Pest Assessment: Puccinia tritici, (wheat leaf rust). http://www.nappfast.org/casestudies_files/wheat_rust%. pdf.
Marsalis, M. A., & Goldberg, N. P. (2006). Leaf, Stem and Stripe Rust Diseases of Wheat, New Mexico State University, College of Agriculture and Home Economics, Guide A-415 (www.cahe.nmsu.edu).
Mavi, H. S., Jhorar, O. P., Sharma, I., Singh, G., Mahi, G. S., Mathauda, S. S., & Ahuja, S. S. (1992). Forecasting karnal bunt disease of wheat-a meteorological method. Cereal Research Communications, 20, 67–74.
Mehta, K. C. (1940). Further studies on cereal rusts in India. Part I (Vol. 14, p. 224). India: Scientific Monograph, Imperial Council of Agricultural Research.
Moschini, R. C., & Perez, B. A. (1999). Predicting wheat leaf rust severity using planting date, genetic resistance, and weather variables. Plant Disease, 83, 381–384.
Park, R. F. (1990). The role of temperature and rainfall in the epidemiology of puccina striformis f.sp.Tritici in the summer rainfall area of eastern Australia. Plant Pathology, 39, 416–423.
Patidar (2006). Management of leaf rust of wheat caused by Puccinia recondite f.sp. tritici Rob. Ex. Desm. M.Sc (Ag) Thesis, University of Agricultural Sciences, Dharwad, India, P. 98.
Peterson, R. E., Campbell, A. B., & Hannah, A. E. (1948). A diagrammatic scale for estimating rust intensity of leaves and stems of cereals. Canadian Journal of Research, 26, 496–500.
Pietravalle, S., Shaw, M. W., Parker, S. R., & Bosch, F. V. D. (2003). Modeling relationships between weather and septoria tritici epidemics in winter wheat: A critical approach. Phytopathology, 93, 1329–1339.
Rader, T., Racca, P., Jorg, E., & Hau, B. (2007). PUCREC/PUCTRI-a decision support system for the control of leaf rust of winter wheat and winter rye. EPPO Bulletin, 37(2), 378–382.
Roelfs, A. P., Singh, R. P., & Saari, E. E. (1992). Rust diseases of wheat: concepts and methods of disease management. Mexico City: CIMMYT.
Rossi, V., Racca, P., Giosue, S., Pancaldi, D., & Alberti, I. (1997). A simulation model for the development of brown rust epidemics in winter wheat. European Journal of Plant Pathology, 103, 453–465.
Singh, R. P., William, H. M., Huerta-Espino, J., & Rosewarne, G. (2004). Wheat rust in Asia: Meeting the challenges with old and new technologies. Proceedings of the 4th International Crop Science Congress, Brisbane, Australia, 26th Sep–1st Oct 2004.
Srivastava, K. D. (1981). Studies on the spread of Puccinia recondita Robs. Ex. Desm and its Epidemiology. Agra, India: Agra University, Ph. D Thesis.
Srivastava, K. D., Joshi, L. M., & Nagarajan, S. (1985). A linear equation for predicting severity of leaf rust of wheat. Indian Phytopathology, 38(1), 116–120.
Steinberg, D. (2000). Modeling the basis for rational disease management. Crop Protection, 19, 747–752.
Subba Rao, K. V., Berggren, G. T., & Snow, J. P. (1990). Characterization of wheat leaf rust epidemics in Louisiana. Phytopathology, 80, 402–410.
Suryanarayana, D., Goel, L. B., & Sinha, V. C. (1973). Epidemiological studies on wheat rusts in Simla hills. INSA Bulletin, 46, 460–463.
te Beest, D. E., Paveley, N. D., Shaw, M. W., & Bosch, F. V. D. (2008). Disease -weather relationships for powdery mildew and yellow rust on winter wheat. Phytopathology, 98(5), 609–617.
te Beest, D. E., Shaw, M. W., Pietravalle, S., & Bosch, F. (2009). A predictive model for early warning of septoria leaf blotch on winter wheat. European Journal of Plant Pathology, 124(3), 413–425.
Tottman, D. R., & Makepeace, R. J. (1979). An explanation of the decimal code for the growth stages of cereals, with illustrations. Annals of Applied Biology, 93, 221–234.
Vallavieille-Pope, C., Huber, L., Leconte, M., & Goyeau, H. (1995). Comparative effects of temperature and interrupted wet periods on germination, penetration and infection of Puccinia recondita f.sp.Tritici and P.Striiformis on wheat seedlings. Phytopathology, 85, 409–415.
Workneh, F., Allen, T. W., Nash, G. H., Narasimhan, B., Srinivasan, R., & Rush, C. M. (2008). Rainfall and temperature distinguish between karnal bunt positive and negative years in wheat fields in Texas. Phytopathology, 98, 95–100.
Acknowledgments
The author thanks Indian Council of Agricultural Research (ICAR) for funding a research project “Developing decision support system for major crops through long-term agroclimatic data analysis”, the results of which formed this article. The data received from All India Coordinated Research Project on Wheat and Barley, Karnal is duly acknowledged. The author profusely thanks Dr. David R. Butler, Ilhéus, Brazil for making necessary language corrections in the manuscript.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Vijaya Kumar, P. Development of weather-based prediction models for leaf rust in wheat in the Indo-Gangetic plains of India. Eur J Plant Pathol 140, 429–440 (2014). https://doi.org/10.1007/s10658-014-0478-6
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10658-014-0478-6