Development of decision support tools for effective pest management
Keywords:
Pest management, simulation models, pest dynamics, multi-pest EILS, decision makingAbstract
Simulation models have been used for several applications in the area of pest management which helped to increase the efficiency of field research greatly. These have become more relevant in emerging research areas such as climate change impacts on pest dynamics and crop-pest interaction and pest forewarning. The application of geo spatial techniques holds promise for efficient pest surveillance and risk analysis on wide-area basis. The appropriate pest management decisions require a holistic crop loss assessment and estimation of multi-pest EILs. The natural enemy populations need to be considered in decision making to prevent unwarranted pesticide applications.
Downloads
References
Rani, S., Chander, S., Pathak, H. and Kalra, N. 2005b. Infocrop: A dynamic simulation model for the assessment of crop yields, losses due to pests, and environment impact of agro-ecosystem in tropical environments. II. Model performance. Agricultural Systems, 89:47-67.
Aggarwal, P.K., Kalra, N., Chander, S. and Pathak, H. 2004. Inforcrop: A generic simulation model for annual crops in tropical environments, Indian Agricultural Research Institute, New Delhi. p. 132.
Aggarwal, P.K., Kalra, N., Chander, S. and Pathak, H. 2005a. Infocrop: A dynamic simulation model for the assessment of crop yields, losses due to pests, and environmental impact of agro-ecosystems in tropical environments. 1. Model description. Agricultural Systems, 89:1-25.
Ainsworth, E.A. and Long, S.P. 2005. What have we learned from 15 years of free air CO2 enrichment (FACE)? A Meta analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2. New Phytologist, 165: 351-372.
Boote, K.J., Jones, J.W., Mishoe, J.W. and Berger, R.D. 1983. Coupling pests to crop growth simulators to predict yield reductions. Phytopathology, 73: 1581-1587.
Chander, S. 1998. Infestation of root and foliage/earhead aphids
on wheat in relation to predators. Indian Journal of Agricultural Sciences, 68: 754 -755.
Chander, S., Aggarwal, P.K. and Swarooparani, D.N.S. 2004. Agro ecological zonation of leaf folder (Cnaphalocrosis medinalis) in Haryana. Indian Journal of Agricultural Sciences, 74: 455- 457.
Chander, S., Ahuja, L.R., Peairs, F.B., Aggarwal, P.K. and Kalra, N. 2005. Modeling the effect of Russian wheat aphid, Diuraphis noxia (Mordvilko) and weeds in winter wheat as guide to management. Agricultural Systems, 88:494-513.
Chander, S. and Singh, V.S. 2001. Distribution, economic injury level and sequential sampling of leaf folder on rice. Indian Journal of Agricultural Sciences, 71: 768-771.
Chander, S., Singh, V.S. and Kalra, N. 2003. Aphid infestation on barley in relation to climatic variability. Proc. National symposium on Frontier Areas of Entomological Research, 5-7 Nov. Entomology Division, IARI, New Delhi. pp. 37-38.
Coakley, S.M., Scherm, H. and Chakraborty, S. 1999. Climate change and plant disease management. Annual Review of Phytopathology. 37:399-442.
Craighead, F.C. 1921. Protection of mesquite cordwood and posts from borers (No. 1197). US Dept. of Agriculture. Frost, C.J. and Hunter, D. 2004. Insect canopy herbivory and frass deposition affect soil nutrient dynamics and export in oak mesocosms. Ecology, 85: 3335–3347.
Graf, B., Lamb, R., Heong, K.L. and Fabellar, K.L. 1992. A simulation model for the population dynamics of rice leaf folders and their interaction with rice. Journal of Applied Ecology, 29: 558-570.
James, W.C. and Teng, P.S. 1979. The quantification of production constraints associated with plant diseases. In: Applied biology (ed. Coaker, T.H.), Academic Press, New York, pp 201-267.
Kaukoranta, T. 1996. Impact of global warming on potato late blight: risk, yield loss and control. Agricultural and Food Science, 5: 311-27.
Nordh, M.B., Zavaleta, L.R. and Ruesink, W.G. 1988. Estimating multidimensional economic injury levels with simulation models. Agricultural Systems, 26:19-33.
Pinnschmimidt, H.O., Batchelor, W.D. and Teng, P.S. 1994. Simulation of multiple species pest damage on rice. Agricultural Systems, 48: 193-222.
Prasannakumar, N.R. and Chander, S. 2014. Weather-based brown planthopper prediction model at Mandya, Karnataka. Journal of Agrometeorology, 16: 126-129.
Prasannakumar, N.R., Chander, S., Sahoo, R.N. and Gupta, V.K. 2013. Assessment of brown planthopper (Nilaparvata lugens) damage in rice using hyper-spectral remote sensing. International Journal of Pest Management 59: 180-188, DOI: 10.1080/09670874.2013.808780.
Prasannakumar, N.R., Chander, S. and Pal, M. 2012. Assessment of impact of climate change with reference to elevated CO2 on rice brown planthopper, Nilaparvata lugens (Stal.) and crop yield. Current Science, 103: 1201-1205.
Subhash Chander
Rabbinge, R., Rossing, W.A.H. and van der Werf, W. 1994. Systems approaches in pest management: the role of production
Breakdown of resistance to sorghum midge. Stenodiplosis sorghicola. Euphytica, 109:131-140.
ecology. In Proceedings o the Fourth Int. Conf. on Plant Protection in the Tropics, 28-31 March 1994, Kuala Lumpur, Malaysia, (eds A. Rajan and Y. Ibrahim). pp. 25-46.
Rabbinge, R., Ward, S.A. and Van Laar, H.H. 1989. Simulation and Systems Management in Crop Protection. Simulation Monographs, PUDOC, Wageningen, the Netherlands, 420p.
Rajna, S. and Chander, S. 2013. Sequential sampling plan for rice planthoppers with incorporation of predator effect. Journal of Biological Control, 27: 10-17.
Reji, G. and Chander, S. 2008. A degree-day simulation model for the population dynamics of the rice bug, Leptocorisa acuta (Thunb.). Journal of Applied Entomology, 132:646-653.
Reji, G., Chander, S., Singh, V.S. and Satish, D.G. 2003. Simulation of population dynamics of rice gundhi bug. Proc. National symposium on Frontier Areas of Entomological Research, 5-7 Nov. 2003, Entomology Division, IARI, New Delhi. pp. 20-21.
Rouse, D.I. 1988. Use of crop growth models to predict the effects of disease. Annual Review of Phytopathology, 26: 183-201. Sachs, E.S., Benedict, J.H., Stelly, D.M., Taylor, J.F., Altman, D.W., Berberich, S.A. and Davis, S.K. 1998. Expression and segregation of genes encoding Cry1A insecticidal proteins in cotton. Journal of Crop Science, 38: 1-11.
Satish, D., Chander, S. and Reji, G. 2007. Simulation of economic injury levels for leaf folder on rice. Journal of Scientific and Industrial Research, 66: 905-911.
Selvaraj, K. and Chander, S. 2015. Simulation of climatic change impact on crop-pest interactions: a case study of rice pink stem borer Sesamia inferens (Walker). Climatic Change, 131: 259-272 DOI 10.1007/s 10584-015-1385-3.
Sharma, H.C., Mukuru, S.Z., Manyasa, E. and Were, J. 1999.
Singh, P., Chander, S., Husain, M., Pal, V. and Singh, P. 2017. Development of a forewarning model to predict rice leaf folder (Cnaphalocrocis medinalis Guenee) incidence in Punjab, India. Proceedings of the National Academy of Sciences, India Section B: Biological Sciences, 87:201-206. DOI 10.1007/s40011- 015-0595-9.
Stiling, P., Cattell, M., Moon, D.C., Rossi, A., Hungate, B.A., Hymus, G. and Drake, B. 2002. Elevated atmospheric CO2 lowers herbivore abundance, but increases leaf abscission rates. Global Change Biology, 8:658-667.
Sujithra, M. and Chander, S. 2013. Simulation of rice brown planthopper, Nilaparvata lugens population and crop-pest interactions to assess climate change impact. Climatic Change, 121: 331-347, DOI 10.1007/s 10584-013-0878-1.
Sutherst, R.W. 1991. Pest risk analysis and the greenhouse effect. Review of Agricultural Entomology, 79: 1177-1187.
Teng, P.S. and Savary, S. 1992. Implementing systems approach in pest management. Agricultural Systems, 40:237-264. Yadav, D.S. and Chander, S. 2010. Simulation of rice plant hopper damage for developing decision support tools. Crop Protection, 29: 267-276.
Yadav, D.S., Chander, S. and Selvaraj, K. 2010. Agro-ecological zoning of brown plant hopper Nilaparvata lugens incidence on rice Oryza sativa. Journal of Scientific and Industrial Research, 69: 818-822.
Yang, X.B., Dowler, W.M. and Royer, M.H. 1991. Assessing the risk and potential impact of an exotic plant disease. Plant Disease, 75: 976-982.