Influence of weather elements on grapes growth, yield and disease incidence using Epidemiological modeling
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Abstract
Mathematical models play a vital role in crop agriculture to understand, predict and forecast the yield and disease incidence. This paper explores the utilization of mathematical model in grapes based on non-steady state equations possessing a nonlinear term. Theoretically, evaluated non-steady state concentration of leaf surface area for optimal strategy for grapes system presented. The analytical results of this study found to be matching with numerical results using MATLAB pdex4 function. Further, the proposed model validated with the field level data collected from Theni district, Tamil Nadu. Disease incidence and yield of grapes were highly influenced by weather variables. In addition, important aspects like disease intensity, infection rate and number of diseased leaves for secondary and primary infection studied in detail.
References
A report of the expert consultation on viticulture in Asia and the Pacific May 2000, Bangkok, Thailand, RAP publication, 2000.
R. Mallik, S.K. Chaudhury, and S. Sarkar (Eds.). (2017). Indian Agriculture. New Delhi: S.K. Book Agency.
R.W. Emmett et al., Grape diseases and vineyard protection, In:Viticulture Practices, B.G. Coombe & P.R. Dry (eds), Winetitles, Adelaide, South Australia. 2 (1992) 232–278.
P.A. Magarey et al., A computer based simulator for rational grapevine downy mildew (Plasmopara viticola) on grape leaves, Phytopathology. 78 (1994) 1316–1321.
F. Miglietta, B. Gozziniand, S. Orlandini, Simulation of leaf appearance in grapevine. Viticultural and Enological Science. 47 (1992) 41–5.
H. Schultz, An empirical model for the simulation of leaf appearance and leaf area development of primary shoots of several grapevine (Vitis vinifera L.) canopy-systems, Scientia Horticulturae. 52 (1992) 179–200.
S. Nagarajan, and K. Muralidaharan, Disease dynamics and analytical epidemiology, Dynamics of plant disease. Allied publishers Limited. New Delhi, (1995) 120–134.
A. Eswari, Weather based yield prediction and PDI model for grapesproduction quality forecast in Tamil Nadu using mathematical modelling, International Journal of Current Microbiology and Applied Sciences, 10(2021).
S. Liang, and D.J. Jeffrey, Comparison of Homotopy analysis method and Homotopy perturbation method through an evolution equation, Department of Mathematics, University of Western Ontario, London, Ontario, Canada, N6A 5B7 (2009) 1–12.
J. Biazar, K. Hosseini and P. Gholamin, Homotopy perturbation method for solving KdV and Sawada-Kotera equations. Journal of Applied Mathematics, 6(21) (2009) 23–29.
J. Biazar, H. Ghazvini, . Exact solution for non-linear Schrodinger Eeuations by hes Homotopy Perturbation method. Physics Letters A, 366 (2007)79–84.
N.H. Sweilam, and M. M. Khader, Exact solution of some coupled non-linear partial differential equation using the Homotopy perturbation method, Computer and mathematics with application, 58 (2009) 2134–2141.
Z. Odibat and S. Momani, A reliable treatment of Homotopy perturbation method for Klein-Gordon equations, Physics Letters A, 356 (2007) 351–357.
A.A. Hemeda, Homotopy perturbation method for solving system of non-linear coupled equation, Applied Mathematical Sciences, 6(96) (2012) 4787–4800.
S. Liao, Beyond Perturbation - Introduction to Homotopy analysis method, ISBN 1-58488-407-X.
J.H. He, A coupling method of Homotopy technique and perturbation technique for non-linear problems, International Journal of Non-Linear Mechanics, 35 (2000) 37–43.
J.H. He, Homotopy perturbation method, a new non-linear analytical technique, Applied Mathematics and Computation, 135 (2003) 73–79.
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