Effect of meteorological factors on progression of Alternaria leaf blight of mustard and comparison of Logistic and Gompertz growth models in predicting disease severity - and SRIKANTA DAS*, SUNITA MAHAPATRA (Indian Phytopathology, 2014)
The step down multiple regression analysis (MRA) was carried out to determine the meteorological parameters influencing in variation of disease severity of Alternaria leaf blight (Alternaria brassicae and A. brassicicola) of mustard. Disease severity estimates (Y) was consideredÂ asÂ dependent variable, where as other weather parameters like maximum (Tmax) and minimum temperature (Tmin); maximum (RHmax) and minimum relative humidity (RHmin); total rainfall (RT); wind velocity evening (WVevening) and morning (WVmorning); vapour pressure noon (VPnoon) and morning(VP morning); and bright sunshine hour (BSH) were used as independent variables. The weather variables were found to influence the disease severity differently when crops were shown at different dates of five sowing time for the two consecutive years, 2007-08 to 2008-09. The Gompertz equation was best linearized with the disease progress data followed by the logistic and the untransformed data sets. The linear prediction equations are (1) Y= 3.203-0.356 ( Tmin) + 0.015 (RHmin) for 20th October sowing; (2) Y = - 1.929 + 1.634 (WVmorning) + 0.067 (RT) for 5th November sowing; (3) Y = - 121.91 + 1.57(Tmin) + 1.083(RHmax) + 0.29(RHmin) - 2.27(VPnoon) - 0.61(VPmorning) - 17.17(WVevening) + 17.83(WVmorning) + 1.65(BSH) + 0.113(RT) for 20th November sowing; (4) Y = - 5.131 + 0.25 (VPnoon) + 0.256 (BSH) + 0.057 (RT) for 5th December sowing; (5) Y = - 3.19 + 0.235(Tmin) for 20th December sowing. Gompertz transformation is best for linerizing and prediction of disease severity in all dates of sowing and in early sowing Tmin, RHmin and WVmorning influenced the disease progression.