To assess the impact of weather on pest-disease of okra, a field experiment was conducted in summer season 2009 in split plot design with five dates of sowing (D1 -15th February, D2 -1st March, D3 -15th March, D4 -1st April and D5 -15th April) and two spraying levels (S0-control, S1-spraying) at Agronomy Farm of B.A. College of Agriculture, Anand Agricultural University, Anand. The results revealed that the infestation of pests and diseases was higher in delayed sowing as compared to early sowing resulting reduction in yield by 44.4%. Different weather parameters were found to have different effect on various pests and diseases. The correlation study revealed that the Tmax had significant influence on jassid population while relative humidity had significant influence on aphid population. The whitefly, percent fruit damage and YVMV disease were significantly influenced by most of the parameters. However, bright sunshine hours (BSS) and pan evaporation (EP) did not have significant influence on any of the pests and disease of okra. Linear simple regression models, multiple regression models and curvilinear regression models developed with various weather parameters. Among all models, the curvilinear regression model using GDD was found well fitted in order to explaining the maximum extent of variability (83** to 98**%) in the population and intensity of most of the pests and disease except whitefly which was well explained by linear regression developed with VPmean (R2 0.88**).
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