Effect of Meteorological variables on Larval Population of Legume Pod Borer Maruca vitrata (Fabricius) (Crambidae: Lepidoptera) in Vegetable Cowpea

Author: Mirala Sruthi, Pravasini Behera, S.K. Mukherjee, J. Padhi, P. Tripathy and K.C. Samal

Journal Name:

Download PDF

Abstract

The present study was designed to develop an infestation predictive model based upon meteorological variables, that is, maximum temperature (Tmax), minimum temperature (Tmin), morning relative humidity (RHm), evening relative humidity (RHe), rainfall (RF), number of rainy days (NRD), bright sunshine hours (BSH), wind velocity (WV), and evapotranspiration (EVP), to predict Maruca vitrata larval density per plant. Correlation and regression analyses were performed to determine the relationship of meteorological variables with larval density per plant. A significant correlation was found between larval density per plant WV (r =.793) as well as with EVP (r =.804) and during summer 2021, whereas there was a negative significant correlation between Tmin (r = -.713) and a significant positive correlation between RHm (r = .804) and larval density per plant during kharif, 2021. Environmental variables and larval density per plant data from two consecutive seasons (summer and kharif, 2021) were used to develop a Maruca vitrata infestation predictive model using a stepwise multiple regression analysis. During summer 2021 Tmin, RHe, NRD, EVP; and during kharif 2021, RHm, RHe, RF, NRD, WV, and EVP significantly (p<0.05) contributed to larval density per plant and explained 99% (R2) of the total variance in larval density per plant during both seasons. The forecasting model developed would be useful to predict infestation severity by the legume pod borer before epidemic occurrence and the time of pesticide application. Hence, the model is helpful to reduce the use of pesticides, lessen environmental pollution, and help limit the cost of production for cowpea growers.

Keywords

Meteorological variables, correlation, stepwise multiple regression analysis, Maruca vitrata, larval density per plant and predictive model

Conclusion

The study developed an infestation predictive model based on meteorological variables to predict Maruca vitrata larval density per plant. Correlation and regression analyses were performed to determine the relationship between meteorological variables and larval density. Results showed a significant correlation between wind velocity and larval density during summer 2021, while negative correlations were found during kharif 2021. This study aims to determine the ideal climatic conditions for the rapid spread of the cowpea pod borer. The regression model can help predict infestation severity and pesticide application time, reducing pesticide use, environmental pollution, and limiting production costs for cowpea growers. There was satisfactory agreement between actual and projected values of M. vitrata larvae density per plant, which implies the fitted regression model of M. vitrata infestation and weather association could rationally forecast the field incidence of legume pod borer in vegetable cowpea.

References

-

How to cite this article

Mirala Sruthi, Pravasini Behera, S.K. Mukherjee, J. Padhi, P. Tripathy and K.C. Samal (2023). Effect of Meteorological variables on Larval Population of Legume Pod Borer Maruca vitrata (Fabricius) (Crambidae: Lepidoptera) in Vegetable Cowpea. Biological Forum – An International Journal, 15(4): 982-988.