Mahesh Haroli SP. Ramanathan GA. Dheebakaran V. Geethalakshmi J.S. Kennedy M.R. Duraisamy


Fall armyworm is a recently occurring invasive pest in India, the most important defoliator causing drastic damage to maize production. Hence, the present study aimed to understand the temporal infestation level of Fall armyworms on maize (Zea mays L.) with weather patterns. Field experiments were conducted during Summer (February-May) and Rainy seasons, 2022 (August-December) at Agro Climate Research Centre, Tamil Nadu Agricultural University, Coimbatore. Three different growing environments (GE1, GE2 and GE3) were created by providing staggered sowing. Regression models were developed for per cent leaf damage against three-days lagged (LT3) and seven-day lagged (LT7) weather variables. Results showed that irrespective of growing environments, weather variables showed negative correlation (Tmax: r = -0.57, -0.81*, -0.31; SSH: -0.30, -0.48, -0.39; Tmean: -0.49, -0.23, -0.30; and SR: -0.48, -0.94*, -0.40) during summer season whereas same variables (i.e Tmax =0.62*, 0.41, 0.33; SSH = 0.09, 0.68*, 0.24; Tmean = 0.29, 0.32, 0.44; and SR=0.13, 0 .67*, 0.26 ) showed a positive correlation with PLD. Rainfall exhibits positive relation (0.06, 0.54, 0.53) and negative correlation (-0.64*, -0.10, -0.02) during summer and rainy season, respectively. Among the regression models, LT7 model had higher R2 (0.65 and 0.76) than LT3 (0.57 and 0.68) during summer and rainy seasons, respectively. These models had good regression values of 0.56 and 0.70 during Rainy and Summer, respectively. It was concluded that Tmax (32.9 °C), Tmin (23.7 °C), Tmean (28.3 °C), RH-I (85.6%), RH-II (56.4%), SSH (4.1), SR (274.6 cal cm-2 m-2), afternoon cloud cover (4.8 okta) and weekly total rainfall (10.2 mm) were very conducive for the greater leaf damage.




Correlation, Fall armyworm, Maize, Per cent leaf damage, Regression

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Research Articles

How to Cite

Studies on the relationship of weather on Fall armyworm damage in maize (Zea mays L.) under different growing environments. (2023). Journal of Applied and Natural Science, 15(2), 844-851. https://doi.org/10.31018/jans.v15i2.4635