Assessment of larval population and damage potential of fall armyworm (Spodoptera frugiperda) in maize Maize (Zea mays) ecosystem

VIMAL  KANAUJIYA; AYUSH KUMAR; SHAILENDRA KUMAR  MISHRA; RAKESH PANDEY; MUKESH KUMAR MISHRA

doi:10.56093/ijas.v96i5.166588

Authors

VIMAL KANAUJIYA Sardar Vallabhbhai Patel University of Agriculture & Technology, Modipuram, Meerut , Uttar Pradesh 250 110, India
AYUSH KUMAR Chandra Shekhar Azad University of Agriculture and Technology, Kanpur, Uttar Pradesh 208 002, India
SHAILENDRA KUMAR MISHRA Krishi Vigyan Kendra, Azamgarh, Uttar Pradesh, India
RAKESH PANDEY Banda University of Agriculture and Technology, Banda, Uttar Pradesh 210 001, India
MUKESH KUMAR MISHRA Banda University of Agriculture and Technology, Banda, Uttar Pradesh 210 001, India

https://doi.org/10.56093/ijas.v96i5.166588

Keywords:

Correlation, Larval population, Leaf damage, PCA, Spodoptera frugiperda, Weather variables

Abstract

A study was conducted to assess the larval incidence and leaf damage potential of fall armyworm, Spodoptera frugiperda (J.E. Smith) in maize Maize (Zea mays Linn.) agroecosystem during Kharif 2022 and 2023 at Banda district of Uttar Pradesh. The larval population first appeared in 33^rd standard meteorological week (SMW), with initial counts of 0.10 and 0.28 larva/plantin 2022 and 2023, respectively. The population peaked at 6.92 larvae/plant in 38^th SMW during 2022 and 4.83 larvae/plant in 37^th SMW during 2023. The leaf damage also varied from 0.37 % to 60.16 % in 2022 and from 4.69 % to 58.14 % in 2023. Correlation analysis indicted a strong positive correlation between larval population and leaf damage, both influenced by abiotic weather parameters. In 2022, only rainfall showed a significant positive correlation (r = 0.57) with larval population. In contrast, during 2023, both larval population and leaf damage showed significant positive correlations with minimum temperature (r = 0.55, 0.55), maximum relative humidity (r = 0.61 and 0.59) and minimum relative humidity (r = 0.56 and 0.59), respectively. Principal component analysis suggested that higher rainfall and relative humidity favour greater population growth and leaf damage in 2023 compared to 2022. The results of the regression analysis revealed that weather variables were more influenced in 2022 (R²=58.7)than 2023 (R²=41.5), showed 58.70% variability in FAW larval population, where maximum temperature was most significant constant. Besides other factors may also responsible for a weaker model in 2023.

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Author Biography

AYUSH KUMAR, Chandra Shekhar Azad University of Agriculture and Technology, Kanpur, Uttar Pradesh 208 002, India

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