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Fall Armyworm

Published: 13th Apr, 2020

A pest attack, albeit confined to a district, has added to the COVID-19-related woes of Assam’s farmers.

Context

A pest attack, albeit confined to a district, has added to the COVID-19-related woes of Assam’s farmers.

About

  • The fall armyworm (Spodoptera frugiperda)is a Lepidopteran pest that feeds in large numbers on leaves and stems of more than 80 plant species, causing major damage to maize, rice, sorghum, sugarcane but also other vegetable crops and cotton. 
  • The caterpillar stage of a moth, the Fall Armyworm is not a picky eater though. Besides corn, it likes to feed on the leaves and stems of more than 350 plant species, including rice, sorghum, sugarcane and wheat.
  • An adult female moth can lay up to a thousand eggs in her lifetime. They are also terrific fliers and can travel up to 100 km in a single night.
  • Fall armyworm is native to tropical and subtropical regions of the Americas.

Why north-eastern states are prone to such attacks?

  • In India, FAW found suitable environmental conditions and appropriate host plants.
  • But taking into account environmental conditions and availability of host species the Eastern side of India is more vulnerable to the pest in the near future.
  • The north-eastern states with their “high humidity and moderately high temperatures” are suitable for the spread of FAW.

Pest attacks in India:

  • In India, pest attacks are on rise, yet no significant step has been taken by the central government or state government.
  • The threats farmers face from pest attacks are often localised but underlines the multitude of risks apart from those related to monsoon failure or a crash in crop prices.
  • Major pest attacks in India:

   

Conclusion:

At present, the government needs to conduct studies on pest attack to help to identify risk areas for mapping spatial and temporal distribution of diseases and insect-pests under a changing climate scenario. In the long run, the findings will be helpful in the development of better, more accurate disease- and pest-prediction models.

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