Machine Learning Approaches for Pest and Insect Management in Forest Scenario: An Outlook

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Published: 2023-12-05

DOI: 10.56557/upjoz/2023/v44i233793

Page: 312-316


Senthilkumar N. *

ICFRE-Institute of Forest Genetics and Tree Breeding (ICFRE - IFGTB), Indian Council of Forestry Research and Education Ministry of Environment, Forest and Climate Change (MoEF & CC), Coimbatore-641002, Tamil Nadu, India.

Sumathi R.

ICFRE-Institute of Forest Genetics and Tree Breeding (ICFRE - IFGTB), Indian Council of Forestry Research and Education Ministry of Environment, Forest and Climate Change (MoEF & CC), Coimbatore-641002, Tamil Nadu, India.

*Author to whom correspondence should be addressed.


Abstract

Forests are nature's most efficient complex ecological system and vulnerable resources of valuable products which contribute to the sustainable development of communities. In the current scenario of climate change, forest became susceptible to major issues such as diseases, insects, pests and their unpredictable pest outbreaks. The sustainable management and protection of this natural environment from insect, pest, diseases, human interference and unwanted disturbances is vital and needs new tools to find insight and effective management. Computer vision is good at spotting disorder and efficient pre-requisite tool for insect pest management. Hence, introduction of Artificial Intelligence (AI) and Machine Learning (ML) techniques could be an alternate advanced precision approach to detect and control the herbivorous insect pests at an early stage to avoid huge damage to forest and continuous indiscriminate usage of the chemical pesticides. This is an opportunity which benefits farmers, state forest departments, Forest Development Corporation, forest and private nurseries, wood-based industries, paper and pulp industries etc.    

Keywords: Ecological, vulnerable, sustainable, management, climate change, insect pest management, resources, susceptible, interference, natural, environment, insect


How to Cite

Senthilkumar N., & Sumathi R. (2023). Machine Learning Approaches for Pest and Insect Management in Forest Scenario: An Outlook. UTTAR PRADESH JOURNAL OF ZOOLOGY, 44(23), 312–316. https://doi.org/10.56557/upjoz/2023/v44i233793

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