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Home▶ Journals▶ Indian Journal of Extension Education▶Archive▶Vol. 61 No. 3 (2025)▶Perception of Paddy Farmers on Climate Change in Western…
Indian Journal of Extension Education
Research Article

Perception of Paddy Farmers on Climate Change in Western Odisha: An ANN Model Integration

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Samik Kumar Pradhan — PG Scholar, Department of Agricultural Extension Education, M.S. Swaminathan School of Agriculture, CUTM, Paralakhemundi-761211, Odisha, India
Akkamahadevi Naik — Assistant Professor, Department of Agricultural Extension Education, M.S. Swaminathan School of Agriculture, CUTM, Paralakhemundi-761211, Odisha, India
Ashok Kumar — Associate Professor, Department of Agricultural Extension Education, M.S. Swaminathan School of Agriculture, CUTM, Paralakhemundi-761211, Odisha, India
Soumik Ray — Associate Professor, Department of Agricultural Economics and Statistics, M.S. Swaminathan School of Agriculture, CUTM, Paralakhemundi 761211, Odisha, India
Published 30 Jun 2025 Vol. 61 No. 3 (2025), pp. 1-6 ● Open access
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Abstract

The study, conducted during 2024-25, to examine Paddy farmers’ perception of climate change in Balangir and Kalahandi districts of Western Odisha, an Artificial Neural Network (ANN) model was integrated to analyse the relationship between socio-economic factors of Paddy farmers and their perception of climate change. A total of 180 farmers were interviewed with a structured interview schedule to evaluate their perceptions of three main components, viz., exposure, sensitivity, and adaptive competence. The majority of farmers strongly agreed that climate variability, including erratic rainfall, rising temperatures, and extreme weather, adversely impacts agricultural production and causes a serious threat to food security, and changes in climatic conditions lead to shifts in cropping patterns. An ANN model identified the best hidden nodes, i.e., (3,3) for both the exposure and sensitivity, and (5,3) for the adaptive competence component, achieving a minimum Mean Square Error of 7.726 for the best neural network architecture. 

 

KeywordsArtificial neural networkClimate changeFarmers perceptionSocio-economic factorsWestern Odisha

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