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Research Article Open access CC BY 4.0

Identifying and Understanding Factors Influencing the Knowledge Level of Farmers in Watershed Development Programme Using Principal Components Analysis

Samir Ranjan Dash, Sidhartha Dev Mukhopadhyay, Prasanna Jit Mishra, Susanta Kumar Swain

Asian Journal of Agricultural Extension, Economics & Sociology · pp. 893–908 · Published 22 Aug 2022

10.9734/ajaees/2022/v40i1031157

Abstract

Watershed Development Programmme is based on bottom-up planning and a participatory approach. It will be easier to implement the programme successfully and get the desired results if we have a good comprehension of the guidelines. On many different developmental programmes implementation its components including institutional arrangement, community organisation, objectives, programme creation and implementation, funding pattern, monitoring and evaluation, significant gaps were observed. These socio -economic factors provide essential information to support efforts and policies aimed at improving adoption by recognizing heterogeneities in the targeted populations. Principal component analysis (PCA) is a technique for reducing the dimensionality of datasets, increasing interpretability but at the same time minimizing information loss. The present study was conducted with a sample size of 192 progressive farmers and watershed user groups in Nuapada and Kalahandi district of Odisha state, aiming to identify the major socio economic factors governing farmers’ knowledge and adoption level of different watershed activities. Three different principal components (PCs) could finally be extracted out of twelve relatively important variables governing knowledge and participation level of farmers in different watershed activities. These three factors were resource richness, which was associated with higher farm revenue, cosmopoliteness, which was associated with extended contact and motivation, and family type, which was associated with manpower and farming as a primary employment. Firstly, data reduction was conducted through principal component analysis to identify three important components accounting for 58.66% of the total variability in the data. It is evident from the results that socioeconomic factors such as Land holding, Annual Income, Type of house, Cosmo politeness and extension contact, Education, more use communication materials, Social participation and age of the farmer, can be associated with higher knowledge and adoption of watershed activities and practices. From the findings of the study, it was concluded that three principal components like ‘resource richness’, ‘education and extension contact’ and ‘farm family occupation” were found to have exerted significantly high influence and contributed 23.44%, 20.12% and 15.1% variance respectively in determining the extent of farmers’ knowledge level about watershed activities . These factors can be used as essential input to predict models or as benchmarks for developing scales or indices for measuring farmers’ progressiveness and knowledge and adoption of watershed activities.

Watershed development programme socio economic factors multivariate analysis dimension reduction technique principal components analysis

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Showing 1 of 2 known citations — external sources report more than can currently be individually listed.

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