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Title: Factors influencing adoption of farm level tree planting in social forestry in Orissa, India
Author: Mahapatra, Ajay Kumar
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Date of Award: 1997
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This study of the adoption of farm level forestry in one eastern Indian state, Orissa, focused on the above issue. 428 farm owners, both tree planters and non planters from 24 villages in two districts were interviewed with a questionnaire and household level data on socio-economic resources, tree products demand and their attitude towards forestry were collected. Descriptive statistical analysis was employed to identify factors influencing the decision of farmers to adopt/reject tree growing on farm. The social status, progressiveness of the households, and participation in village organisations were the important variables on social aspects, whereas land, credit, agricultural production and livestock ownership on the economic front were seen to be affecting householders decisions. Household supply of labour, land tenancy and family structure did not have a relationship with farm decision to adopt. Result of Chi-square and Spearman test indicated the land ownership to be positively correlated with most social and economic variables, but having little effect on demand for biofuels. The result of the cross tabulation between participation and householders interaction with extension agents, mass media and awareness about social forestry established that dissemination across socio-economic groups was influenced by communication factors rather than household demands of firewood or timber. There was no distinct difference in the attitude of tree planters and non-planters towards the forestry problems. The stepwise discriminant analysis resulted in prediction models of agroforestry adoption. The social and economic models based on selected variables were able to classify about 66% and 64% of the cases, whereas the communication factors successfully distinguished 74% of planters and non planters. The integrated model resulted in a prediction rate of 90%. The parameters estimated from the discrimination function showed the relative impact of the determinants in identifying adopter and non adopter. The variance in the production of the major crop, paddy, was higher for the tree planter which might have motivated them to grow trees to reduce uncertainty in the farm production.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Forestry & agroforestry & sustainable forestry Forests and forestry Geography