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Adoption of Water Conservation Technologies among Small Scale Farmers in Lwengo District – Uganda

Adoption of Water Conservation Technologies among Small Scale Farmers in Lwengo District – Uganda

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dc.contributor.author Nabalegwa Muhamud Wambede
dc.contributor.author Joyfred Asaba
dc.contributor.author Othieno Esther Ebifa
dc.contributor.author Nabatta Claire
dc.date.accessioned 2021-01-10T11:55:55Z
dc.date.available 2021-01-10T11:55:55Z
dc.date.issued 2019
dc.identifier.uri https://combine.alvar.ug/handle/1/49293
dc.description.abstract This study identified and characterised the dominant water conservation technologies (WCT) employed by small scale farmers in Malongo and Kyazanga sub-counties in Lwengo district. It employed a cross sectional household survey design, using systematic sampling to obtain 380 household samples. A quantitative analysis, Multiple Correspondence Analysis (MCA) and Logit regression model were used to analyse these data to identify and characterise the dominant WCT and establish the most significant factor affecting the adoption of the technologies. Results indicated that mulching was the most dominant WCT employed, followed by Valley dams/reservoirs, terracing, tied ridges, deep tillage and infiltration pits. The Logit model indicated that out of seven factors, five had a significant positive influence namely: access to credit (1.3); farm slope location (0.7); farm size (0.4); access to agricultural inputs and investment subsidies (0.4); and level of income (0.2). One factor had a significant negative influence (engagement in other economic activities/off-farm employment activities) and only one was found to be insignificant (access to market). It is recommended that the significant water conservation techniques be upscaled, and that emphasis also be placed on the most significant factors in order to strengthen the adoption of water conservation in the area.
dc.title Adoption of Water Conservation Technologies among Small Scale Farmers in Lwengo District – Uganda
dc.identifier.mag 3006291376
dc.identifier.lens 110-310-938-933-576
dc.identifier.volume 1
dc.identifier.issue 1
dc.identifier.spage 84
dc.identifier.epage 96
dc.subject.lens-fields Water conservation
dc.subject.lens-fields Agriculture
dc.subject.lens-fields Logistic regression
dc.subject.lens-fields Tillage
dc.subject.lens-fields Systematic sampling
dc.subject.lens-fields Geography
dc.subject.lens-fields Household survey
dc.subject.lens-fields Agricultural science
dc.subject.lens-fields Subsidy
dc.subject.lens-fields Multiple correspondence analysis


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