Developing a Mobile App for Precision Irrigation Management in Smallholder Farms

Thesis Abstract

Smallholder farmers constitute a vital segment of agricultural production but often face significant challenges in optimizing water use due to limited access to precise irrigation technologies and resource constraints. Inadequate irrigation management leads to water wastage, crop stress, yield variability, and environmental degradation, underscoring the urgent need for accessible digital solutions to enhance irrigation efficiency at the smallholder level. This study aims to develop, implement, and evaluate a mobile application designed to facilitate precision irrigation management for smallholder farmers, thereby contributing to sustainable water and crop productivity enhancement. The specific objectives include (1) assessing farmers’ current irrigation practices and their technological literacy; (2) designing a user-centered mobile app integrating soil moisture monitoring, weather data, and crop water requirements; (3) evaluating the usability and acceptance of the app among smallholder farmers; and (4) analyzing the impact of app-enabled irrigation management on water use efficiency and crop yields. The research adopts a mixed-methods approach, combining qualitative assessments and quantitative analysis. The study population encompasses 300 smallholder farmers engaged in vegetable and maize cultivation within the Riverine Agricultural Zone. A stratified random sampling technique was employed to select participants, ensuring representation across different farm sizes and socioeconomic backgrounds. Data collection instruments include structured questionnaires to evaluate baseline irrigation practices and technology familiarity, semi-structured interviews for in-depth insights, and field measurements of soil moisture content and water volume used pre- and post-intervention. The mobile app’s usability and acceptance data are collected via the System Usability Scale (SUS) and Technology Acceptance Model (TAM) questionnaires administered at two intervals before and after app deployment. The analytical framework involves descriptive statistics and inferential analysis. Quantitative data on water consumption, crop yields, and user satisfaction will be analyzed using paired t-tests and multiple regression analysis to determine the effect of app use on water efficiency and productivity. Thematic analysis will be employed to interpret qualitative interview data, identifying perceived benefits, barriers, and suggestions for app improvement. The study also draws on the Technology Acceptance Model (TAM) and Diffusion of Innovations theory to interpret adoption behaviors and acceptance levels. Expected findings suggest that the mobile app will significantly improve water use efficiency, with an anticipated reduction in water consumption by approximately 20% and a yield increase of around 15% among users, compared to baseline figures. The usability assessments are projected to indicate high acceptance and satisfaction levels, with positive correlations between perceived ease of use, perceived usefulness, and actual app adoption. Moreover, qualitative data are expected to reveal critical factors influencing sustained usage, including contextual relevance, ease of navigation, and perceived sustainability benefits. This research contributes to agricultural extension and ICT adoption literature by providing empirical evidence on the effectiveness of mobile-based decision support systems in smallholder irrigation practices. It advances theoretical understanding by applying and validating the applicability of TAM and Diffusion of Innovations within the context of environmental sustainability and resource-constrained farming systems. The developed app’s design framework and evaluation findings offer scalable models for similar smallholder contexts across developing regions, thereby aligning with global objectives to enhance water efficiency and food security. The study concludes that tailored mobile applications, grounded in user-centered design and contextual relevance, are viable tools for promoting sustainable irrigation practices among smallholder farmers. Recommendations include integrating the app into government and NGO extension programs, undertaking continuous user training, and fostering an enabling policy environment to support digital agricultural innovations. Future research should explore long-term impacts, scalability, and integration with other climate-smart agricultural technologies to sustain and amplify the benefits demonstrated.