Adoption and Limitations of Smartphone Plant Disease Identification Apps in Early Disease Detection Among Crop Farmers in Atiba Local Government Area, Oyo State, Nigeria

Abstract

Crop diseases pose a major threat to agricultural productivity in sub-Saharan Africa, with estimated yield losses of 20–40% annually, while traditional diagnostic services remain out of reach for many smallholder farmers. This study assessed awareness, adoption and constraints related to smartphone-based plant disease identification applications among 150 crop farmers in Atiba Local Government Area, Oyo State, Nigeria, using a descriptive survey design and multistage sampling. Data were collected through face-to-face administration of structured questionnaires and analysed using descriptive statistics and chi-square tests. The socioeconomic profile showed a predominantly middle-aged population with generally low to moderate education and digital experience, and although all respondents either owned or had access to smartphones, awareness of disease identification applications was only 47.3%. Adoption remained modest, with 25.3% regular users, 15.3% occasional users, and 52.7% never-users. Chi-square results indicated that age group, educational level, smartphone ownership and digital experience were all significantly associated with adoption status. Among users, perceived benefits include early disease detection (mean = 3.42), reduced crop loss (3.31), improved yield (3.18) and reduced chemical costs (3.05) all exceeded the decision threshold of 2.50. Major constraints were poor internet connectivity (3.48), high data costs (3.36), concerns about diagnostic accuracy (3.12), and low digital literacy (3.05). The study concludes that increasing adoption will require integrated efforts to improve rural connectivity and data affordability, strengthen farmers’ digital skills and embed validated localised applications within extension systems.