This study investigates the potential of mobile technology to enhance sustainable land and soil management among smallholder maize farmers in Southwest Nigeria. Applying DesignScience Research Methodology (DSRM) approach, and quantitative research method, this study evaluates how the Land Potential Knowledge System (LandPKS) mobile application conforms to mobile design principles, assess the accuracy of its underlying soil data from the Harmonized World Soil Database, and examine its adaptability to local usability needs and farming practices. A heuristic evaluation was conducted to assess the app´s design features, revealing that while LandPKS performs well in areas such as ease of use, system status visibility and offline functionality, it lacks critical features like local language support, technical performance, accessibility compliance, responsive feedback systems and up-to-date content/version improvement. Correlation analysis between the Harmonized World Soil Database (HWSD) and local observed field measurements showed weak and very limited alignment for key variables such as ESP and ECEC, indicating that the LandPKS app´s soil data may not adequately reflect the field-level variability. While ANOVA analysis showed no statistically significant differences between cropping systems’ groups for all the measured soil properties, the descriptive mean comparison highlights variation in two key soil properties (Phosphorus (P), ESP) across cropping systems. Furthermore, the survey data revealed that factors that influenced maize productivity are essentially the original status of fertility of the cultivated land, and the use of the soil and water conservation techniques used by the farmers. The access to the extension services and the training, as well as training and implementation of correction techniques show strong correlations, but they do not have a direct impact on the land’s productivity. These findings suggest that the app's decision-making support mechanism should integrate local agricultural practices, and reflect the learnings farmers get from the training which indeed seem to inform them about the corrections they can implement. Technically, there is a need to improve the LandPKS responsiveness and personalization, as well as to incorporate locally validated soil data. This study contributes to the digital agriculture by shedding light on the comparative accuracy of HWSD versus local soil data and suggests practical recommendations for improving the contextual relevance, usability and reliability of mobile apps like LandPKS in dynamic and resource-constrained farming environments.