The estimation of soil properties is an important factor in agriculture. With the advancement of smartphones and artificial intelligence, estimating soil properties such as the Munsell soil color, pH, soil organic matter and moisture is tangible, alleviating the need for laboratories, which are time-consuming and costly. While there are several smartphone applications available in different app stores that claim to provide this functionality, an evaluation of the limitations and quality is required for these apps. The objective of this study is to identify existing soil property estimation apps, devise a soil apps rating scale to evaluate the functionality along with the software quality characteristics, and provide design guidelines for improving apps of this type. A thorough search was conducted in two prominent app stores: the Google Play and Apple App store. The selected apps were then rated by four individual raters. A total of 337 apps were found in the search and from this list, 32 selected apps were reviewed using the devised app rating scale. The rating scale evaluates the apps against ten sub-scales: app metadata, aesthetics, general app features, performance and efficiency, usability, functionality, subjective quality, transparency, user comments, and the perceived impact of the app on users. The inter-rater and intra-rater reliability are calculated along with the internal consistency of the rating scale to ensure the validity of the results. The evaluation results that returned the highest-ranking mean sub-scales were performance, usability, and aesthetics. Adversely, the lowest-ranging sub-scales were functionality and general features. There was also an evident absence of the functionality to calculate any type of soil properties in all but four of the apps reviewed. Several key design considerations were identified, such as the need for automated estimation of soil properties, an improvement of general features, and the inclusion of a shared soil database.
