Development of mobile-based recommender system for smallholder dairy farmers to increase their production in Tanzania

Abstract

Dairy farming is a branch of agriculture which is devoted to the production of milk and the processing of dairy products. Small holder farmers are individuals producing small amounts of products on small land holdings of less than two (2) hectares. This study aimed to make a recommendation model using association rules to suggest recommendations for dairy farm management to smallholder farmers based on their farm details. The key objectives were to identify requirements of the recommendation model, to develop the recommendation model, to deploy and validate the model as an end user mobile tool. The study was conducted in Arusha and Kilimanjaro regions in Tanzania. Systematic random sampling was used for data collection, Apriori algorithm was used in recommendation model development and incremental methodology was used in mobile application development. A recommender system was developed through association rules mining to provide recommendations to the smallholder dairy farmers that help them to increase their production using strategies available from fellow farmers in the same cluster. These association rules were used to help small holder dairy farmers to move from low milk production (9.15  3.25 litres) to medium milk production (11.08  4.29 litres) and then to high milk production (14.45  5.12 litres) gradually. The Dairy Recommender System mobile application with a recommendation model deployed in the backend was developed for farmers to easily get information on how to improve dairy farming practices.