Review of Agricultural and Rural Development System Models and Frameworks to Support Farming as a Business via Benchmarking: The Case of Tanzania

This research article published by the International Journal of Computing and Digital Systems, 2019This paper presents a review of the current state of agricultural and rural development (ARD) system frameworks, focusing on their capabilities and limitations to support farming-as-a-business via benchmarking (FAABB). Presented and discussed include the state of system models in relation to five modelling views of the ARD systems, namely: (i) defining factors for agricultural echo systems, (ii) farm characterization and management practices, (iii) simulation systems for predictable farm data, (iv) limiting factors for agricultural optimization, and (v) performance estimation through benchmarking. Also, the paper proposes a new framework to support FAABB in Tanzania that is being tested through various use-cases in the Southern Agricultural Growth Corridor of Tanzania (SAGCOT) with a FAABB Cyber Studio hosted at the Nelson Mandela – African Institution of Science and Technology (NM-AIST) also in Tanzania. The FAABB setup at NM-AIST promises to address not only the agricultural knowledge codification problem, but also the need for cultural change among agricultural researchers to ensure that data for addressing a range of use-cases is available for future mobile application development. The proposed FAABB framework provides a useful starting point for addressing limitations of existing frameworks and considering a ubiquitous m-app development framework for targeted ARD research in developing countries