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

This 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 mo...

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Published in:International Journal of Computing and Digital System (Jāmiʻat al-Baḥrayn. Markaz al-Nashr al-ʻIlmī) Vol. 8; no. 6; pp. 575 - 588
Main Authors: Kyaruzi, John J, Yonah, Zaipuna O, Swai, Hulda S
Format: Journal Article
Language:English
Published: University of Bahrain, Deanship of Graduate Studies and Scientific Research 01-11-2019
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Abstract This 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. Keywords: Agricultural and rural development (ARD), Farming-as-a-business via benchmarking (FAABB), System models, Frameworks, Use-cases.
AbstractList This 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. Keywords: Agricultural and rural development (ARD), Farming-as-a-business via benchmarking (FAABB), System models, Frameworks, Use-cases.
This 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.
Audience Academic
Author Swai, Hulda S
Kyaruzi, John J
Yonah, Zaipuna O
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SubjectTerms Agricultural industry
Analysis
Benchmarking
Developing countries
Rural development
Technology
Title Review of Agricultural and Rural Development System Models and Frameworks to Support Farming as a Business via Benchmarking: The Case of Tanzania
Volume 8
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