Adopting TOGAF Framework for Sustainable and Scalable Robusta Coffee Leaf Rust Management

Robusta coffee (Coffea canephora) is a globally significant crop. However, managing Coffee Leaf Rust remains challenging due to the reliance on manual detection methods and the lack of structured technological integration. This study proposes a TOGAF-based framework as a scalable and adaptable solut...

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Main Authors: Thein Oak Kyaw Zaw, Kalaiarasi Sonai Muthu Anbananthen, Saravanan Muthaiyah, Baarathi Balasubramaniam, Suraya Mohammad, Yunus Yusoff, Khairul Shafee Kalid
Format: Article
Language:English
Published: Ital Publication 2025-06-01
Series:Emerging Science Journal
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Online Access:https://ijournalse.org/index.php/ESJ/article/view/3013
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author Thein Oak Kyaw Zaw
Kalaiarasi Sonai Muthu Anbananthen
Saravanan Muthaiyah
Baarathi Balasubramaniam
Suraya Mohammad
Yunus Yusoff
Khairul Shafee Kalid
author_facet Thein Oak Kyaw Zaw
Kalaiarasi Sonai Muthu Anbananthen
Saravanan Muthaiyah
Baarathi Balasubramaniam
Suraya Mohammad
Yunus Yusoff
Khairul Shafee Kalid
author_sort Thein Oak Kyaw Zaw
collection DOAJ
description Robusta coffee (Coffea canephora) is a globally significant crop. However, managing Coffee Leaf Rust remains challenging due to the reliance on manual detection methods and the lack of structured technological integration. This study proposes a TOGAF-based framework as a scalable and adaptable solution for structuring Coffee Leaf Rust management strategies. The framework leverages enterprise architecture principles to integrate learning algorithms, image detection, and systematic plantation mapping within a structured approach that enhances data organization, rust severity visualization, and predictive analysis. The proposed framework provides a strategic roadmap for integrating technology into Coffee Leaf Rust detection and management by focusing on modularity, scalability, and stakeholder engagement. Unlike existing ad-hoc approaches, this framework is a foundation for future technology-driven solutions, balancing manual practices with structured digital adoption. As no prior research has combined TOGAF with agricultural disease management, this study presents a novel conceptual contribution that could guide future developments in smart agriculture. By adopting this framework, the Robusta coffee industry can move toward proactive, data-driven Coffee Leaf Rust management, fostering long-term resilience and productivity.
format Article
id doaj-art-65f6ce8b668d416d9eafcb0a87acefcf
institution Kabale University
issn 2610-9182
language English
publishDate 2025-06-01
publisher Ital Publication
record_format Article
series Emerging Science Journal
spelling doaj-art-65f6ce8b668d416d9eafcb0a87acefcf2025-08-20T03:27:10ZengItal PublicationEmerging Science Journal2610-91822025-06-01931308132110.28991/ESJ-2025-09-03-0102736Adopting TOGAF Framework for Sustainable and Scalable Robusta Coffee Leaf Rust ManagementThein Oak Kyaw Zaw0Kalaiarasi Sonai Muthu Anbananthen1Saravanan Muthaiyah2Baarathi Balasubramaniam3Suraya Mohammad4Yunus Yusoff5Khairul Shafee Kalid6School of Business and Technology, International Medical University, Kuala Lumpur, 57000Centre for Advanced Analytics, CoE for Artificial Intelligence & Faculty of Information Science and Technology, Multimedia University, Melaka 75450School of Business and Technology, International Medical University, Kuala Lumpur, 57000Centre for Advanced Analytics, CoE for Artificial Intelligence & Faculty of Information Science and Technology, Multimedia University, Melaka 75450Communication Technology Section, Universiti Kuala Lumpur British Malaysian Institute, Gombak, SelangorInstitute of Informatics and Computing in Energy (IICE) and College of Computing and Informatics, University Tenaga Nasional, 43000 KajangDepartment of Computer Information Sciences, Universiti Teknologi PETRONAS, Seri IskandarRobusta coffee (Coffea canephora) is a globally significant crop. However, managing Coffee Leaf Rust remains challenging due to the reliance on manual detection methods and the lack of structured technological integration. This study proposes a TOGAF-based framework as a scalable and adaptable solution for structuring Coffee Leaf Rust management strategies. The framework leverages enterprise architecture principles to integrate learning algorithms, image detection, and systematic plantation mapping within a structured approach that enhances data organization, rust severity visualization, and predictive analysis. The proposed framework provides a strategic roadmap for integrating technology into Coffee Leaf Rust detection and management by focusing on modularity, scalability, and stakeholder engagement. Unlike existing ad-hoc approaches, this framework is a foundation for future technology-driven solutions, balancing manual practices with structured digital adoption. As no prior research has combined TOGAF with agricultural disease management, this study presents a novel conceptual contribution that could guide future developments in smart agriculture. By adopting this framework, the Robusta coffee industry can move toward proactive, data-driven Coffee Leaf Rust management, fostering long-term resilience and productivity.https://ijournalse.org/index.php/ESJ/article/view/3013agricultural technology integrationcoffee leaf rustcoffee rust detectiontogaf framework
spellingShingle Thein Oak Kyaw Zaw
Kalaiarasi Sonai Muthu Anbananthen
Saravanan Muthaiyah
Baarathi Balasubramaniam
Suraya Mohammad
Yunus Yusoff
Khairul Shafee Kalid
Adopting TOGAF Framework for Sustainable and Scalable Robusta Coffee Leaf Rust Management
Emerging Science Journal
agricultural technology integration
coffee leaf rust
coffee rust detection
togaf framework
title Adopting TOGAF Framework for Sustainable and Scalable Robusta Coffee Leaf Rust Management
title_full Adopting TOGAF Framework for Sustainable and Scalable Robusta Coffee Leaf Rust Management
title_fullStr Adopting TOGAF Framework for Sustainable and Scalable Robusta Coffee Leaf Rust Management
title_full_unstemmed Adopting TOGAF Framework for Sustainable and Scalable Robusta Coffee Leaf Rust Management
title_short Adopting TOGAF Framework for Sustainable and Scalable Robusta Coffee Leaf Rust Management
title_sort adopting togaf framework for sustainable and scalable robusta coffee leaf rust management
topic agricultural technology integration
coffee leaf rust
coffee rust detection
togaf framework
url https://ijournalse.org/index.php/ESJ/article/view/3013
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