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Alignment of the TRL-MRL for Selected Smartphone-Based Applications in Agricultural Extension and Education

Document Type : Research Paper

Authors

1 - Assistant Professor, Department of Agricultural Extension and Education, Faculty of Agricultural Engineering and Rural Development, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran.

2 M.S Department of Agricultural Extension and Education, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran

3 Assistant Professor, Department of Agricultural Extension and Education, Sari Agricultural Sciences and Natural Resources University

10.22092/jaear.2025.134001

Abstract

The imperative to achieve food security, sustainable agricultural practices, and smart farming development has reinforced technology studies with a sociological perspective. The deep interconnection between agricultural development strategies and technological transformations highlights the need for novel tools and methodologies to assess technology in support of innovation and entrepreneurship. Accordingly, this qualitative study aimed to develop an innovative framework for evaluating smartphone-based applications in agricultural extension and education, based on balancing technology readiness level (TRL) and market readiness level (MRL). The research instrument was a questionnaire derived from the nine-cell TRL-MRL matrix, the face and content validity of which was confirmed by university experts in agricultural extension and education, as well as subject-matter specialists proficient in technology assessment. Additionally, the reliability of the tool was estimated to be satisfactory, with a Guttman’s reproducibility coefficient (CR ≥ 0.80). Using the TRL-MRL matrix, the performance of 16 domestic agricultural extension and education applications was evaluated through a survey of 15 experts. Based on the findings, the applications were classified into four main categories: (1) agricultural knowledge and communication media, (2) education, consulting, and agricultural input provision, (3) farm smartification and monitoring, and (4) artificial intelligence in plant, pest, and disease identification. This classification provides an overview of the current status and developmental potential of agricultural extension and education applications. Furthermore, the findings revealed that most of these applications are at the market readiness stage, indicating their potential for widespread adoption and societal penetration. The proposed comparative matrix, with its structured approach to technology management, can serve as a lever for implementing innovative solutions to the evolving challenges of the agricultural sector.

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References
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Agricultural Education Administration Research
Volume 16, Issue 71 - Serial Number 71
March 2025
Pages 98-109
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