Linking Artificial Intelligence and Insect Genetics for Coffee Plantation Research: A Bibliometric Perspective

Authors

Priyambodo Priyambodo , M. Iqbal Parabi , Elly Lestari Rustiati , Nindy Permatasari , Syarif Hidayat Amrullah , Siti Hamidatul 'Aliyah

DOI:

10.29303/jbt.v25i4.9996

Published:

2025-10-08

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Abstract

Artificial intelligence (AI) has advanced rapidly over the past two decades, creating opportunities to address ecological and agricultural challenges by integrating computational methods with genetics. This study aims to map the scientific landscape of research at the intersection of AI, insect population genetics, and coffee agroecosystems. A bibliometric analysis was conducted using the Scopus database, covering publications from 1978 to 2025 and employing co-occurrence, co-authorship, centrality, and co-citation analyses supported by VOSviewer for visualization. The results show a significant growth in publications since 2010, with the United States and Brazil as leading contributors, while collaborations among influential authors and institutions have shaped three main clusters: ecology and agroecosystem management, insect–pest interactions and biological control, and genetics with molecular approaches to plant metabolism. The co-citation network further highlights the integration of pest ecology, biodiversity conservation, and the economic value of pollinators as central themes. These findings indicate that AI–genetics integration is increasingly pivotal for sustainable coffee management, with future research directions emphasizing predictive modeling of pest and pollinator dynamics under climate variability, alongside investigations into soil microbiomes and pollinator health to enhance resilience in coffee production systems.

Keywords:

agroecosystems artificial intelligence coffee insect genetics

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Author Biographies

Priyambodo Priyambodo, Universitas Lampung

Author Origin : Indonesia

M. Iqbal Parabi, Jurusan Ilmu Komputer, FMIPA, Universitas Lampung

Author Origin : Indonesia

Elly Lestari Rustiati, Jurusan Biologi, FMIPA, Universitas Lampung

Author Origin : Indonesia

Nindy Permatasari, Jurusan Budidaya Tanaman Perkebunan, Politeknik Negeri Lampung

Author Origin : Indonesia

Syarif Hidayat Amrullah, Jurusan Biologi, FST, Universitas Islam Negeri Alauddin

Author Origin : Indonesia

Siti Hamidatul 'Aliyah, Pusat Riset Biomedis, Badan Riset dan Inovasi Nasional

Author Origin : Indonesia

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How to Cite

Priyambodo, P., Parabi, M. I., Rustiati, E. L., Permatasari, N., Amrullah, S. H., & ’Aliyah, S. H. (2025). Linking Artificial Intelligence and Insect Genetics for Coffee Plantation Research: A Bibliometric Perspective. Jurnal Biologi Tropis, 25(4), 5265–5277. https://doi.org/10.29303/jbt.v25i4.9996

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