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Technologies Applied to Artificial Lighting in Indoor Agriculture: A Review

Author

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  • Luisa F. Lozano-Castellanos

    (TADRUS Research Group, Department of Agricultural and Forestry Engineering, ETSIIAA, University of Valladolid, 34004 Palencia, Spain
    Research Group on Biodiversity and Dynamics of Tropical Ecosystems—GIBDET, Faculty of Engineering Forestry, University of Tolima, Ibagué 730006, Colombia)

  • Luis Manuel Navas-Gracia

    (TADRUS Research Group, Department of Agricultural and Forestry Engineering, ETSIIAA, University of Valladolid, 34004 Palencia, Spain)

  • Isabel C. Lozano-Castellanos

    (Faculty of Science and Engineering, Curtin University, Perth 6102, Australia)

  • Adriana Correa-Guimaraes

    (TADRUS Research Group, Department of Agricultural and Forestry Engineering, ETSIIAA, University of Valladolid, 34004 Palencia, Spain)

Abstract

Artificial lighting is essential in indoor agriculture, directly influencing plant growth and productivity. Optimizing its use requires advanced technologies that improve light management and adaptation to crop needs. This systematic review, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, examines recent advancements in artificial lighting technologies, focusing on their applications, challenges, and future directions. A systematic search in Web of Science (WOS) and Scopus identified 70 relevant studies published between 2019 and 2024. The analysis highlights five major technology groups: (i) lighting control systems, with Light-Emitting Diodes (LEDs) as the dominant solution; (ii) Internet of Things (IoT) incorporating sensors, deep neural networks, Artificial Intelligence (AI), digital twins, and machine learning (ML) for real-time optimization, as well as communication technologies, enabling remote control and data-driven adjustments; (iii) simulation and modeling tools, refining lighting strategies to enhance plant responses and system performance; and (iv) complementary energy sources, improving lighting sustainability. IoT-driven automation has significantly improved artificial lighting efficiency, optimizing adaptation and plant-specific management. However, challenges such as system complexity, high energy demands, and scalability limitations persist. Future research should focus on refining IoT-driven adaptive lighting, improving sensor calibration for precise real-time adjustments, and developing cost-effective modular systems to enhance widespread adoption and optimize resource use.

Suggested Citation

  • Luisa F. Lozano-Castellanos & Luis Manuel Navas-Gracia & Isabel C. Lozano-Castellanos & Adriana Correa-Guimaraes, 2025. "Technologies Applied to Artificial Lighting in Indoor Agriculture: A Review," Sustainability, MDPI, vol. 17(7), pages 1-22, April.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:7:p:3196-:d:1627697
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    References listed on IDEAS

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    2. Chen, Xinge & Ji, Yaning & Wu, Gang & Zang, Jianbin & Lu, Lin & Zhang, Yi & Liang, Hao, 2025. "Optical and thermal performance of a spectral-splitting transmission/photovoltaic system for plant factories," Energy, Elsevier, vol. 336(C).

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