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NeRF Driven 3D Crop Phenomics Intelligent Monitoring for Precision Greenhouse Agriculture
1
School of Computer Science and Engineering, Chongqing Three Gorges University, Wanzhou District, Chongqing 404020, China
*
Author to whom correspondence should be addressed.
JEIT 2025 7(4):262; https://doi.org/10.69610/j.eit.2025080801
Received: / Accepted: / Published Online: 8 August 2025
Abstract
With the advancement of agricultural modernization, the intelligent management of greenhouses has become crucial for improving agricultural productivity. Neural Radiance Fields (NeRF), as an emerging 3D modeling and rendering technology, offers new solutions for environmental monitoring, crop growth modeling, and pest and disease early warning in greenhouses. This paper reviews the principles of NeRF, its 3D reconstruction methods, and its application progress in greenhouses. It also explores the potential of integrating NeRF with digital twin technology and analyzes the current status of plant growth models in greenhouses. The study shows that NeRF has broad prospects for application in agriculture but still faces challenges in data acquisition, model optimization, and computational efficiency. Future research needs to further integrate multi-source data and optimize neural network models to promote the intelligent management of greenhouses.
Copyright: © 2025 by Li, Wang, Zhang, Zhao and Lian. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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ACS Style
Li, T.; Wang, J.; Zhang, T.; Zhao, J.; Lian, S. NeRF Driven 3D Crop Phenomics Intelligent Monitoring for Precision Greenhouse Agriculture. Journal of Engineering Innovations & Technology, 2025, 7, 262. doi:10.69610/j.eit.2025080801
AMA Style
Li T., Wang J., Zhang T. et al.. NeRF Driven 3D Crop Phenomics Intelligent Monitoring for Precision Greenhouse Agriculture. Journal of Engineering Innovations & Technology; 2025, 7(4):262. doi:10.69610/j.eit.2025080801
Chicago/Turabian Style
Li, Taizhi; Wang, Jingya; Zhang, Tingshun; Zhao, Jin; Lian, Shuo 2025. "NeRF Driven 3D Crop Phenomics Intelligent Monitoring for Precision Greenhouse Agriculture" Journal of Engineering Innovations & Technology 7, no.4:262. doi:10.69610/j.eit.2025080801
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References
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