Exploring Accurate 3D Phenotyping in Greenhouse through Neural Radiance Fields

arXiv:2403.15981v1 Announce Type: new
Abstract: Accurate collection of plant phenotyping is critical to optimising sustainable farming practices in precision agriculture. Traditional phenotyping in controlled laboratory environments, while valuable, falls short in understanding plant growth under real-world conditions. Emerging sensor and digital technologies offer a promising approach for direct phenotyping of plants in farm environments. This study investigates a learning-based phenotyping method using the Neural Radiance Field to achieve accurate in-situ phenotyping of pepper plants in greenhouse environments. To quantitatively evaluate …

abstract agriculture arxiv collection cs.cv digital digital technologies environments farming fields greenhouse growth laboratory neural radiance fields practices precision sensor sustainable sustainable farming technologies through type understanding world