Object-Centric 3D Gaussian Splatting for Strawberry Plant Reconstruction and Phenotyping

Abstract

Strawberries are among the most economically significant fruits in the United States, generating over $2 billion in annual farm-gate sales and accounting for approximately 13% of the total fruit production value. Plant phenotyping plays a vital role in selecting superior cultivars by characterizing plant traits such as morphology, canopy structure, and growth dynamics. However, traditional plant phenotyping methods are time-consuming, labor-intensive, and often destructive. Recently, neural rendering techniques, notably Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS), have emerged as powerful frameworks for high-fidelity 3D reconstruction. By capturing a sequence of multi-view images or videos around a target plant, these methods enable non-destructive reconstruction of complex plant architectures. Despite their promise, most current applications of 3DGS in agricultural domains reconstruct the entire scene, including background elements, which introduces noise, increases computational costs, and complicates downstream trait analysis. To address this limitation, we propose a novel object-centric 3D reconstruction framework incorporating a preprocessing pipeline that leverages the Segment Anything Model v2 (SAM-2) and alpha channel background masking to achieve clean strawberry plant reconstructions. This approach produces more accurate geometric representations while substantially reducing computational time. With a background-free reconstruction, our algorithm can automatically estimate important plant traits, such as plant height and canopy width, using DBSCAN clustering and Principal Component Analysis (PCA). Experimental results show that our method outperforms conventional pipelines in both accuracy and efficiency, offering a scalable and non-destructive solution for strawberry plant phenotyping.

Plant phenotyping relevance

イチゴ植物の3D再構成、背景除去、形質推定を一体化した新規フェノタイピング手法の開発・評価が中心であり、植物高と樹冠幅を自動推定して精度・効率を比較している。

Code and data availability

The supplied blocks describe the authors' strawberry video dataset (15 plants, iPhone 16, April 2025) and their object-centric 3DGS pipeline, but contain no public deposit, availability statement, or authors' URL for the dataset, images, code, or models. The only allowed URL is a cited market report (Fresh Produce 2024

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