中国稻米2026，Vol.32Issue(2)：45-52,8.DOI:10.3969/j.issn.1006-8082.2026.02.008
基于三维重建的分蘖期水稻性状提取方法研究
Research on a Tillering Stage Rice Traits Extraction Method Based on 3D Reconstruction
摘要
Abstract
Rice is a major staple food crop worldwide,and accurate measurement of phenotypic traits during the tillering stage is essential for breeding programs and yield assessment.Conventional measurement methods are often time-consuming,labor-intensive,and susceptible to subjective errors.To overcome these limitations,this study introduces a 3D reconstruction approach based on Neural Radiance Fields(NeRF)for high-precision,non-destructive extraction of phenotypic parameters of rice at the tillering stage.The method begins by capturing multi-view videos of rice plants using a consumer-grade smartphone,followed by an adaptive frame extraction algorithm to obtain high-quality image sequences.Camera poses are then estimated using Structure-from-Motion(SfM),and an improved Instant-NGP algorithm is applied for efficient 3D reconstruction.Compared to the original NeRF,the proposed method achieves a 17.3%improvement in peak signal-to-noise ratio,a 54.3%reduction in GPU memory usage,and a 99.4%decrease in reconstruction time.The resulting point clouds undergo preprocessing—including downsampling,denoising,coordinate correction,and segmentation—to extract key phenotypic traits such as plant height,stem diameter,tiller number,tiller angle,projected area,bounding box volume,and leaf count.Experimental results show strong agreement between automated and manual measurements,with coefficients of determination(R2)of 0.98,0.94,1.00,0.95,and 0.97 for plant height,stem diameter,tiller number,tiller angle,and leaf number,respectively.The corresponding mean absolute percentage errors were 2.38%,5.16%,0%,7.15%,and 2.20%.This research offers reliable technical support for rice breeding and precision cultivation.关键词
水稻/分蘖期/三维重建/神经辐射场/表型性状Key words
rice/tillering stage/3D reconstruction/Neural Radiance Fields(NeRF)/phenotypic traits分类
信息技术与安全科学引用本文复制引用
谈颖,高发瑞,卢淼,王刘西航,杨圣杰,展颖超,冯尚宗,傅生辉,刘双喜..基于三维重建的分蘖期水稻性状提取方法研究[J].中国稻米,2026,32(2):45-52,8.基金项目
山东省现代农业产业技术体系水稻农业机械岗位专家项目(SDAIT-17-08) （SDAIT-17-08）
