用普通相机拍20秒视频，就能低成本精准测量玉米穗三维形状。
AI-enabled Low-Cost 3D Maize Ear Morphometry Platform at Breeding Scale
- 单次拍摄+神经辐射场重建，自动完成玉米穗3D建模。
- 83.3%样本通过质检，长度与人工测量相关性达0.964，体积误差仅5.26mL。
- 硬件成本仅607美元，每穗处理时间从5分钟减至1分钟。
玉米穗几何形态（长度、宽度、弯曲度、体积）与产量和籽粒充实密切相关，但现有高通量表型流程受限于成本、人力和专用设备。我们开发并验证了一种低成本方案：使用消费级单反相机在匀光LED环境下，配合电机转台拍摄20秒视频，即可重建出封闭的玉米穗三维网格模型。通过多种子点COLMAP获取相机位姿，初始化神经辐射场（NeRF），并利用已知直径的圆柱形支架在每帧中实现自动尺度校准及下游几何质量控制。该方法应用于300个不同自交系玉米穗，其中250个（83.3%）成功通过自动化处理与质量检测。骨架长度与人工卡尺测量结果高度一致（R² = 0.964，RMSE = 4.68 mm）；凸包体积与排水法测量在15个跨度全尺寸范围的样本上吻合良好（R² = 0.982，RMSE = 5.26 mL）。残差长度误差随穗弯曲度增加而上升，而边界框高度（对应卡尺直线弦长）无此趋势，说明差异源于测量定义：卡尺测弦长，骨架长度追踪大地弧长。整套系统硬件成本约607美元，操作时间由约5分钟/穗降至1分钟/穗，后续处理全程无人值守。该平台为育种规模的三维穗表型分析奠定了基础。
原文摘要 · Abstract (English)
Maize ear geometry (length, width, curvature, and volume) is closely tied to yield and grain-filling outcomes, but existing high-throughput phenotyping pipelines remain constrained by the cost, labor, and specialized hardware they require. We developed and validated a low-cost pipeline that reconstructs a watertight 3-D mesh of a maize ear from a single 20-second video captured with a consumer-grade DSLR on a motorized turntable under uniform LED illumination. Camera poses from a multi-seed COLMAP procedure initialize a Neural Radiance Field (NeRF), and a cylindrical holder of known diameter, visible in every frame, provides automatic metric scaling with downstream geometric quality control. Applied to 300 ears spanning a diverse maize inbred panel, 250 (83.3%) passed automated processing and quality control. Skeleton length agreed with manual caliper measurements across all 250 ears (R^2 = 0.964, RMSE = 4.68 mm), and convex-hull volume agreed with water-displacement volume on a 15-ear subset spanning the full size range (R^2 = 0.982, RMSE = 5.26 mL). Residual length error grew with ear curvature, whereas bounding-box height, which records the same straight-line chord as calipers, showed no such trend; the discrepancy therefore originates in the measurement definition, since calipers record the chord while skeleton length traces the geodesic arc. The capture hardware costs approximately 607 USD, and operator involvement fell from roughly five minutes to one minute per ear, with all downstream processing running unattended. The platform provides a foundation for breeding-scale 3-D ear phenotyping.
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