基于YOLO和增强现实的玉米穗位高实时测量方法

Real-time Measurement of Maize Ear Height Based on YOLO and Augmented Reality

摘要:

高效、准确的玉米穗位高监测对于玉米抗倒伏育种研究至关重要。传统人工测量方法费时费力，现有自动化方案在复杂田间条件下鲁棒性不足或成本高。本研究基于YOLO模型和增强现实（AR）技术，设计了一款用于玉米穗位高智能测量的iOS应用程序，可实现玉米穗位高实时、精准、高效且低成本的测量。该系统包含玉米雌穗检测模型和高度测量模块。雌穗检测模型使用在灌浆期玉米田间采集的1000幅雌穗图像构建的数据集（涵盖不同光照和遮挡条件）进行模型训练与验证，在多个目标检测模型中，YOLO v5s表现出最佳性能，精确率为0.844，召回率为0.724，平均精度AP0.5为0.814。该雌穗检测模型被集成至基于AR技术的实时测量模块，在iOS设备上的兼容性和准确性均表现良好，响应时间小于0.3s。田间验证表明，穗位高检测结果与人工实测值高度一致（R2为0.750~0.864，RMSE为0.10~0.13m）；智能测量系统由单人操作，单个小区测量10株以上雌穗用时2min以内，与传统塔尺测量相比速度提高6倍以上。本系统在保证准确性的同时显著提升了玉米穗位高测量的效率，可为玉米育种研究提供实时精准的数据支持。

Abstract:

Efficient and accurate monitoring of maize ear height (EH) is critical for anti-lodging breeding. The traditional manual measurement approach is labor-intensive and time-consuming, while existing automated approaches often lack robustness under varying field conditions or involve high costs. To address these limitations, an iOS application (APP) was developed based on the you only look once (YOLO) model and augmented reality (AR) technology for real-time, accurate, efficient, and low-cost maize EH measurement. It comprised two modules: a maize ear detection model and a height measurement module. The ear detection model was trained and validated on a dataset comprising 1000 field images collected from maize fields during the filling stage, under various lighting and occlusion conditions. Among different object detection models, the YOLO v5s model demonstrated the most robust performance with a precision of 0.844, a recall of 0.724, and an AP0.5 of 0.814. The trained detection model had been integrated into a maize EH measurement system, which utilized the AR technology for real-time measurement. It demonstrated excellent compatibility and performance on iOS devices, with response time below 0.3 s. Field evaluation results indicated a high correlation between the EH measured by the app and manual measurements (R2=0.750~0.864, RMSE=0.10~0.13m). The app was optimized for solo operation. To finish measuring a plot with over 10 maize plants only took less than 2 minutes, which was over 6 times faster than that of the traditional measurement with the leveling rod. This app significantly improved the efficiency of maize EH measurements while maintaining accuracy, providing real-time and precise data support for field management and breeding programs.