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基于多源图像和环境信息融合的规模化养殖蛋鸡体温测量方法

宋道一 罗升 朱玉华 童勤 王红英 王粮局

农业机械学报2025,Vol.56Issue(1):37-46,10.
农业机械学报2025,Vol.56Issue(1):37-46,10.DOI:10.6041/j.issn.1000-1298.2025.01.004

基于多源图像和环境信息融合的规模化养殖蛋鸡体温测量方法

Temperature Measurement Method for Commercially Farmed Layer Hens Based on Multi-source Image and Environmental Data Fusion

宋道一 1罗升 2朱玉华 1童勤 3王红英 1王粮局1

作者信息

  • 1. 中国农业大学工学院,北京 100083
  • 2. 江苏省农业机械试验鉴定站,南京 210017
  • 3. 中国农业大学水利与土木工程学院,北京 100083
  • 折叠

摘要

Abstract

Large-scale egg farming faces challenges in assessing the health status of laying hens and preventing disease outbreaks.The need for effective flock health monitoring in egg production is becoming increasingly important.As homeothermic animals,the body temperature of laying hens serves as a crucial indicator of their health.A method for measuring the body temperature of stacked cage laying hens was proposed by integrating multi-source information.To improve measurement accuracy,temperature drift correction and distance correction were applied to the thermal infrared camera.The thermal infrared images were then pixel-level aligned with the acquired near-infrared and depth images.These fused multi-source images were used to detect the heads of the laying hens through the YOLO v8n detection network,achieving detection results of 97.0%for AP50 and 76.1%for AP50-95.Temperature drift and distance corrections were performed on the thermal infrared images of the hens'heads,using ambient temperature and distance information.Temperature feature points were then extracted from the corrected images to calculate the head temperature of the laying hens.A prediction dataset was constructed based on environmental factors such as ambient temperature,humidity,wind speed,light intensity,and the hens'head temperature.Various machine learning algorithms were used to predict the body temperature,with the random forest algorithm showing the best performance,achieving an R2 of0.696 and an RMSE of 0.246℃.The research result can provide a reference for achieving accurate,high-throughput,and non-invasive measurement of body temperature in large-scale egg farms.

关键词

蛋鸡/规模化养殖/测温/热红外图像/YOLO v8n

Key words

layer hens/large-scale farming/temperature measurement/thermal infrared imaging/YOLO v8n

分类

计算机与自动化

引用本文复制引用

宋道一,罗升,朱玉华,童勤,王红英,王粮局..基于多源图像和环境信息融合的规模化养殖蛋鸡体温测量方法[J].农业机械学报,2025,56(1):37-46,10.

基金项目

科技创新2030—"新一代人工智能"重大项目(2021ZD0113804-3) (2021ZD0113804-3)

农业机械学报

OA北大核心

1000-1298

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