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首次评估红外热像技术在奶牛养殖场监测乳房健康状况中的应用。

First Evaluation of Infrared Thermography as a Tool for the Monitoring of Udder Health Status in Farms of Dairy Cows.

机构信息

Department of Human Sciences and Quality of Life Promotion, Università Telematica San Raffaele Roma, Via di Val Cannuta 247, Rome 00166, Italy.

Department of Veterinary Medicine, Università degli Studi di Milano, Via Celoria 10, Milan 20133, Italy.

出版信息

Sensors (Basel). 2018 Mar 14;18(3):862. doi: 10.3390/s18030862.

Abstract

The aim of the present study was to test infrared thermography (IRT), under field conditions, as a possible tool for the evaluation of cow udder health status. Thermographic images (n. 310) from different farms (n. 3) were collected and evaluated using a dedicated software application to calculate automatically and in a standardized way, thermographic indices of each udder. Results obtained have confirmed a significant relationship between udder surface skin temperature (USST) and classes of somatic cell count in collected milk samples. Sensitivity and specificity in the classification of udder health were: 78.6% and 77.9%, respectively, considering a level of somatic cell count () of 200,000 cells/mL as a threshold to classify a subclinical mastitis or 71.4% and 71.6%, respectively when a threshold of 400,000 cells/mL was adopted. Even though the sensitivity and specificity were lower than in other published papers dealing with non-automated analysis of IRT images, they were considered acceptable as a first field application of this new and developing technology. Future research will permit further improvements in the use of IRT, at farm level. Such improvements could be attained through further image processing and enhancement, and the application of indicators developed and tested in the present study with the purpose of developing a monitoring system for the automatic and early detection of mastitis in individual animals on commercial farms.

摘要

本研究旨在测试红外热成像(IRT)在野外条件下作为评估奶牛乳房健康状况的一种可能工具。从不同农场(n = 3)收集了热成像图像(n = 310),并使用专用软件应用程序进行评估,以自动且标准化地计算每个乳房的热成像指数。结果证实,乳房表面皮肤温度(USST)与采集牛奶样本中的体细胞计数等级之间存在显著关系。在将体细胞计数()为 200,000 个细胞/mL 作为分类亚临床乳腺炎的阈值的情况下,对乳房健康的分类的敏感性和特异性分别为 78.6%和 77.9%;当采用 400,000 个细胞/mL 的阈值时,敏感性和特异性分别为 71.4%和 71.6%。尽管敏感性和特异性低于其他处理 IRT 图像非自动化分析的已发表论文,但考虑到这是这项新技术的首次现场应用,因此被认为是可以接受的。未来的研究将允许在农场层面进一步改进 IRT 的使用。通过进一步的图像处理和增强,以及应用本研究中开发和测试的指标,可以实现这种改进,目的是为商业农场的个体动物自动和早期检测乳腺炎开发监测系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c36d/5877300/2fab4c774d1d/sensors-18-00862-g001.jpg

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