肉牛生理指标智能监测技术研究进展与展望
[目的/意义]随着自动化、数智化技术的快速发展及其相关技术在肉牛养殖上的逐步推广利用，肉牛智能化养殖技术研究也取得了一定进步。肉牛的生理指标如运动量、体温、心率、呼吸频率，以及反刍量等变化反映了肉牛的健康或亚健康状态。基于多种传感器采集到的数据以及机器学习、数据挖掘及模型化分析等技术的利用，肉牛的生理指标可由智能感知装备尤其接触式设备自动获取并用于发情、产犊、健康和应激的监测。[进展]针对肉牛养殖过程生理指标的智能监测技术及其利用价值进行了系统分析，分析了生理指标监测技术在实际生产中的应用现状，总结了肉牛生理指标监测的难点和挑战，并提出了未来发展方向。[结论/展望]肉牛生理指标的智能监测与利用...
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| Published in | 智慧农业（中英文） Vol. 6; no. 4; pp. 1 - 17 |
|---|---|
| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
中国农业科学院农业信息研究所
30.07.2024
中国农业科学院 北京畜牧兽医研究所,畜禽营养与饲养全国重点实验室,北京 100193,中国%阳信亿利源清真肉类有限公司,山东滨州 251800,中国%北京首农畜牧发展有限公司,北京 102600,中国 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2096-8094 |
| DOI | 10.12133/j.smartag.SA202312001 |
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| Abstract | [目的/意义]随着自动化、数智化技术的快速发展及其相关技术在肉牛养殖上的逐步推广利用，肉牛智能化养殖技术研究也取得了一定进步。肉牛的生理指标如运动量、体温、心率、呼吸频率，以及反刍量等变化反映了肉牛的健康或亚健康状态。基于多种传感器采集到的数据以及机器学习、数据挖掘及模型化分析等技术的利用，肉牛的生理指标可由智能感知装备尤其接触式设备自动获取并用于发情、产犊、健康和应激的监测。[进展]针对肉牛养殖过程生理指标的智能监测技术及其利用价值进行了系统分析，分析了生理指标监测技术在实际生产中的应用现状，总结了肉牛生理指标监测的难点和挑战，并提出了未来发展方向。[结论/展望]肉牛生理指标的智能监测与利用既提高数据采集的时效性和准确性，有利于提高一线人员工作效率，促进肉牛养殖的智能化水平及健康养殖水平。结合当前中国肉牛实际饲养现状和肉牛生理指标智能监测传感器的研究现状，未来需降低接触类相关设备能耗、提高使用寿命；提高各监测数据的相互融合深度分析，提高监测准确率；加强非接触、高精度、自动化的数据采集分析技术研发，减少人工佩戴设备的工作量和设备使用成本。 |
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| AbstractList | [目的/意义]随着自动化、数智化技术的快速发展及其相关技术在肉牛养殖上的逐步推广利用，肉牛智能化养殖技术研究也取得了一定进步。肉牛的生理指标如运动量、体温、心率、呼吸频率，以及反刍量等变化反映了肉牛的健康或亚健康状态。基于多种传感器采集到的数据以及机器学习、数据挖掘及模型化分析等技术的利用，肉牛的生理指标可由智能感知装备尤其接触式设备自动获取并用于发情、产犊、健康和应激的监测。[进展]针对肉牛养殖过程生理指标的智能监测技术及其利用价值进行了系统分析，分析了生理指标监测技术在实际生产中的应用现状，总结了肉牛生理指标监测的难点和挑战，并提出了未来发展方向。[结论/展望]肉牛生理指标的智能监测与利用既提高数据采集的时效性和准确性，有利于提高一线人员工作效率，促进肉牛养殖的智能化水平及健康养殖水平。结合当前中国肉牛实际饲养现状和肉牛生理指标智能监测传感器的研究现状，未来需降低接触类相关设备能耗、提高使用寿命；提高各监测数据的相互融合深度分析，提高监测准确率；加强非接触、高精度、自动化的数据采集分析技术研发，减少人工佩戴设备的工作量和设备使用成本。 TP315%F326.3; [目的/意义]随着自动化、数智化技术的快速发展及其相关技术在肉牛养殖上的逐步推广利用,肉牛智能化养殖技术研究也取得了一定进步.肉牛的生理指标如运动量、体温、心率、呼吸频率,以及反刍量等变化反映了肉牛的健康或亚健康状态.基于多种传感器采集到的数据以及机器学习、数据挖掘及模型化分析等技术的利用,肉牛的生理指标可由智能感知装备尤其接触式设备自动获取并用于发情、产犊、健康和应激的监测.[进展]针对肉牛养殖过程生理指标的智能监测技术及其利用价值进行了系统分析,分析了生理指标监测技术在实际生产中的应用现状,总结了肉牛生理指标监测的难点和挑战,并提出了未来发展方向.[结论/展望]肉牛生理指标的智能监测与利用既提高数据采集的时效性和准确性,有利于提高一线人员工作效率,促进肉牛养殖的智能化水平及健康养殖水平.结合当前中国肉牛实际饲养现状和肉牛生理指标智能监测传感器的研究现状,未来需降低接触类相关设备能耗、提高使用寿命;提高各监测数据的相互融合深度分析,提高监测准确率;加强非接触、高精度、自动化的数据采集分析技术研发,减少人工佩戴设备的工作量和设备使用成本. |
| Abstract_FL | [Significance]The beef cattle industry plays a pivotal role in the development of China's agricultural economy and the enhancement of people's dietary structure.However,there exists a substantial disparity in feeding management practices and economic efficiency of beef cattle industry compared to developed countries.While the beef cattle industry in China is progressing towards intensive,mod-ern,and large-scale development,it encounters challenges such as labor shortage and rising labor costs that seriously affect its healthy development.The determination of animal physiological indicators plays an important role in monitoring animal welfare and health status.Therefore,leveraging data collected from various sensors as well as technologies like machine learning,data mining,and mod-eling analysis enables automatic acquisition of meaningful information on beef cattle physiological indicators for intelligent manage-ment of beef cattle.In this paper,the intelligent monitoring technology of physiological indicators in beef cattle breeding process and its application value are systematically summarized,and the existing challenges and future prospects of intelligent beef cattle breeding process in China are prospected.
[Progress]The methods of obtaining information on beef cattle physiological indicators include contact sensors worn on the body and non-contact sensors based on various image acquisitions.Monitoring the exercise behavior of beef cattle plays a crucial role in disease prevention,reproduction monitoring,and status assessment.The three-axis accelerometer sensor,which tracks the amount of time that beef cattle spend on lying,walking,and standing,is a widely used technique for tracking the movement behavior of beef cattle.Through machine vision analysis,individual recognition of beef cattle and identification of standing,lying down,and straddling move-ments can also be achieved,with the characteristics of non-contact,stress-free,low cost,and generating high data volume.Body tem-perature in beef cattle is associated with estrus,calving,and overall health.Sensors for monitoring body temperature include rumen temperature sensors and rectal temperature sensors,but there are issues with their inconvenience.Infrared temperature measurement technology can be utilized to detect beef cattle with abnormal temperatures by monitoring eye and ear root temperatures,although the accuracy of the results may be influenced by environmental temperature and monitoring distance,necessitating calibration.Heart rate and respiratory rate in beef cattle are linked to animal diseases,stress,and pest attacks.Monitoring heart rate can be accomplished through photoelectric volume pulse wave measurement and monitoring changes in arterial blood flow using infrared emitters and re-ceivers.Respiratory rate monitoring can be achieved by identifying different nostril temperatures during inhalation and exhalation us-ing thermal infrared imaging technology.The ruminating behavior of beef cattle is associated with health and feed nutrition.Currently,the primary tools used to detect rumination behavior are pressure sensors and three-axis accelerometer sensors positioned at various head positions.Rumen acidosis is a major disease in the rapid fattening process of beef cattle,however,due to limitations in battery life and electrode usage,real-time pH monitoring sensors placed in the rumen are still not widely utilized.Changes in animal physiolo-gy,growth,and health can result in alterations in specific components within body fluids.Therefore,monitoring body fluids or sur-rounding gases through biosensors can be employed to monitor the physiological status of beef cattle.By processing and analyzing the physiological information of beef cattle,indicators such as estrus,calving,feeding,drinking,health conditions,and stress levels can be monitored.This will contribute to the intelligent development of the beef cattle industry and enhance management efficiency.While there has been some progress made in developing technology for monitoring physiological indicators of beef cattle,there are still some challenges that need to be addressed.Contact sensors consume more energy which affects their lifespan.Various sensors are susceptible to environmental interference which affects measurement accuracy.Additionally,due to a wide variety of beef cattle breeds,it is difficult to establish a model database for monitoring physiological indicators under different feeding conditions,breeding stages,and breeds.Furthermore,the installation cost of various intelligent monitoring devices is relatively high,which also limits its utilization coverage.
[Conclusion and Prospects]The application of intelligent monitoring technology for beef cattle physiological indicators is highly signif-icance in enhancing the management level of beef cattle feeding.Intelligent monitoring systems and devices are utilized to acquire physiological behavior data,which are then analyzed using corresponding data models or classified through deep learning techniques to promptly monitor subtle changes in physiological indicators.This enables timely detection of sick,estrus,and calving cattle,facili-tating prompt measures by production managers,reducing personnel workload,and improving efficiency.The future development of physiological indicators monitoring technologies in beef cattle primarily focuses on the following three aspects:(1)Enhancing the lifespan of contact sensors by reducing energy consumption,decreasing data transmission frequency,and improving battery life.(2)Integrating and analyzing various monitoring data from multiple perspectives to enhance the accuracy and utility value.(3)Strengthening research on non-contact,high-precision and automated analysis technologies to promote the precise and intelligent development within the beef cattle industry. |
| Author | 周梦婷 熊本海 杨振刚 冯文晓 刘民泽 唐湘方 张帆 |
| AuthorAffiliation | 中国农业科学院 北京畜牧兽医研究所,畜禽营养与饲养全国重点实验室,北京 100193,中国%阳信亿利源清真肉类有限公司,山东滨州 251800,中国%北京首农畜牧发展有限公司,北京 102600,中国 |
| AuthorAffiliation_xml | – name: 中国农业科学院 北京畜牧兽医研究所,畜禽营养与饲养全国重点实验室,北京 100193,中国%阳信亿利源清真肉类有限公司,山东滨州 251800,中国%北京首农畜牧发展有限公司,北京 102600,中国 |
| Author_FL | FENG Wenxiao LIU Minze ZHANG Fan YANG Zhengang TANG Xiangfang XIONG Benhai ZHOU Mengting |
| Author_FL_xml | – sequence: 1 fullname: ZHANG Fan – sequence: 2 fullname: ZHOU Mengting – sequence: 3 fullname: XIONG Benhai – sequence: 4 fullname: YANG Zhengang – sequence: 5 fullname: LIU Minze – sequence: 6 fullname: FENG Wenxiao – sequence: 7 fullname: TANG Xiangfang |
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| Keywords | 人工智能 数据融合 传感器 智能监测 肉牛生理指标 data fusion beef cattle physiological indicator intelligent monitoring sensor artificial intelligence |
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| Title | 肉牛生理指标智能监测技术研究进展与展望 |
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