.png){kind=icon}
返回
Technologies in cattle traceability: A bibliometric analysis
.png){kind=icon}
PRE
AI
DOI：10.1016/j.compag.2024.109459.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
It has been widely documented that livestock cattle can play a non-negligible role in natural landscapes due to climate change, deforestation, and enteric methane emissions. Alternatively, sustainable protocols and market digitalization are highlighted as promising tools to mitigate environmental cattle impacts by authenticated data in digital traceability systems. Digital inclusion, particularly for cattle breeders, can be a useful starting point for employing sustainable protocol in food chain production and management. This study analyzes the evolution of knowledge in the area of animal traceability to compare applied technologies found by a bibliometric analysis of articles published in Web of Science. The study evidences a clear change in thematic research over decades, currently culminating in technologies such as blockchain, IoT (Internet of Things), machine learning, and deep learning. These technologies emerge as the main research scopes in promoting transparency and reliability in the production chain, especially considering individual digital identification. However, challenges such as high investment requirements and difficulties in data accessibility, interoperability, privacy, and security implicate the low maturity level of available technologies and knowledge, therefore preventing further adoption and development of reliable worldwide animal traceability systems.
Keyword:
Agriculture 4.0
Beef Chain
Animal identification Tag
Technology adoption
Transparency
期刊
IF:
8.9
论文数:
1.0W
被引数:
4.8W
机构
引用论文
.png){kind=icon}
Intelligent perception for cattle monitoring: A review for cattle identification, body condition score evaluation, and weight estimation牛监测的智能感知: 牛识别，身体状况评分评估和体重估计的综述
OAAI
OAAI分享收藏分享收藏
分享收藏分享收藏
查看更多内容