Shao Qian-Qian, Xiao Ping, Zhang Xia, Guo Sheng, Duan Jin-Ao
Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Key Laboratory of Chinese Medicinal Resources Recycling Utilization, National Administration of Traditional Chinese Medicine, Nanjing University of Chinese Medicine Nanjing 210023, China College of Artificial Intelligence and Information Technology, Nanjing University of Chinese Medicine Nanjing 210023, China.
Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Key Laboratory of Chinese Medicinal Resources Recycling Utilization, National Administration of Traditional Chinese Medicine, Nanjing University of Chinese Medicine Nanjing 210023, China.
Zhongguo Zhong Yao Za Zhi. 2024 Jan;49(2):344-353. doi: 10.19540/j.cnki.cjcmm.20230905.102.
In the context of the "antibiotic ban" era, the feed conversion of medicinal and edible traditional Chinese medicine(TCM) resources is a research hotspot in the field of antibiotic alternatives development. How to develop feed products that are beneficial to agriculture and livestock while ensuring nutrient balance and precision using medicinal and edible TCM resources as raw materials has become a challenge. Artificial intelligence(AI) technology has unique advantages in feed production and improving the efficiency of intelligent breeding. If AI technology is applied to the feed development of medicinal and edible TCM resources, it is possible to realize feeding and antibiotic-replacement value while ensuring precise nutrition. In order to better apply AI technology in the field of feed development of medicinal and edible TCM resources, this article used CiteSpace software to carry out literature visualization analysis and found that AI technology had a good application in the field of feed formulation optimization in recent years. However, there is still a gap in the research on the intelligent utilization of medicinal and edible TCM resources. Nonetheless, it is feasible for AI technology to be applied to the feed conversion of medicinal and edible TCM resources. Therefore, this article proposed for the first time an intelligent formulation system framework for feed materials derived from medicinal and edible TCM resources to provide new ideas for research in the field of feed development of medicinal and edible TCM resources and the research on the development of antibiotic alternatives. At the same time, it can pave the way for a new green industry chain for contemporary animal husbandry and the TCM industry.
在“禁抗”时代背景下,药食同源的中药资源饲料化是抗生素替代物开发领域的研究热点。如何以药食同源的中药资源为原料,开发出有利于农牧养殖且保证营养均衡与精准的饲料产品成为一项挑战。人工智能(AI)技术在饲料生产及提高智能养殖效率方面具有独特优势。若将AI技术应用于药食同源中药资源的饲料开发,有可能在保证精准营养的同时实现饲喂及抗生素替代价值。为更好地将AI技术应用于药食同源中药资源饲料开发领域,本文运用CiteSpace软件进行文献可视化分析,发现近年来AI技术在饲料配方优化领域有良好应用。然而,在药食同源中药资源智能利用方面的研究仍存在差距。尽管如此,AI技术应用于药食同源中药资源饲料化是可行的。因此,本文首次提出药食同源中药资源饲料原料智能配方系统框架,为药食同源中药资源饲料开发领域及抗生素替代物开发研究提供新思路。同时,可为当代畜牧产业与中药产业新的绿色产业链铺就道路。