Article(id=1297139211384156225, tenantId=1146029695717560320, journalId=1296801528146919473, issueId=1297139203754709410, articleNumber=null, orderNo=null, doi=10.12377/1671-4393.26.06.04, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=null, receivedDateStr=null, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1787191687675, onlineDateStr=2026-08-20, pubDate=1782316800000, pubDateStr=2026-06-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1787191687675, onlineIssueDateStr=2026-08-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1787191687675, creator=13701087609, updateTime=1787191687675, updator=13701087609, issue=Issue{id=1297139203754709410, tenantId=1146029695717560320, journalId=1296801528146919473, year='2026', volume='', issue='6', pageStart='3', pageEnd='156', issueExtLink='null', onlineDate='null', pubDate='1782316800000', pubDateStr='2026-06-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1787191685856, creator='13701087609', updateTime=1787192210976, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1297141406343131394, tenantId=1146029695717560320, journalId=1296801528146919473, issueId=1297139203754709410, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1297141406343131395, tenantId=1146029695717560320, journalId=1296801528146919473, issueId=1297139203754709410, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=30, endPage=39, ext={EN=ArticleExt(id=1297139211686146114, articleId=1297139211384156225, tenantId=1146029695717560320, journalId=1296801528146919473, language=EN, title=Research Progress on Synergistic Regulation Technology of Nutrition, Health and Emission Reduction in Ruminants, columnId=1297139204610347427, journalTitle=China Dairy, columnName=RUMINANT NUTRITION AND HEALTH, runingTitle=null, highlight=null, articleAbstract=

Against the dual backdrop of global warming and China's strategy for revitalizing the dairy industry, ruminant production systems that balance high productivity, high efficiency and low carbon footprint have emerged as a core research topic for the sustainable development of the sector. Centered on the synergistic advancement of intelligent nutritional regulation and green emission reduction, this paper elaborates on the synergistic mechanisms linking ruminant nutrition, animal health and pollutant mitigation from three dimensions: nutritional metabolism, microecological interaction and stress regulation. It systematically reviews the current applications of smart technologies—including Internet of Things (IoT) sensors, big data and machine learning, and intelligent feeding equipment—in precision nutritional management, and analyzes the merits and inherent limitations of closed-loop management enabled by these technologies. This work further highlights technological innovations under the low-carbon breeding framework, such as the exploitation of novel feed resources, application of eco-friendly additives and formulation of low-emission diets, alongside their practical industrial performance. Four pivotal challenges prevailing in this field are identified: fragmented research on the synergistic nutrition-health-emission reduction mechanisms; poor scalability of smart breeding technologies; unsatisfactory economic viability and long-term stability of emission abatement techniques; and the absence of unified integrated evaluation criteria for the industry. To address the above bottlenecks, future research priorities and industrialization pathways are prospected, covering in-depth deployment of multi-omics technologies, development of low-cost intelligent facilities, establishment of differentiated technical frameworks for farms of varying scales, and construction of comprehensive emission assessment systems. This study intends to provide scientific evidence and theoretical support for the intelligent, healthy and green transformation of China's ruminant livestock industry.

, authors=Zepeng WU, Weijun WU^*, Songqun LI, Dongmei LI, Cunfei FAN, Kelong SUN, Qiping CHEN, Wanying ZHANG, Fan LIU, Siyi LIN, authorsList=Zepeng WU, Weijun WU, Songqun LI, Dongmei LI, Cunfei FAN, Kelong SUN, Qiping CHEN, Wanying ZHANG, Fan LIU, Siyi LIN, authorCompany=null, correspAuthors=Weijun WU, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1297139212092993603, articleId=1297139211384156225, tenantId=1146029695717560320, journalId=1296801528146919473, language=CN, title=反刍动物营养-健康-减排协同调控技术研究进展, columnId=1297139204757148069, journalTitle=中国乳业, columnName=反刍动物营养与健康养殖专题, runingTitle=null, highlight=null, articleAbstract=

在全球气候变暖及国内奶业振兴战略的双重背景下，兼顾高产高效与绿色低碳的反刍动物养殖模式，已成为行业可持续发展的核心研究课题。本文以智能营养调控与绿色减排协同发展为研究核心，从营养代谢、微生态互作、应激调控三个层面，深入阐释反刍动物营养、机体健康与污染物减排的协同作用机制。文章系统总结了物联网传感、大数据机器学习、智能饲喂设备等智慧技术在精准营养管控中的应用现状，剖析了相关技术闭环管理的优势与现存短板，并重点综述低碳养殖理念下的技术创新成果，涵盖新型饲料资源开发、环保添加剂施用、低排放日粮优化设计等内容，同时梳理了各类技术的产业落地应用成效。研究明确了当前领域存在四大核心问题：营养-健康-减排协同机理研究较为零散；智慧养殖技术规模化适配性不足；减排技术经济效益与长期稳定性欠佳；行业统一的一体化评价标准尚未完善。针对以上瓶颈，本文从多组学技术深化应用、低成本智能设备研发、差异化规模养殖技术体系构建、综合减排评价机制搭建等方面展望未来研究与产业化方向，旨在为我国反刍动物养殖业智能化、健康化、绿色化转型升级提供科学依据与理论支撑。

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吴泽鹏（1991-），男，广东揭阳人，本科，助理工程师，研究方向为食品质量安全

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吴泽鹏（1991-），男，广东揭阳人，本科，助理工程师，研究方向为食品质量安全

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李颂群（1977-），女，广东梅州人，本科，工程师，研究方向为乳品质量管控

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李颂群（1977-），女，广东梅州人，本科，工程师，研究方向为乳品质量管控

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李冬梅（1985-），女，福建漳州人，硕士，高级工程师，研究方向为乳制品质量管理和技术改进

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李冬梅（1985-），女，福建漳州人，硕士，高级工程师，研究方向为乳制品质量管理和技术改进

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范存斐（1986-），女，山西大同人，硕士，助理工程师，研究方向为乳品检测分析

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范存斐（1986-），女，山西大同人，硕士，助理工程师，研究方向为乳品检测分析

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孙克龙（1983-），男，黑龙江肇东人，本科，助理工程师，研究方向为食品质量安全

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孙克龙（1983-），男，黑龙江肇东人，本科，助理工程师，研究方向为食品质量安全

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