人类学学报 ›› 2021, Vol. 40 ›› Issue (03): 535-545.doi: 10.16359/j.1000-3193/AAS.2021.0051cstr: 32091.14.j.1000-3193/AAS.2021.0051

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中国有机残留物分析的研究进展及展望

杨益民()   

  1. 中国科学院大学人文学院考古学与人类学系,北京,100049
  • 收稿日期:2020-12-13 修回日期:2021-03-23 出版日期:2021-06-15 发布日期:2021-06-24
  • 作者简介:杨益民(1977-),男,博士,教授,研究方向为科技考古。E-mail: yiminyang@ucas.ac.cn
  • 基金资助:
    教育部人文社会科学研究规划基金项目(17YJAZH107);中组部青年拔尖人才计划和中国科学院青年创新促进会

The research progress and prospect of organic residue analysis in China

YANG Yimin()   

  1. Department of archaeology and anthropology, University of Chinese Academy of Sciences, Beijing 100049
  • Received:2020-12-13 Revised:2021-03-23 Online:2021-06-15 Published:2021-06-24

摘要:

有机残留物分析,是指从残留物载体中提取有机分子,利用科技检测手段进行定性、定量分析,判断有机残留物的生物来源,从而了解古代动植物的加工、利用和相关载体的功能等。中国有机残留物分析工作已开展40余年,取得了很多进展,但仍需要更多重视。本文首先回顾了中国考古遗存研究中有机残留物分析的发展历程,然后梳理了动物制品、粮食作物制品、经济作物制品、器物内炭化物和有机宝石等方面的研究进展;研究成果主要涉及生物标记物、脂质和蛋白质等三类有机分子,并少量涉及淀粉粒、植硅体等植物微体化石方面的突破性工作。最后,对未来的研究动向进行了展望。

关键词: 科技考古, 动植物利用, 有机残留物分析, 生物标记物, 脂质分析, 蛋白质组

Abstract:

Organic residue analysis refers to extract and identify organic molecules from their carriers, and explore the biological origins of organic residue in order to understand the processing and exploitation of ancient animals and plants by ancient humans, as well as the function of corresponding carriers. Organic residue analysis has been practiced over forty years in China, and many advances have been achieved, but still needs more attention. This paper mainly reviews the development history of organic residue analysis in China archaeology, and then summarizes the research progress associated with animal products, cereal crop products, economic crop products, carbonized materials in vessels and organic gemstones. These studies mainly involve the use of biomarkers, lipids and proteins, also a few breakthroughs of plant microfossils including starch grains and phytolith analysis. Finally, the prospect of organic residue analysis in China is outlined.

Key words: Archaeometry, Exploitation of animals and plants, Organic residue analysis, Biomarkers, Lipid analysis, Proteomics

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