|
|
|
|
|
|
Study on Chemical Composition and Provenience Differentiation of Turquoises Excavated from Two Sites in Xinjing |
XIAN Yi-heng1,2, LI Xin-tong1,2, ZHOU Xue-qi3, MA Jian1, LI Yan-xiang4, WEN Rui1,2 |
1. Key Laboratory of Cultural Heritage Conservation and Research, Ministry of Education,Northwest University, Xi’an 710069, China
2. Scientific and Archaeological Research Center, Northwest University, Xi’an 710069, China
3. School of Archaeology and Museology, Peking University, Beijing 100871, China
4. Institute of Metallurgy and Materials History, University Science and Technology Beijing, Beijing 100083, China |
|
|
Abstract Study on geological provenience of turquoise can reveal a lot about ancient trade, organization of resources and cultural exchanges, thus the origin of turquoise artifacts excavated from Xinjiang has been a hot issue in archaeometry in recent years. At present, there are three major academic hypotheses on the provenience of turquoise objects found in Xinjiang: Central Plains, Xinjiang or Persia. In order to determine the provenience of turquoise excavated from Jiayi and Xigou sites, two cemeteries in the eastern part of Xinjiang have been chosen, and we examined the turquoise samples using LA-ICP-AES to analyze the chemical composition and PCA to compare the results with samples from five regions in the eastern Qinling Mountains (Central Plains). The results of the composition analysis of the objects from these two sites have shown that five of the Jiayi site samples are rare zinc turquoise, while the other samples are similar to those turquoise samples of the Xigou site and contain relatively high level of Fe and Sr. Based on the comparative analysis of the turquoise composition data between these two sites and samples from the Qinling Mountains, it was suggested that the trace elements of turquoise artifacts from Jiayi and Xigou sites are not similar to the turquoise samples in the Central Plains, different in view of higher level of B2O (Wt%) and lower level of BaO (wt%). According to the provenience differentiation model, the samples from these two sites have formed a cluster and are clearly distinguished from the distribution areas of Qinling Mountains. Hence, it can be concluded that the composition of the turquoise artifacts excavated from Jiayi and Xigou sites is different from the minerals of Qinling, Mountains in Central Plains. Based on the discovery of the ancient turquoise mining site in Hami, Xinjiang, the turquoise artifacts found in Jiayi and Xigou sites are barely likely to be from Central Plains.
|
Received: 2019-05-19
Accepted: 2019-09-11
|
|
|
[1] Henan Provincial Cultural Relics Archaeological Research Institute(河南省文物考古研究所). Wu Yang Site(舞阳贾湖). Beijing: Science Press(北京: 科学出版社), 1999.
[2] XU Liang-gao, ZHAO Chun-yan(徐良高,赵春燕). The Three Generation of Archaeology(三代考古), 2011, (00): 497.
[3] CUI Jian-feng,HE Chuan-kun, LIU Ke-hong, et al(崔剑锋,何传坤,刘克竑,等). Relics from South(南方文物), 2008, (4): 109.
[4] ZHANG Bei-li(张蓓莉). Systematic Gemmology(系统宝石学). Beijing:The Geological Publishing House(北京: 地质出版社), 2010.
[5] Maskelyne N S. Nature, 1878, 18: 426.
[6] HAN Zhao-xin, LUAN Li-jun, WANG Chao-you(韩照信,栾丽君,王朝友). Journal of Earth Science and Enivronmental(地球科学与环境学报), 2004, (2):24.
[7] CHEN Quan-li, LIU Xian-yu,JIN Wen-jing, et al(陈全莉,刘衔宇,金文靖,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2018, 38(10): 3084.
[8] WU Dian-ting, WU Di(吴殿廷, 吴 迪). Mathematics in Practice and Theory(数学的实践与认识), 2015, 20: 143. |
[1] |
WANG Cai-ling1,ZHANG Jing1,WANG Hong-wei2*, SONG Xiao-nan1, JI Tong3. A Hyperspectral Image Classification Model Based on Band Clustering and Multi-Scale Structure Feature Fusion[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 258-265. |
[2] |
HU Cai-ping1, HE Cheng-yu2, KONG Li-wei3, ZHU You-you3*, WU Bin4, ZHOU Hao-xiang3, SUN Jun2. Identification of Tea Based on Near-Infrared Spectra and Fuzzy Linear Discriminant QR Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3802-3805. |
[3] |
LUO Li, WANG Jing-yi, XU Zhao-jun, NA Bin*. Geographic Origin Discrimination of Wood Using NIR Spectroscopy
Combined With Machine Learning Techniques[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3372-3379. |
[4] |
FANG Zheng, WANG Han-bo. Measurement of Plastic Film Thickness Based on X-Ray Absorption
Spectrometry[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3461-3468. |
[5] |
HUANG Zhao-di1, CHEN Zai-liang2, WANG Chen3, TIAN Peng2, ZHANG Hai-liang2, XIE Chao-yong2*, LIU Xue-mei4*. Comparing Different Multivariate Calibration Methods Analyses for Measurement of Soil Properties Using Visible and Short Wave-Near
Infrared Spectroscopy Combined With Machine Learning Algorithms[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3535-3540. |
[6] |
JIA Zong-chao1, WANG Zi-jian1, LI Xue-ying1, 2*, QIU Hui-min1, HOU Guang-li1, FAN Ping-ping1*. Marine Sediment Particle Size Classification Based on the Fusion of
Principal Component Analysis and Continuous Projection Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3075-3080. |
[7] |
CHEN Jia-wei1, 2, ZHOU De-qiang1, 2*, CUI Chen-hao3, REN Zhi-jun1, ZUO Wen-juan1. Prediction Model of Farinograph Characteristics of Wheat Flour Based on Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3089-3097. |
[8] |
XUE Fang-jia, YU Jie*, YIN Hang, XIA Qi-yu, SHI Jie-gen, HOU Di-bo, HUANG Ping-jie, ZHANG Guang-xin. A Time Series Double Threshold Method for Pollution Events Detection in Drinking Water Using Three-Dimensional Fluorescence Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3081-3088. |
[9] |
LIU Hong-wei1, FU Liang2*, CHEN Lin3. Analysis of Heavy Metal Elements in Palm Oil Using MP-AES Based on Extraction Induced by Emulsion Breaking[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3111-3116. |
[10] |
JIA Hao1, 3, 4, ZHANG Wei-fang1, 3, LEI Jing-wei1, 3*, LI Ying-ying1, 3, YANG Chun-jing2, 3*, XIE Cai-xia1, 3, GONG Hai-yan1, 3, DING Xin-yu1, YAO Tian-yi1. Study on Infrared Fingerprint of the Classical Famous
Prescription Yiguanjian[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3202-3210. |
[11] |
CAO Qian, MA Xiang-cai, BAI Chun-yan, SU Na, CUI Qing-bin. Research on Multispectral Dimension Reduction Method Based on Weight Function Composed of Spectral Color Difference[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2679-2686. |
[12] |
XU Ya-fen1, LIU Xian-yu1*, CHEN Quan-li2, XU Chang3. Study on Mineral Composition and Spectral Characteristics of “Middle East Turquoise”[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2862-2867. |
[13] |
JIA Yu-ge1, YANG Ming-xing1, 2*, YOU Bo-ya1, YU Ke-ye1. Gemological and Spectroscopic Identification Characteristics of Frozen Jelly-Filled Turquoise and Its Raw Material[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2974-2982. |
[14] |
ZHANG Zi-hao1, GUO Fei3, 4, WU Kun-ze1, YANG Xin-yu2, XU Zhen1*. Performance Evaluation of the Deep Forest 2021 (DF21) Model in
Retrieving Soil Cadmium Concentration Using Hyperspectral Data[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2638-2643. |
[15] |
CHEN Wan-jun1, XU Yuan-jie2, LU Zhi-yun3, QI Jin-hua3, WANG Yi-zhi1*. Discriminating Leaf Litters of Six Dominant Tree Species in the Mts. Ailaoshan Based on Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2119-2123. |
|
|
|
|