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利用多元素稳定同位素特征对未加工棉花进行地理来源的鉴别。

Discrimination of unprocessed cotton on the basis of geographic origin using multi-element stable isotope signatures.

机构信息

Stable Isotope Laboratory, James Hutton Institute, Invergowrie, Dundee, DD2 5DA, UK; Environmental and Forensic Science Research Group, Robert Gordon University, Aberdeen, AB10 7GJ, UK.

出版信息

Rapid Commun Mass Spectrom. 2014 Mar 15;28(5):545-52. doi: 10.1002/rcm.6811.

Abstract

RATIONALE

Cotton is the most commonly used natural plant product for the manufacture of yarns and textiles. Consumer perception regarding differences in textile quality in relation to geographic provenance of cotton as well as stringent product labelling requirements demand for the supply chain to furnish proof of geographic provenance beyond merely paper-based audit trails.

METHODS

We have applied isotope ratio mass spectrometry to generate multivariate data sets of raw cotton. A two-point equilibration process with water at ambient temperature was used to account for hydrogen exchange between free hydroxyl groups in the cellulose lattice at ambient humidity, prior to hydrogen isotope analysis.

RESULTS

The molar fraction of exchangeable hydrogen in cotton at ambient temperature was found to be 0.046, which is in good agreement with the expected exchange fraction of 0.05. Hierarchical cluster analysis of multivariate stable isotope abundance data from 17 US cotton and 15 non-US cotton samples was able to cluster 15 of the 17 US cotton samples in one group.

CONCLUSIONS

Hierarchical cluster analysis of multivariate stable isotope signatures of raw cotton showed great promise as an analytical tool to differentiate between US and non-US cotton and possibly even to be able to group unprocessed cotton according to geographic origin.

摘要

原理

棉花是最常用于制造纱线和纺织品的天然植物产品。消费者对与棉花地理来源相关的纺织品质量差异的认知,以及严格的产品标签要求,都要求供应链提供除基于纸张的审计跟踪之外的地理来源证明。

方法

我们已经应用同位素比质谱生成了原棉的多变量数据集。在进行氢同位素分析之前,采用在环境温度下用水分两步平衡的方法,以考虑纤维素晶格中游离羟基基团在环境湿度下的氢交换。

结果

发现环境温度下棉花中可交换氢的摩尔分数为 0.046,与预期的 0.05 交换分数非常吻合。对来自 17 个美国棉花和 15 个非美国棉花样本的多变量稳定同位素丰度数据进行层次聚类分析,能够将 17 个美国棉花样本中的 15 个聚类到一组。

结论

原棉多变量稳定同位素特征的层次聚类分析显示出作为一种区分美国和非美国棉花的分析工具的巨大潜力,甚至有可能根据地理来源对未加工棉花进行分组。

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