Non-invasive study of natural dyes in textiles of the Qing Dynasty using fiber optic reflectance spectroscopy

Ding, Li; Gong, Tianyi; Wang, Bo; Qin, Yang; Liu, Wei; Pemo, Rigzin; Metok, Tsokyi

doi:10.1016/j.culher.2020.10.013

Cited by 22 publications

(13 citation statements)

References 46 publications

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“…Based on error rate values in cross-validation (Fig. SI1), we used 10 PCs for both PCA-LDA (error rate 0%) model of the single fibres dataset and 20 PCs for the model including the [43] 6658 1502 O-H from adsorbed water and aminoacids, 1st overtone of N-H [30,44] 6831 1464 1st overtone of N-H, 3rd overtone of C=O [30] 7133 1402 1stovertone of O-H stretching vibration of water [45] 8410 1189 3rd overtone C-H [45] Silk 6345 1576 Amide groups in β-sheet, O-H and N-H overtones and combination bands [8,26] 6506 1537 1st overtone amide A stretching N-H amorphous [23,27] 6658 1502 N-H stretching from Amide A crystalline and 1st overtone stretching Amide II. Amide groups in β-sheet [26,27] 7153 1398 1stovertone of O-H stretching vibration of water [45] 8292 1206 3rd overtone C-H [45] Cotton 8190 1221 2nd overtone C-H stretching CH and CH 2 from cellulose [46,47] 7962 1256 2nd overtone C-H stretching CH and CH 2 from cellulose [46,47] 6729 1486 1st overtone OH stretching from semi-crystalline cellulose [46,47] fibre blends (error rate 5.29%).…”

Section: Evaluation Of Classification Techniquesmentioning

confidence: 99%

“…On the other hand, non-invasive methods such as external reflection FTIR and handheld portable NIR spectrometry-based on miniaturized technology that may impact on the instrumental performance (e.g. noisier detectors and lower spectral resolution) [17]-proved suitable for the identification of fibres without sampling [18][19][20][21] as well as fibre optics reflectance spectroscopy (FORS) in the NIR region [22,23]. The latter relies on the use of optic fibres to carry the reflected light (UV, Vis, and NIR), and generally employ better performance components (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Non-invasive identification of textile fibres using near-infrared fibre optics reflectance spectroscopy and multivariate classification techniques

et al. 2022

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The identification of textile fibres from cultural property provides information about the object's technology. Today, microscopic examination remains the preferred method, and molecular spectroscopies (e.g. Fourier transform infrared (FTIR) and Raman spectroscopies) can complement it but may present some limitations. To avoid sampling, non-invasive fibre optics reflectance spectroscopy (FORS) in the near-infrared (NIR) range showed promising results for identifying textile fibres; but examining and interpreting numerous spectra with features that are not well defined is highly time-consuming. Multivariate classification techniques may overcome this problem and have already shown promising results for classifying textile fibres for the textile industry but have been seldom used in the heritage science field. In this work, we compare the performance of two classification techniques, principal component analysis–linear discrimination analysis (PCA-LDA) and soft independent modelling of class analogy (SIMCA), to identify cotton, wool, and silk fibres, and their mixtures in historical textiles using FORS in the NIR range (1000–1700 nm). We built our models analysing reference samples of single fibres and their mixtures, and after the model calculation and evaluation, we studied four historical textiles: three Persian carpets from the nineteenth and twentieth centuries and an Italian seventeenth-century tapestry. We cross-checked the results with Raman spectroscopy. The results highlight the advantages and disadvantages of both techniques for the non-invasive identification of the three fibre types in historical textiles and the influence their vicinity can have in the classification.

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Section: Evaluation Of Classification Techniquesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Non-invasive identification of textile fibres using near-infrared fibre optics reflectance spectroscopy and multivariate classification techniques

et al. 2022

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“…Therefore, developing a non-destructive approach to studying Norwich textiles is expected to be extended to understanding fabrics of similar substrate and age; and to extending the approach to other textiles and dyed substrates (e.g., paper). Typical use of FORS in the literature identi es dyes in textiles via manual interpretation, 18, [23][24][25][26][27][28][29] with only a handful of works employing multivariate analyses. [30][31][32][33] The present work builds on the limited body of multivariate analysis of FORS spectra by rst, signi cantly increasing dataset size; second, expanding analysis to identifying spectral regions that correspond to multivariate clustering; and lastly, validating these ndings with selected HPLC-MS analyses.…”

Section: Introductionmentioning

confidence: 99%

“…Further analysis is underway to discern whether this observation should be attributed to the HPLC validation set being small, or to speci c chromophore bands in FORS, as many reports have suggested. 18,22,23,25,[33][34][35][36][37] Experimental…”

Section: Introductionmentioning

confidence: 99%

Identification of Historical Textiles via Non-destructive Spectroscopic Analysis and Multivariate Cluster Analysis

Celani

Degano

Chen

et al. 2023

Preprint

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One of the foremost challenges facing dye analysis of historical textiles is that the gold standard technique – high performance liquid chromatography (HPLC) – is inherently destructive, costly, and relatively few institutions have the necessary equipment and expertise. This is especially problematic considering historical samples are unique, sampling is undesirable, and historical textiles can be exceptionally fragile. One proposed solution to this is the implementation of non-destructive, spectroscopic, techniques, such as Fiber Optic Reflectance Spectroscopy (FORS). In this work, 204 well-provenanced red Norwich textiles were measured with FORS and analyzed, aiming to test if the technique would be able to discern the chromophore combinations / recipes used to dye historical textiles. Cluster analysis algorithms and spectroscopic domain knowledge were coupled with selective HPLC validation to assess overall ability of FORS to identify chromophore combinations. The UV/VIS region, particularly 380-469 nm, showed a narrow visible region that was primarily responsible for clustering behavior that correlates with HPLC-validated samples. In contrast, the near infrared (NIR) region of the spectrum contained little meaningful information in multivariate space. This indicates that FORS shows promise for identifying chromophores in textile samples. Suspecting the observed spectral inflection point shift around 600 nm was correlated to the presence of mordants, complementary X-ray fluorescence (XRF) analysis was used, with the corresponding statistical treatment, which showed no correlation. From this work, three main conclusions can be drawn: 1) FORS adequately identifies visual information, which shows reasonable correlation to HPLC-validated dye recipes, warranting further investigation, and indicating utility for confirmatory analysis, and strongly suggesting this is a good tool for persons with visual impairments; 2) XRF analysis confirms that ~600 nm inflection point shift and mordant are not correlated when measuring dyed textiles; 3) many documented structural-to-spectral relationships established in the conservation literature are too weak in dyed textiles for statistical analysis and, by extension, expert spectral identification.

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“…In this study, we demonstrate that it is possible to obtain comparable analytical results on madder-dyed woolen threads between liquid chromatography analysis and reflectance measurements. While a number of studies have focused on the development of FORS for the identification of madder, regardless of species − or considering only alizarin and purpurin,, very little attention has been devoted to the analysis of other anthraquinones present in natural products. This is due to the fact that these compounds are not easy to acquire, as some are unstable, not produced commercially, or too expensive to synthesize.…”

Section: Introductionmentioning

confidence: 99%

Noninvasive Characterization and Quantification of Anthraquinones in Dyed Woolen Threads by Visible Diffuse Reflectance Spectroscopy

et al. 2022

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The anthraquinone components of the roots of various species of madder (like Rubia tinctorum L. and Rubia peregrina L.) have been used for millennia as red colorants in textiles, carpets, tapestries, and other objects. To understand the selection and preparation of dyestuffs in various cultures and historical periods, these dyes (mainly alizarin and purpurin) are traditionally analyzed by means of separation methods that require sampling. This contribution focuses on establishing a fast, noninvasive, and in situ analytical procedure based on visible reflectance spectroscopy for the characterization and quantification of anthraquinones in ancient wool yarns. The method was successfully applied to Coptic textiles, and the analytical results are in agreement with prior observations obtained on samples by separation techniques.

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Non-invasive study of natural dyes in textiles of the Qing Dynasty using fiber optic reflectance spectroscopy

Cited by 22 publications

References 46 publications

Non-invasive identification of textile fibres using near-infrared fibre optics reflectance spectroscopy and multivariate classification techniques

Non-invasive identification of textile fibres using near-infrared fibre optics reflectance spectroscopy and multivariate classification techniques

Identification of Historical Textiles via Non-destructive Spectroscopic Analysis and Multivariate Cluster Analysis

Noninvasive Characterization and Quantification of Anthraquinones in Dyed Woolen Threads by Visible Diffuse Reflectance Spectroscopy

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