A UPLC/ESI–MS method for identifying wool, cashmere and yak fibres

Vineis, Claudia; Tonetti, Cinzia; Paolella, Sara; Pozzo, PierDavide; Sforza, Stefano

doi:10.1177/0040517513512394

Cited by 21 publications

(7 citation statements)

References 7 publications

(7 reference statements)

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“…Chen and Wang used the NAOH solution to test the solubility of wool and cashmere fibers under different conditions, and quantitatively analyzed the difference between them by comparing the difference in alkali solution concentration [1]. Vineis et al proposed a UPLC/ESI-MS method for identifying wool and cashmere which was used to extract the enzymatic digestion of keratin and analyze the peptide, then the quantitative analysis and classification of fibers can be realized [2]. Tang proposed a method for fiber analysis based on mitochondrial DNA.…”

Section: Introductionmentioning

confidence: 99%

Identification of Extremely Similar Animal Fibers Based on Matched Filter and HOG-SVM

et al. 2019

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Identification of extremely similar animal fibers has always been one of the challenging research topics in the textile field. In this paper, an improved image-based recognition method was proposed for the identification of extremely similar animal fibers including cashmere and wool. A total of 100 groups of wool and 100 groups of cashmere fiber images were collected using the self-developed microscope image analysis system. The contrast of original fiber micro images usually was not high enough and some impurities always existed during the slicing process, so the matched filters were first applied for these images to extract the enhanced fiber binary texture, which only needs to set reasonable segment length and the threshold for different fiber images to eliminate impurities and background. Then, the high-dimensional texture features of the original color images, gray images, and the images processed by matched filter were extracted by calculating and analyzing the histogram of oriented gradient (HOG). The 200 sets of original color images, gray images, and processed images were divided into the training set and testing set according to different proportions, and the recognition expert system based on the support vector machine (SVM) could be trained and validated accordingly. The experimental results show that the recognition accuracy of the fiber images processed by matched filter was obviously improved compared with that of the other two data sets, and the recognition rate reaches the highest with 92.5%. It also proves that the proposed algorithm in this paper can classify and identify extremely similar wool and cashmere fibers more quickly and effectively compared with other texture feature extraction and identification algorithms. INDEX TERMS Extremely similar fibers, image identification, matched filter, HOG, SVM.

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Section: Introductionmentioning

confidence: 99%

Identification of Extremely Similar Animal Fibers Based on Matched Filter and HOG-SVM

et al. 2019

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“…Apart from qualitative proteomic mapping, quantitative comparison using the iTRAQ approach uncovered an interesting correlation of wool fiber quality parameters with expression changes of specific KAPs [ 19 , 21 ]. Therefore, it is conceivable that mass spectrometry analysis of species-related proteins or peptides would offer a rather promising solution to textile authentication, which was shown feasible in exploratory research by Sforza et al [ 11 , 22 ].…”

Section: Introductionmentioning

confidence: 99%

Combining Untargeted and Targeted Proteomic Strategies for Discrimination and Quantification of Cashmere Fibers

Zhang

Wang

et al. 2016

PLoS ONE

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Cashmere is regarded as a specialty and luxury fiber due to its scarcity and high economic value. For fiber quality assessment, it is technically very challenging to distinguish and quantify the cashmere fiber from yak or wool fibers because of their highly similar physical appearance and substantial protein sequence homology. To address this issue, we propose a workflow combining untargeted and targeted proteomics strategies for selecting, verifying and quantifying biomarkers for cashmere textile authentication. Untargeted proteomic surveys were first applied to identify 174, 157, and 156 proteins from cashmere, wool and yak fibers, respectively. After marker selection at different levels, peptides turned out to afford much higher selectivity than proteins for fiber species discrimination. Subsequently, parallel reaction monitoring (PRM) methods were developed for ten selected peptide markers. The PRM-based targeted analysis of peptide markers enabled accurate determination of fiber species and cashmere percentages in different fiber mixtures. Furthermore, collective use of these peptide makers allowed us to discriminate and quantify cashmere fibers in commercial finished fabrics that have undergone heavy chemical treatments. Cashmere proportion measurement in fabric samples using our proteomic approach was in good agreement with results from traditional light microscopy, yet our method can be more readily standardized to become an objective and robust assay for assessing authenticity of fibers and textiles. We anticipate that the proteomic strategies presented in our study could be further implicated in discovery of quality trait markers for other products containing highly homologous proteomes.

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“…A correspondence between the nomenclatures is provided in the Supplementary material Table S1. Proteomic analysis of hair, fur, and textiles was first conducted on modern samples to assess the quality of textile products (Hollemeyer et al, 2002;Hollemeyer and Heinzle, 2007;Clerens et al, 2010;Plowman et al, 2012;Paolella et al, 2013;Vineis et al, 2014;Li et al, 2016;Plowman et al, 2018). Analysis of ancient samples in order to characterise remains of Neolithic human hair and clothes (Hollemeyer et al, 2008(Hollemeyer et al, , 2012Fresnais et al, 2017) and for other, archaeozoological applications (Solazzo, 2017;Solazzo et al, 2017Solazzo et al, , 2014Solazzo et al, , 2013Solazzo et al, , 2011 has permitted researchers to refine taxonomic attributions, in some cases increasing knowledge of the fabrication of ancient textiles (Fresnais et al, 2017;Solazzo et al, 2011).…”

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confidence: 99%

Animal fibre use in the Keriya valley (Xinjiang, China) during the Bronze and Iron Ages: A proteomic approach

Azémard

Zazzo

Marie

et al. 2019

Journal of Archaeological Science

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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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A UPLC/ESI–MS method for identifying wool, cashmere and yak fibres

Cited by 21 publications

References 7 publications

Identification of Extremely Similar Animal Fibers Based on Matched Filter and HOG-SVM

Identification of Extremely Similar Animal Fibers Based on Matched Filter and HOG-SVM

Combining Untargeted and Targeted Proteomic Strategies for Discrimination and Quantification of Cashmere Fibers

Animal fibre use in the Keriya valley (Xinjiang, China) during the Bronze and Iron Ages: A proteomic approach

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