ACS Publications. Most Trusted. Most Cited. Most Read
Development and Use of an Attenuated Total Reflectance/Fourier Transform Infrared (ATR/FT-IR) Spectral Database To Identify Foreign Matter in Cotton
My Activity

Figure 1Loading Img
    Article

    Development and Use of an Attenuated Total Reflectance/Fourier Transform Infrared (ATR/FT-IR) Spectral Database To Identify Foreign Matter in Cotton
    Click to copy article linkArticle link copied!

    View Author Information
    Quality Assessment Research Unit, Richard B. Russell Research Center, Agricultural Research Service, U.S. Department of Agriculture, P.O. Box 5677, Athens, Georgia 30605-5677; Hewlett-Packard Company, MS711A, 1000 N.E. Circle Boulevard, Corvallis, Oregon 97330; and Cotton Quality Research Laboratory, Agricultural Research Service, U.S. Department of Agriculture, Clemson, South Carolina 29631
    Other Access Options

    Journal of Agricultural and Food Chemistry

    Cite this: J. Agric. Food Chem. 2006, 54, 20, 7405–7412
    Click to copy citationCitation copied!
    https://doi.org/10.1021/jf052949g
    Published September 9, 2006
    Copyright © 2006 American Chemical Society

    Abstract

    Click to copy section linkSection link copied!

    The presence of foreign matter in cotton seriously affects the cotton grade and thus the price per bale paid by the spinner to the grower, the efficiency of the spinning and ginning operations, and the quality of the final woven product. Rapid identification of the nature of the extraneous matter in cotton at each stage of cleaning and processing is necessary to permit actions to eliminate or reduce its presence and improve efficiency and quality. Although several instruments are being successfully employed for the measurement of contamination in cotton fibers based on particle size/weight, no commercial instrument is capable of accurate qualitative identification of contaminants. To this end, ATR/FT-IR spectra of retrieved foreign matter were collected and subsequently rapidly matched to an authentic spectrum in a spectral database. The database includes contaminants typically classified as “trash”, cotton plant parts (hull, shale, seed-coat fragments, bract, cacyx, leaf, bark, sticks, and stems) and grass plant parts (leaf and stem); “foreign objects and materials”, synthetic materials (plastic bags, film, rubber, bale wrapping and strapping); organic materials (other fibers, yarns, paper, feathers, and leather); plus entomological and physiological sugars and inorganic materials (sand and rust). The spectral matching resulted in consistently high-score identification of the foreign matter based on chemical composition, irrespective of its particle size. The method is envisioned to be employed with stand-alone rugged infrared instrumentation to provide specific identification of extraneous materials in cotton as opposed to only general classification of the type by particle size or shape.

    Keywords: Attenuated total reflectance; mid-infrared; FT-IR; spectral matching; upland cotton (Gossypium hirsutum L.); Pima cotton (Gossypium barbadense L.); cotton trash; foreign matter; ginning; spinning

    Copyright © 2006 American Chemical Society

    Read this article

    To access this article, please review the available access options below.

    Get instant access

    Purchase Access

    Read this article for 48 hours. Check out below using your ACS ID or as a guest.

    Recommended

    Access through Your Institution

    You may have access to this article through your institution.

    Your institution does not have access to this content. Add or change your institution or let them know you’d like them to include access.

    *

     Author to whom correspondence should be addressed [e-mail [email protected]; telephone (706) 546-3233; fax (706) 546-3607].

     USDA-ARS, Athens, GA.

     Hewlett-Packard Co., Corvallis, OR.

    §

     USDA-ARS, Clemson, SC.

    Cited By

    Click to copy section linkSection link copied!
    Citation Statements
    Explore this article's citation statements on scite.ai

    This article is cited by 47 publications.

    1. Ian G. M. Anthony, Matthew R. Brantley, Adam R. Floyd, Christina A. Gaw, Touradj Solouki. Improving Accuracy and Confidence of Chemical Identification by Gas Chromatography/Vacuum Ultraviolet Spectroscopy-Mass Spectrometry: Parallel Gas Chromatography, Vacuum Ultraviolet, and Mass Spectrometry Library Searches. Analytical Chemistry 2018, 90 (20) , 12307-12313. https://doi.org/10.1021/acs.analchem.8b04028
    2. Keith Jones, Girish Ramakrishnan, Minori Uchimiya, and Alexander Orlov . New Applications of X-ray Tomography in Pyrolysis of Biomass: Biochar Imaging. Energy & Fuels 2015, 29 (3) , 1628-1634. https://doi.org/10.1021/ef5027604
    3. Minori Uchimiya, Lynda H. Wartelle, K. Thomas Klasson, Chanel A. Fortier, and Isabel M. Lima . Influence of Pyrolysis Temperature on Biochar Property and Function as a Heavy Metal Sorbent in Soil. Journal of Agricultural and Food Chemistry 2011, 59 (6) , 2501-2510. https://doi.org/10.1021/jf104206c
    4. Prathiba Meganathan, Lakshmi Manokari Selvaraj, Sounder Subbaiah, Venkatesh Subramanian, Sudhagar Pitchaimuthu, Nagarajan Srinivasan. A synergistic self-cleaning and antibacterial studies of photocatalytic carbon nitride/polypyrrole coated cotton fabrics for smart textile application. Cellulose 2023, 30 (17) , 11211-11230. https://doi.org/10.1007/s10570-023-05533-w
    5. Chengjun Chen, Feixiang Shen, Chenggang Dai. SwinTD: Transformer-based detection network for foreign objects in the cut section of tobacco packets. Measurement 2023, 216 , 112953. https://doi.org/10.1016/j.measurement.2023.112953
    6. Pappu Kumar Yadav, J. Alex Thomasson, Robert Hardin, Stephen W. Searcy, Ulisses Braga-Neto, Sorin C. Popescu, Roberto Rodriguez III, Daniel E Martin, Juan Enciso, Karem Meza, Emma L. White. Plastic Contaminant Detection in Aerial Imagery of Cotton Fields Using Deep Learning. Agriculture 2023, 13 (7) , 1365. https://doi.org/10.3390/agriculture13071365
    7. Zhongqi HE, Yongliang LIU, Hee Jin KIM, Haile TEWOLDE, Hailin ZHANG. Fourier transform infrared spectral features of plant biomass components during cotton organ development and their biological implications. Journal of Cotton Research 2022, 5 (1) https://doi.org/10.1186/s42397-022-00117-8
    8. Yi Meng, Chenwei Zhang, Xiaoyu Gong, Jie Lu, Yi Cheng, Yehan Tao, Haisong Wang. A bio-based elastomer from cornstalk pith scaffold and natural rubber complexing with ferric ions: Preparation and mechanical properties. Polymer 2022, 244 , 124678. https://doi.org/10.1016/j.polymer.2022.124678
    9. Xihui Bian. Pattern Recognition Methods. 2022, 329-379. https://doi.org/10.1007/978-981-19-1625-0_12
    10. R.G. Candido, A.R. Gonçalves. Evaluation of two different applications for cellulose isolated from sugarcane bagasse in a biorefinery concept. Industrial Crops and Products 2019, 142 , 111616. https://doi.org/10.1016/j.indcrop.2019.111616
    11. Wenqian Xu, Zhiqing Song, Xinyu Luan, Changjiang Ding, Zhiyuan Cao, Xiaohong Ma. Biological Effects of High-Voltage Electric Field Treatment of Naked Oat Seeds. Applied Sciences 2019, 9 (18) , 3829. https://doi.org/10.3390/app9183829
    12. Yongliang Liu, Christopher Delhom. The relationship between instrumental leaf grade and Shirley Analyzer trash content in cotton lint. Textile Research Journal 2018, 88 (10) , 1091-1098. https://doi.org/10.1177/0040517517697641
    13. Xing-Quan Wang, Ren-Wu Zhou, Gerard de Groot, Kateryna Bazaka, Anthony B. Murphy, Kostya Ostrikov. Spectral characteristics of cotton seeds treated by a dielectric barrier discharge plasma. Scientific Reports 2017, 7 (1) https://doi.org/10.1038/s41598-017-04963-4
    14. Michael Santiago Cintrón, James E. Rodgers. Identification of Common Cotton Contaminants using an FTIR Microscope with a Focal Plane Array Detector. AATCC Journal of Research 2017, 4 (6) , 12-17. https://doi.org/10.14504/ajr.4.6.3
    15. M. H. J. van der Sluijs, L. Hunter. Cotton contamination. Textile Progress 2017, 49 (3) , 137-171. https://doi.org/10.1080/00405167.2018.1437008
    16. José Refugio Martínez, Alejandra Nieto-Villena, José Ángel de la Cruz-Mendoza, Gerardo Ortega-Zarzosa, Azdrubal Lobo Guerrero. Monitoring the natural aging degradation of paper by fluorescence. Journal of Cultural Heritage 2017, 26 , 22-27. https://doi.org/10.1016/j.culher.2017.01.011
    17. Mengyun Zhang, Changying Li, Fuzeng Yang. Classification of foreign matter embedded inside cotton lint using short wave infrared (SWIR) hyperspectral transmittance imaging. Computers and Electronics in Agriculture 2017, 139 , 75-90. https://doi.org/10.1016/j.compag.2017.05.005
    18. Chanel Fortier, Michael Santiago Cintrón, James Rodgers, Krystal Fontenot, Donna Peralta. Fourier-Transform Imaging of Cotton and Botanical and Field Trash Mixtures. Fibers 2017, 5 (2) , 20. https://doi.org/10.3390/fib5020020
    19. Derek P Whitelock, S Ed Hughs, Carlos B Armijo. Classifying cotton bark and grass extraneous matter using image analysis. Textile Research Journal 2017, 87 (8) , 891-901. https://doi.org/10.1177/0040517516641360
    20. Jesse Kuzy, Changying Li. A Pulsed Thermographic Imaging System for Detection and Identification of Cotton Foreign Matter. Sensors 2017, 17 (3) , 518. https://doi.org/10.3390/s17030518
    21. R.G. Candido, A.R. Gonçalves. Synthesis of cellulose acetate and carboxymethylcellulose from sugarcane straw. Carbohydrate Polymers 2016, 152 , 679-686. https://doi.org/10.1016/j.carbpol.2016.07.071
    22. Ruoyu Zhang, Changying Li, Mengyun Zhang, James Rodgers. Shortwave infrared hyperspectral reflectance imaging for cotton foreign matter classification. Computers and Electronics in Agriculture 2016, 127 , 260-270. https://doi.org/10.1016/j.compag.2016.06.023
    23. Adnan Mustafic, Yu Jiang, Changying Li. Cotton contamination detection and classification using hyperspectral fluorescence imaging. Textile Research Journal 2016, 86 (15) , 1574-1584. https://doi.org/10.1177/0040517515590416
    24. Wanhuai Zhou, Shoudong Xv, Congjiu Liu, Jianfeng Zhang. Applications of near infrared spectroscopy in cotton impurity and fiber quality detection: A review. Applied Spectroscopy Reviews 2016, 51 (4) , 318-332. https://doi.org/10.1080/05704928.2015.1131710
    25. Yongliang Liu, Zhongqi He, Mark Shankle, Haile Tewolde. Compositional features of cotton plant biomass fractions characterized by attenuated total reflection Fourier transform infrared spectroscopy. Industrial Crops and Products 2016, 79 , 283-286. https://doi.org/10.1016/j.indcrop.2015.11.022
    26. Yu Jiang, Changying Li. mRMR-based feature selection for classification of cotton foreign matter using hyperspectral imaging. Computers and Electronics in Agriculture 2015, 119 , 191-200. https://doi.org/10.1016/j.compag.2015.10.017
    27. Chanel Fortier, Michael Santiago Cintròn, James Rodgers. Fourier Transform Infrared Macro-Imaging of Botanical Cotton Trash. AATCC Journal of Research 2015, 2 (6) , 1-6. https://doi.org/10.14504/ajr.2.6.1
    28. Barun Shankar Gupta, Bjørn Petter Jelle, Tao Gao. Wood facade materials ageing analysis by FTIR spectroscopy. Proceedings of the Institution of Civil Engineers - Construction Materials 2015, 168 (5) , 219-231. https://doi.org/10.1680/coma.13.00021
    29. Barun Shankar Gupta, Bjørn Petter Jelle, Tao Gao. Wood facade materials ageing analysis by FTIR spectroscopy. Proceedings of the Institution of Civil Engineers - Construction Materials 2015, 168 (5) , 219-231. https://doi.org/10.1680/jcoma.13.00021
    30. Adnan Mustafic, Changying Li. Classification of cotton foreign matter using color features extracted from fluorescent images. Textile Research Journal 2015, 85 (12) , 1209-1220. https://doi.org/10.1177/0040517514561923
    31. Yu Jiang, Changying Li, . Detection and Discrimination of Cotton Foreign Matter Using Push-Broom Based Hyperspectral Imaging: System Design and Capability. PLOS ONE 2015, 10 (3) , e0121969. https://doi.org/10.1371/journal.pone.0121969
    32. Adnan Mustafic, Changying Li, Mark Haidekker. Blue and UV LED-induced fluorescence in cotton foreign matter. Journal of Biological Engineering 2014, 8 (1) https://doi.org/10.1186/1754-1611-8-29
    33. Feng Liu, Zhenwei Su, Xiangcheng He, Chaoyong Zhang, Mouqin Chen, Li Qiao. A laser imaging method for machine vision detection of white contaminants in cotton. Textile Research Journal 2014, 84 (18) , 1987-1994. https://doi.org/10.1177/0040517514530027
    34. Xiao-Li CHU, Jing-Yan LI, Pu CHEN, Yu-Peng XU. Algorithms, Strategies and Application Progress of Spectral Searching Methods. Chinese Journal of Analytical Chemistry 2014, 42 (9) , 1379-1386. https://doi.org/10.1016/S1872-2040(14)60768-4
    35. Atanu Biswas, S. Kim, Gordon W. Selling, H.N. Cheng. Conversion of agricultural residues to carboxymethylcellulose and carboxymethylcellulose acetate. Industrial Crops and Products 2014, 60 , 259-265. https://doi.org/10.1016/j.indcrop.2014.06.004
    36. Minori Uchimiya, Tsutomu Ohno, Zhongqi He. Pyrolysis temperature-dependent release of dissolved organic carbon from plant, manure, and biorefinery wastes. Journal of Analytical and Applied Pyrolysis 2013, 104 , 84-94. https://doi.org/10.1016/j.jaap.2013.09.003
    37. M. Navarro Escamilla, F. Rodenas Sanz, H. Li, S.A. Schönbichler, B. Yang, G.K. Bonn, C.W. Huck. Rapid determination of baicalin and total baicalein content in Scutellariae radix by ATR-IR and NIR spectroscopy. Talanta 2013, 114 , 304-310. https://doi.org/10.1016/j.talanta.2013.05.046
    38. Jihong Liu, Bo Zhu, Hongxia Jiang, Weidong Gao. Image analysis measurement of cottonseed coat fragments in 100% cotton woven fabric. Fibers and Polymers 2013, 14 (7) , 1208-1214. https://doi.org/10.1007/s12221-013-1208-y
    39. Jari Pajander, Kenneth Brian Haugshøj, Kathrine Bjørneboe, Pia Wahlberg, Jukka Rantanen. Foreign matter identification from solid dosage forms. Journal of Pharmaceutical and Biomedical Analysis 2013, 80 , 116-125. https://doi.org/10.1016/j.jpba.2013.02.036
    40. Yongliang Liu, Devron Thibodeaux, Gary Gamble. Development of Fourier transform infrared spectroscopy in direct, non-destructive, and rapid determination of cotton fiber maturity. Textile Research Journal 2011, 81 (15) , 1559-1567. https://doi.org/10.1177/0040517511410107
    41. Minori Uchimiya, SeChin Chang, K. Thomas Klasson. Screening biochars for heavy metal retention in soil: Role of oxygen functional groups. Journal of Hazardous Materials 2011, 190 (1-3) , 432-441. https://doi.org/10.1016/j.jhazmat.2011.03.063
    42. H.N. Cheng, Atanu Biswas. Chemical modification of cotton-based natural materials: Products from carboxymethylation. Carbohydrate Polymers 2011, 84 (3) , 1004-1010. https://doi.org/10.1016/j.carbpol.2010.12.059
    43. Chanel A Fortier, James E Rodgers, Michael S Cintrón, Xiaoliang Cui, Jonn A Foulk. Identification of cotton and cotton trash components by Fourier transform near-infrared spectroscopy. Textile Research Journal 2011, 81 (3) , 230-238. https://doi.org/10.1177/0040517510383620
    44. Yongliang Liu, Gary R. Gamble, Devron Thibodeaux. Assessment of Recovered Cotton Fibre and Trash Contents in Lint Cotton Waste by Ultraviolet/Visible/Near Infrared Reflectance Spectroscopy. Journal of Near Infrared Spectroscopy 2010, 18 (4) , 239-246. https://doi.org/10.1255/jnirs.890
    45. Fei Zhou, Tianhuai Ding. Detection of Cotton Lint Trash within the Ultraviolet—Visible Spectral Range. Applied Spectroscopy 2010, 64 (8) , 936-941. https://doi.org/10.1366/000370210792081091
    46. J. Brian Loudermilk, David S. Himmelsbach, Franklin E. Barton, James A. de Haseth. Novel Search Algorithms for a Mid-Infrared Spectral Library of Cotton Contaminants. Applied Spectroscopy 2008, 62 (6) , 661-670. https://doi.org/10.1366/000370208784657968
    47. Elisa Robotti, Marco Bobba, Andrea Panepinto, Emilio Marengo. Monitoring of the surface of paper samples exposed to UV light by ATR-FT-IR spectroscopy and use of multivariate control charts. Analytical and Bioanalytical Chemistry 2007, 388 (5-6) , 1249-1263. https://doi.org/10.1007/s00216-007-1370-4

    Journal of Agricultural and Food Chemistry

    Cite this: J. Agric. Food Chem. 2006, 54, 20, 7405–7412
    Click to copy citationCitation copied!
    https://doi.org/10.1021/jf052949g
    Published September 9, 2006
    Copyright © 2006 American Chemical Society

    Article Views

    1086

    Altmetric

    -

    Citations

    Learn about these metrics

    Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.

    Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.

    The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated.