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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">zhps</journal-id><journal-title-group><journal-title xml:lang="ru">Журнал прикладной спектроскопии</journal-title><trans-title-group xml:lang="en"><trans-title>Zhurnal Prikladnoii Spektroskopii</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">0514-7506</issn><publisher><publisher-name>B. I. Stepanov Institute of Physics of the National Academy of Sciences</publisher-name></publisher></journal-meta><article-meta><article-id custom-type="elpub" pub-id-type="custom">zhps-16</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>Статьи</subject></subj-group></article-categories><title-group><article-title>ОБНАРУЖЕНИЕ ОСТАТКОВ РАКТОПАМИНА И КЛЕНБУТЕРОЛА ГИДРОХЛОРИДA В СВИНИНЕ С ИСПОЛЬЗОВАНИЕМ СПЕКТРОСКОПИИ ПОВЕРХНОСТНОГО ГИГАНТСКОГО КОМБИНАЦИОННОГО РАССЕЯНИЯ СВЕТА</article-title><trans-title-group xml:lang="en"><trans-title>DETECTION OF RACTOPAMINE AND CLENBUTEROL HYDROCHLORIDE RESIDUES IN PORK USING SURFACE ENHANCED RAMAN SPECTROSCOPY</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Zhao</surname><given-names>J. H.</given-names></name><name name-style="western" xml:lang="en"><surname>Zhao</surname><given-names>J. H.</given-names></name></name-alternatives><email xlink:type="simple">noemail@neicon.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Yuan</surname><given-names>H. C.</given-names></name><name name-style="western" xml:lang="en"><surname>Yuan</surname><given-names>H. C.</given-names></name></name-alternatives><email xlink:type="simple">noemail@neicon.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Peng</surname><given-names>Y. J.</given-names></name><name name-style="western" xml:lang="en"><surname>Peng</surname><given-names>Y. J.</given-names></name></name-alternatives><email xlink:type="simple">noemail@neicon.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Hong</surname><given-names>Q. .</given-names></name><name name-style="western" xml:lang="en"><surname>Hong</surname><given-names>Q. .</given-names></name></name-alternatives><email xlink:type="simple">noemail@neicon.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Liu</surname><given-names>M. H.</given-names></name><name name-style="western" xml:lang="en"><surname>Liu</surname><given-names>M. H.</given-names></name></name-alternatives><email xlink:type="simple">suikelmh@sohu.com</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Инженерный колледж, Аграрный университет провинции Цзянси</institution></aff><aff xml:lang="en"><institution>College of Engineering, Jiangxi Agricultural University</institution></aff></aff-alternatives><pub-date pub-type="collection"><year>2017</year></pub-date><pub-date pub-type="epub"><day>10</day><month>03</month><year>2020</year></pub-date><volume>84</volume><issue>1</issue><fpage>90</fpage><lpage>95</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Zhao J.H., Yuan H.C., Peng Y.J., Hong Q..., Liu M.H., 2020</copyright-statement><copyright-year>2020</copyright-year><copyright-holder xml:lang="ru">Zhao J.H., Yuan H.C., Peng Y.J., Hong Q..., Liu M.H.</copyright-holder><copyright-holder xml:lang="en">Zhao J.H., Yuan H.C., Peng Y.J., Hong Q..., Liu M.H.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://zhps.ejournal.by/jour/article/view/16">https://zhps.ejournal.by/jour/article/view/16</self-uri><abstract><p>Спектроскопия поверхностного гигантского комбинационного рассеяния (ГКР) в сочетании с хемометрическими методами, такими как метод адаптивных итеративно взвешенных наименьших квадратов (AIR-PLS), вейвлет-преобразование и метод наименьших квадратов опорных векторов (LSSVM), применена для быстрого обнаружения и идентификации следов рактопамина (RAC) и кленбутерола гидрохлорида (CL) в свинине. Интенсивности первых вейвлет-сигналов на 1168 см-1 использованы для создания стандартной кривой остатков RАС в свинине (линейное уравнение регрессии у = -4.3683x - 11.059, коэффициент корреляции -0.9726), а интенсивности вторых сигналов на 1258 см-1 - остатков CL (линейное уравнение регрессии у = 33.595x + 36,538, коэффициент корреляции 0.9842). Вторые вейвлет-сигналы спектров ГКР выбраны в качестве входов модели классификации LSSVM для идентификации остатков RАС и CL в свинине со степенью точности, достигающей 100%. Экспериментальные результаты показывают, что предложенный метод, основанный на ГКР, является хорошей схемой быстрого обнаружения и идентификации остатков RAC и CL в свинине. </p></abstract><trans-abstract xml:lang="en"><p>Surface enhanced Raman spectroscopy (SERS) coupled with chemometric methods, such as adaptive iteratively reweighted penalized least squares (AIR-PLS), wavelet transform, and least squares support vector machine (LSSVM), was investigated to realize the rapid detection and identification of ractopamine (RAC) and clenbuterol hydrochloride (CL) residues in pork. First-level wavelet detail signal intensities at 1168 cm- 1  were used to establish a standard curve of the RAC residues in pork, and the linear regression equation and the correlation coefficient were y = -4.3683x - 11.059 and -0.9726. Second-level wavelet detail signal intensities at 1258 cm-1 were used to establish a standard curve of the CL residues in pork, and the linear regression equation and the correlation coefficient were y=33.595x+36.538 and 0.9842. The second-level wavelet detail signals of the SERS spectra were selected as the inputs of the LSSVM classification model for the identification of the RAC and CL residues in pork, with a total accuracy rate reaching 100%. The experimental results demonstrate that the proposed method based on SERS is a good detection scheme for the rapid detection and identification of RAC and CL residues in pork. </p></trans-abstract><kwd-group xml:lang="ru"><kwd>рактопамин</kwd><kwd>кленбутерола гидрохлорид</kwd><kwd>спектроскопия гигантского комбинационного рассеяния света</kwd><kwd>свинина</kwd><kwd>быстрое обнаружение и идентификация</kwd><kwd>ractopamine</kwd><kwd>clenbuterol hydrochloride</kwd><kwd>surface enhanced Raman spectroscopy</kwd><kwd>pork</kwd><kwd>rapid detection and identification</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">D.Wang, S. M. Yang, X. W. Liu, H. X. Yu, J. Instrum. Analysis, 29, No. 8, 812-816 (2010).</mixed-citation><mixed-citation xml:lang="en">D.Wang, S. M. Yang, X. W. Liu, H. X. Yu, J. Instrum. 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