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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-2419</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>АННОТАЦИИ АНГЛОЯЗЫЧНЫХ СТАТЕЙ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>ABSTRACTS ENGLISH-LANGUAGE ARTICLES</subject></subj-group></article-categories><title-group><article-title>Разработка колориметрической сенсорной системы и прогностическое моделирование для быстрого обнаружения хлорпирифоса</article-title><trans-title-group xml:lang="en"><trans-title>Development of a Colorimetric Sensing System and Predictive Modeling for Fast Chlorpyrifos Detection</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>Li</surname><given-names>W.</given-names></name><name name-style="western" xml:lang="en"><surname>Li</surname><given-names>Wen</given-names></name></name-alternatives><bio xml:lang="ru"><p>Пекин</p></bio><bio xml:lang="en"><p>Beijing</p></bio><email xlink:type="simple">leewen2012@163.com</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>Xiao</surname><given-names>H.</given-names></name><name name-style="western" xml:lang="en"><surname>Xiao</surname><given-names>Hongbing</given-names></name></name-alternatives><bio xml:lang="ru"><p>Пекин</p></bio><bio xml:lang="en"><p>Beijing</p></bio><email xlink:type="simple">x.hb@163.com</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Пекинская ключевая лаборатория технологий больших данных для обеспечения безопасности  пищевых продуктов; Пекинский технологический и коммерческий университет</institution><country>Китай</country></aff><aff xml:lang="en"><institution>Beijing Key Laboratory of Big Data Technology for Food Safety; School of Computer and Artificial Intelligence, Beijing Technology and Business University</institution><country>China</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2026</year></pub-date><pub-date pub-type="epub"><day>28</day><month>09</month><year>2026</year></pub-date><volume>93</volume><issue>5</issue><fpage>724</fpage><lpage>724</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Li W., Xiao H., 2026</copyright-statement><copyright-year>2026</copyright-year><copyright-holder xml:lang="ru">Li W., Xiao H.</copyright-holder><copyright-holder xml:lang="en">Li W., Xiao 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/2419">https://zhps.ejournal.by/jour/article/view/2419</self-uri><abstract><p>Для быстрого количественного определения хлорпирифоса разработана методика, объединяющая колориметрическую спектроскопию и хемометрику. На основе молекулярной структуры хлорпирифоса в качестве колориметрических реагентов выбраны хлорид палладия и резорцин, а в качестве растворителей для хлорида палладия – соляная и уксусная кислоты. Созданы три колориметрические системы для реакции с хлорпирифосом различных концентраций. При сравнении спектров поглощения после колориметрических реакций установлено, что раствор хлорида палладия в уксусной кислоте является наиболее эффективным колориметрическим реагентом, способным различать сигналы поглощения при концентрациях хлорпирифоса 0.01 мг/кг. Для 50 образцов хлорпирифоса (0.01–88 мг/кг) оптимальная модель выбрана путем оценки ключевых параметров: коэффициентов детерминации калибровочного набора (Rc2), набора прогнозирования (Rp2), а также среднеквадратичных ошибок калибровки (RMSEC) и прогнозирования (RMSEP). Модель регрессии методом частичных наименьших квадратов (PLS) достигла значений Rc2 = 0.9975, RMSEC = 1.3383 мг/кг, Rp2 = 0.9948 и RMSEP = = 1.8614 мг/кг. Эта чувствительность соответствует пределам обнаружения, установленным для некоторых пищевых продуктов в китайском национальном стандарте GB2763-2021. Метод обладает эксплуатационной безопасностью, требует всего 2 мин для колориметрической реакции и обеспечивает практическую основу для разработки приборов обнаружения других серосодержащих органофосфорных пестицидов.</p></abstract><trans-abstract xml:lang="en"><p>For rapid quantitative detection of chlorpyrifos, an enhanced technique integrating colorimetric spectroscopy and chemometrics was created. Based on the molecular structure of chlorpyrifos, palladium chloride and resorcinol were selected as colorimetric reagents, with hydrochloric acid and acetic acid used as solvents for palladium chloride, respectively. Three distinct colorimetric systems were constructed to react with chlorpyrifos at varying concentrations. By comparing the absorbance spectra after the colorimetric reactions, the palladium chloride-acetic acid solution was idjentified as the most effective colorimetric reagent, capable of distinguishing absorbance signals for chlorpyrifos concentrations as low as 0.01 mg/kg. For 50 chlorpyrifos samples (0.01–88 mg/kg), the optimal model was selected by evaluating four key parameters: the determination coefficients of the calibration set (Rc2) and the prediction set (Rp2), together with the root mean square errors of calibration (RMSEC) and prediction (RMSEP). The partial least squares (PLS) regression model achieved Rc2 = 0.9975, RMSEC = 1.3383 mg/kg, Rp2 = 0.9948, and RMSEP = 1.8614 mg/kg. This sensitivity meets the detection limits specified for certain food products in the Chinese National Standard GB 2763-2021. The method is operationally safe, requires only 2 minutes for the colorimetric reaction, and provides a practical basis for developing detection instruments for other sulfur-containing organophosphorus pesticides. </p></trans-abstract><kwd-group xml:lang="ru"><kwd>хлорпирифос</kwd><kwd>колориметрическая сенсорная система</kwd><kwd>быстрое обнаружение</kwd><kwd>хлорид палладия</kwd></kwd-group><kwd-group xml:lang="en"><kwd>chlorpyrifos</kwd><kwd>colorimetric sensing system</kwd><kwd>fast detection</kwd><kwd>palladium chloride</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">This work was supported by the National Natural Science Foundation of China (No. 61473009).</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">W. J. Li, J. L. Chen, F. Z. Linli, X. G. Chen, Y. K. Huang, X. Yang, Food Chem. 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