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Direct Identification and Quantitation of Protein Peptide Powders Based on Multi-Molecular Infrared Spectroscopy and Multivariate Data Fusion.
Lin, Xiao-Wen; Liu, Run-Hui; Wang, Song; Yang, Jie-Wen; Tao, Ning-Ping; Wang, Xi-Chang; Zhou, Qun; Xu, Chang-Hua.
Afiliação
  • Lin XW; College of Food Science & Technology, Shanghai Ocean University, Shanghai 201306, P. R. China.
  • Liu RH; Shanghai Qinpu Biotechnology Pte Ltd, Shanghai 201306, China.
  • Wang S; College of Food Science & Technology, Shanghai Ocean University, Shanghai 201306, P. R. China.
  • Yang JW; College of Food Science & Technology, Shanghai Ocean University, Shanghai 201306, P. R. China.
  • Tao NP; Shanghai Qinpu Biotechnology Pte Ltd, Shanghai 201306, China.
  • Wang XC; College of Food Science & Technology, Shanghai Ocean University, Shanghai 201306, P. R. China.
  • Zhou Q; College of Food Science & Technology, Shanghai Ocean University, Shanghai 201306, P. R. China.
  • Xu CH; Shanghai Engineering Research Center of Aquatic-Product Processing & Preservation, Shanghai 201306, China.
J Agric Food Chem ; 71(28): 10819-10829, 2023 Jul 19.
Article em En | MEDLINE | ID: mdl-37406208
Given that protein peptide powders (PPPs) from different biological sources were inherited with diverse healthcare functions, which aroused adulteration of PPPs. A high-throughput and rapid methodology, united multi-molecular infrared (MM-IR) spectroscopy with data fusion, could determine the types and component content of PPPs from seven sources as examples. The chemical fingerprints of PPPs were thoroughly interpreted by tri-step infrared (IR) spectroscopy, and the defined spectral fingerprint region of protein peptide, total sugar, and fat was 3600-950 cm-1, which constituted MIR finger-print region. Moreover, the mid-level data fusion model was of great applicability in qualitative analysis, in which the F1-score reached 1 and the total accuracy was 100%, and a robust quantitative model was established with excellent predictive capacity (Rp: 0.9935, RMSEP: 1.288, and RPD: 7.97). MM-IR coordinated data fusion strategies to achieve high-throughput, multi-dimensional analysis of PPPs with better accuracy and robustness which meant a significant potential for the comprehensive analysis of other powders in food as well.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Peptídeos / Proteínas Tipo de estudo: Diagnostic_studies / Prognostic_studies / Qualitative_research Idioma: En Revista: J Agric Food Chem Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Peptídeos / Proteínas Tipo de estudo: Diagnostic_studies / Prognostic_studies / Qualitative_research Idioma: En Revista: J Agric Food Chem Ano de publicação: 2023 Tipo de documento: Article