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Integrated recognition and quantitative detection of starch in surimi by infrared spectroscopy and spectroscopic imaging.
Hou, Shi-Wei; Wei, Wei; Wang, Yang; Gan, Jian-Hong; Lu, Ying; Tao, Ning-Ping; Wang, Xi-Chang; Liu, Yuan; Xu, Chang-Hua.
Afiliação
  • Hou SW; College of Food Science & Technology, Shanghai Ocean University, Shanghai 201306, China.
  • Wei W; College of Food Science & Technology, Shanghai Ocean University, Shanghai 201306, China.
  • Wang Y; First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300112, China.
  • Gan JH; College of Food Science & Technology, Shanghai Ocean University, Shanghai 201306, China.
  • Lu Y; College of Food Science & Technology, Shanghai Ocean University, Shanghai 201306, China.
  • Tao NP; College of Food Science & Technology, Shanghai Ocean University, Shanghai 201306, China.
  • Wang XC; College of Food Science & Technology, Shanghai Ocean University, Shanghai 201306, China.
  • Liu Y; Department of Food Science and Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China. Electronic address: y_liu@sjtu.edu.cn.
  • Xu CH; College of Food Science & Technology, Shanghai Ocean University, Shanghai 201306, China; Shanghai Engineering Research Center of Aquatic-Product Processing & Preservation, Shanghai 201306, China; Laboratory of Quality and Safety Risk Assessment for Aquatic Products on Storage and Preservatio
Article em En | MEDLINE | ID: mdl-30818215
ABSTRACT
Surimi products have become increasingly-consumed food with prominent characteristics of high nutrition and convenience and its supply falls short of demand. However, due to exhausted fishery resource in recent years, surimi adulteration, such as addition of plant proteins, starch and other animal origin meat, is becoming serious, so recognition of these exogenous substances has become an urgent issue. In this study, Fourier transform infrared spectroscopy (FT-IR) combined with infrared spectroscopic imaging could distinguish heterogeneity in surimi qualitatively and quantitatively and obtain integral chemical images so that spatial distribution of each component in surimi could be visually displayed, thus a rapid recognition method and a prediction model were developed. The different starch contents in surimi had been primarily identified through intensity change of infrared absorption peaks at 1045cm-1 and 988cm-1, specifically with peak shifts to 1041cm-1 and to 992cm-1, respectively. In infrared imaging analysis, principal components (PCs) were separated and one key PC was confirmed as starch by characteristic peaks comparison at 1147cm-1, 1075cm-1, 997cm-1 and 930cm-1. Meanwhile, an established statistic model could predict starch content in surimi correctly with a reliable correlation coefficient (R=0.9856) and root mean square error of prediction (RMSEP=5.64). Therefore, FT-IR combined with infrared spectroscopic imaging could be applicable to integrally recognize and quantitatively detect starch in surimi.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Espectrofotometria Infravermelho / Amido / Produtos Pesqueiros Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Spectrochim Acta A Mol Biomol Spectrosc Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2019 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Espectrofotometria Infravermelho / Amido / Produtos Pesqueiros Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Spectrochim Acta A Mol Biomol Spectrosc Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2019 Tipo de documento: Article País de afiliação: China