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Prediction of chicken quality attributes by near infrared spectroscopy.
Barbin, Douglas Fernandes; Kaminishikawahara, Cintia Midori; Soares, Adriana Lourenco; Mizubuti, Ivone Yurika; Grespan, Moises; Shimokomaki, Massami; Hirooka, Elisa Yoko.
Afiliación
  • Barbin DF; Department of Food Science, Federal University of Technology - Parana (UTFPR), Brazil. Electronic address: dfbarbin@yahoo.com.br.
  • Kaminishikawahara CM; Department of Food Science and Technology, State University of Londrina (UEL), Brazil.
  • Soares AL; Department of Food Science and Technology, State University of Londrina (UEL), Brazil.
  • Mizubuti IY; Department of Animal Science, State University of Londrina (UEL), Brazil.
  • Grespan M; Doctor of Veterinary Medicine, Cascavel, PR, Brazil.
  • Shimokomaki M; Department of Food Science, Federal University of Technology - Parana (UTFPR), Brazil; Department of Animal Science, State University of Londrina (UEL), Brazil.
  • Hirooka EY; Department of Food Science and Technology, State University of Londrina (UEL), Brazil.
Food Chem ; 168: 554-60, 2015 Feb 01.
Article en En | MEDLINE | ID: mdl-25172747
In the present study, near-infrared (NIR) reflectance was tested as a potential technique to predict quality attributes of chicken breast (Pectoralis major). Spectra in the wavelengths between 400 and 2500nm were analysed using principal component analysis (PCA) and quality attributes were predicted using partial least-squares regression (PLSR). PCA performed on NIR dataset revealed the influence of muscle reflectance (L(∗)) influencing the spectra. PCA was not successful to completely discriminate between pale, soft and exudative (PSE) and pale-only muscles. High-quality PLSR were obtained for L(∗) and pH models predicted individually (R(2)CV of 0.91 and 0.81, and SECV of 1.99 and 0.07, respectively). Water-holding capacity was the most challenging attribute to determine (R(2)CV of 0.70 and SECV of 2.40%). Sample mincing and different spectra pre-treatments were not necessary to maximise the predictive performance of models. Results suggest that NIR spectroscopy can become useful tool for quality assessment of chicken meat.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Músculos Pectorales / Espectroscopía Infrarroja Corta / Tecnología de Alimentos / Carne Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Animals Idioma: En Revista: Food Chem Año: 2015 Tipo del documento: Article Pais de publicación: Reino Unido
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Músculos Pectorales / Espectroscopía Infrarroja Corta / Tecnología de Alimentos / Carne Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Animals Idioma: En Revista: Food Chem Año: 2015 Tipo del documento: Article Pais de publicación: Reino Unido