Prediction of Textural Properties of Grass Carp (Ctenopharyngodon idellus) by Near Infrared Spectroscopy
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Abstract:
Texture and water-holding capacity of 211 grass carp samples were analyzed by near infrared spectrum and chemometric method. The diffuse reflectance spectra of samples were performed with different spectral pretreatments, such as multiplicative scatter correction (MSC), orthogonal signal correction (OSC), and standardization (S). The near-infrared quantitative analysis models were obtained for texture and water-holding capacity by partial least square regression. The results showed that the measured values met the modeling requirements. The optimized spectral pretreatments was orthogonal signal correction (OSC) which was suitable for analysis of water-holding capacity, hardness, resilience, springiness and shear force models of grass carp, while standardization was used for chewiness model. Partial least square method was applied to build near infrared spectrum models of grass carp texture indexes, and the correlation coefficients of the models were 0.9194, 0.9812, 0.9830, 0.9871, 0.7860 and 0.9896 for water-holding capacity, hardness, resilience, springiness, chewiness and shear force, respectively. The results indicated that the models have the potential to predict texture and water-holding capacity of grass carp expect chewiness. The NIR spectroscopy offers great advantages for the rapid and on-line application.
