近红外光谱技术分析草鱼的质构特性

Prediction of Textural Properties of Grass Carp (Ctenopharyngodon idellus) by Near Infrared Spectroscopy

摘要:

采用化学计量学方法，测定211个草鱼样品鱼肉的质构参数和持水性，并采集各样品的近红外光谱，以建立基于近红外光谱技术的草鱼质构特性的快速检测方法。结果表明，样品数据范围较大，可满足建模要求，比较多种光谱预处理方法，确定正交信号校正（OSC）适宜分析鱼肉持水性、硬度、回复性、弹性和剪切力的大小，而鱼肉咀嚼性的近红外光谱的最佳预处理方法是数据标准化（S）。采用偏最小二乘法分别建立草鱼各质构指标的近红外定量分析模型。所建立的鱼肉持水性、硬度、回复性、弹性、咀嚼性和剪切力指标的近红外光谱模型的相关系数分别为0.9194、0.9812、0.9830、0.9871、0.7860和0.9896，说明除了咀嚼性模型外，草鱼质构指标各数学模型的预测值和实测值之间具有较高的相关性，采用该方法能较为准确、快速地测出草鱼鱼肉持水性、硬度、回复性、弹性和剪切力的值。

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.