近红外光谱技术建立镜鲤新鲜度定量预测模型

以镜鲤为研究对象,利用近红外光谱技术和化学计量法采集、测定相关指标,并应用偏最小二乘法(PLS)、偏最小二乘法和BP人工神经网络两种方法经比较优化模型。经过鱼肉样品光谱的扫描及pH值、TVB-N(挥发性盐基氮)值、TBA(硫代巴比妥酸)值的测定,在21种预处理下,确定最佳建模方式、预处理方式和最优波段。经模型优化得知,pH、TVB-N、TBA均在偏最小二乘法中建立的模型最好,最优预处理方法分别为基线校正和标准正态变量变换、净分析信号、Savitzky-Golay导数和基线校正,最优波段分别为1 000~1 300 nm和1 700~1 799 nm、1 000~1 200 nm和1 300~1 650 nm、1 000~1 799 nm,并且pH、TVB-N和TBA的Rc分别为0.9906、0.99865、0.99971,Rp分别为0.6436、0.021357、0.7723,达到了利用近红外光谱技术对镜鲤新鲜度高效、快捷、无损伤的定量检测预测模型的建立。

Isolation and identification of Orf virus ORFV/GD-QY/01 strain

Taking mirror carp as the research object, the near infrared spectroscopy (NIRS) and stoichiometry were used to collect and determine the related indexes. The partial least squares (PLS), partial least squares (PLS) and BP artificial neural network were used to optimize the model. The optimum modeling method, pretreatment method and wave band were determined under 21 pretreatments by scanning the spectrum of fish and pH value, TVB-N (volatile base nitrogen) value and TBA (thiobarbituric acid) value. The model optimization shows that pH, TVB-N and TBA are the best models in the partial least squares method. The optimal preprocessing methods are baseline correction and standard normal variable transformation, net analysis signal, Savitzky-Golay derivative and baseline correction. The optimal bands respectively are 1000-1300 and 1700-1799 nm, 1000-1200 and 1300-1650 nm, 1000-1799 nm. The RC values of pH, TVB-N and TBA respectively were 0.9906, 0.99865 and 0.99971, respectively. The Rp values respectively were 0.6436, 0.021357 and 0.7723. The establishment of a quantitative detection and prediction model for freshness of mirror carp by near infrared spectroscopy was achieved.