近红外光谱技术在鱼糜等级评定中的应用研究

利用近红外光谱技术，对冷冻和解冻状态的不同等级白姑鱼糜进行等级评定。采用一阶导数法和标准正态变量变换法进行光谱预处理，再对预处理后的数据进行主成分分析，以主成分分析-马氏距离模式识别方法建立不同等级白姑鱼糜的等级评定模型，并对7项理化指标(水分、蛋白质、粗脂肪、盐溶性蛋白、凝胶强度、持水率和白度值)进行了测定。结果表明，主成分分析可以将三个等级白姑鱼糜较好地区分开;冷冻状态白姑鱼糜建立的等级评定模型效果优于解冻状态白姑鱼糜，前者的综合预测正确率为96.3%，后者的综合预测正确率为83.3%;三个等级白姑鱼糜的理化指标存在一定的差异。研究表明，近红外光谱技术可以快速无损评定白姑鱼糜等级。

Applied Research in Grade Estimation of Surimi by Near Infrared Spectroscopy

The feasibility of utilizing near infrared spectroscopy for estimating frozen and thawed white croaker surimi with different grades was presented in the research. First-derivative and standard normal variable transformation were used as pretreatment method, then principal component analysis was carried out on the processed datas. Establish grade estimation model on white croaker surimi with different grades by principal component analysis-mahalanobis distance pattern recognition method. Seven kinds of physicochemical indexes (moisture, protein, crude fat, salt-soluble protein, gel strength, water-holding ability and whiteness) of white croaker surimi with different grades were determinated. We came to the following conclusions. Firstly, white croaker surimi with three grade could be distinguished effectively by principal component analysis. Secondly, the model of grade estimation established by principal component analysis-mahalanobis distance pattern recognition method had better performance on frozen white croaker surimi than thawed ones, the former’s comprehensive accuracy was 96.3% with the latter’s is 83.3%. Thirdly, the physicochemical indexes of white croaker surimi with different grades had some distinctions. The research indicated that near infrared spectroscopy could estimate the grade of white croaker surimi rapidly and nondestructively.