近红外光谱技术在鱼糜定性和定量上的应用

以海水鱼糜(包括狭鳕、带鱼、鲷和混合鱼糜)以及淡水鱼糜(包括鲢和草鱼鱼糜)为研究对象,应用傅立叶近红外光谱技术结合化学计量学对鱼糜进行定性和定量分析。用聚类分析和线性判别的方法建立海水和淡水鱼糜的定性鉴别模型,并应用偏最小二乘法(PLS)分别建立海水鱼糜水分含量和蛋白质含量的近红外定量分析模型。结果表明,海水和淡水鱼糜的定性鉴别模型预测率达100%;建立的近红外定量分析模型中,海水鱼糜的水分和蛋白质的模型的相关系数分别达0.98和0.96以上,模型能较为准确、快速地预测定海水鱼糜中水分和蛋白质含量,有很大的潜力可应用于实际生产。

Qualitative and quantitative analyses of surimi with near infrared reflectance spectroscopy

With the increasing production and trade of surimi and surimi based foods,consumers have a higher quality requirement.Traditional analysis methods are time consumed,consumed large quantities of chemical reagents.Quality of surimi can be rapidly detected using near infrared analysis.Seawater surimi(including Alaska pollock surimi,hairtail surimi,sea bream surimi and mix surimi)and freshwater surimi(including silver carp surimi and grass carp surimi)were used in the study.Chemometric methods,including cluster and linear discriminant analysis(LDA)as well as partial least square(PLS)regression,were used to interpret spectral data.Results indicated that NIR method could successfully classify seawater and freshwater surimi with 100% prediction rate.In addition,the PLS models for water and protein content in surimi had good predictability:the correlation coefficients of the models were 0.98 for water and 0.96 for protein.Results showed that NIRS has great potential to be used in determining surimi quality.And important efforts for the practical application of near infrared have been made.In future studies,more representative samples should be added to enhance adaptability of models.