气相红外光谱无损检测臭鳜鱼中挥发性盐基氮  

Non-destructive Testing of Total Volatile Base Nitrogen in Stinky Mandarin Fish by Gas-Phase Infrared Spectroscopy

作　　者：查靖 葛玲 姚颖 李婷婷 龙白雪 刘鑫汉 王武[1,2] 马飞 ZHA Jing;GE Ling;YAO Ying;LI Tingting;LONG Baixue;LIU Xinhan;WANG Wu;MA Fei(School of Food and Biological Engineering,Hefei University of Technology,Hefei 230009,Anhui,China;South Anhui Distinctive Agricultural Product Processing Technology Research and Application Center,Xuancheng 242000,Anhui,China;Xuanzhou District Bureau of Agriculture and Rural Affairs,Xuancheng 242000,Anhui,China)

机构地区：[1]合肥工业大学食品与生物工程学院,安徽合肥230009 [2]皖南特色农产品加工技术研究与应用中心,安徽宣城242000 [3]宣城市宣州区农业农村局,安徽宣城242000

出　　处：《食品研究与开发》2023年第16期150-156,共7页Food Research and Development

基　　金：“十四五”国家重点研发计划项目(2022YFD2100602);大学生创新训练项目(S202210359384);皖南特色农产品加工技术研究与应用中心专项基金(W2021JSFW0388)。

摘　　要：挥发性盐基氮(total volatile basic nitrogen,TVB-N)是衡量臭鳜鱼新鲜度的一项重要指标,而现有检测方法存在速度慢、对样品破坏性强的局限性。为实现TVB-N快速无损检测,该文利用气相傅里叶变换红外光谱获取不同贮藏条件下臭鳜鱼挥发物的光谱信息,采用高斯滤波、稳健局部加权回归(robust locally weighted regression,RLWR)、小波阈值去噪、模拟退火-偏最小二乘(simulated annealing-partial least squares,SA-PLS)等方法进行光谱预处理,偏最小二乘回归和支持向量回归算法构建预处理光谱与TVB-N之间的关联性模型。结果表明,与其它模型相比,经RLWR结合SA-PLS选择的特征波长光谱可建立最优预测模型,其决定系数(decision coefficient,R^(2)_(p))和相对预测误差分别为0.9428和4.0050,具有较高的精准度与鲁棒性。Total volatile basic nitrogen(TVB-N)is an important indicator for evaluating the freshness of stinky mandarin fish.The existing methods for detecting TVB-N,however,are generally time-consuming and in a destructive manner.Gas-phase Fourier transform infrared spectroscopy was employed to obtain the spectral information of volatiles from stinky mandarin fish under different storage conditions,so as to achieve the rapid and non-destructive testing of TVB-N.The spectral data were then pre-processed by Gaussian filtering,robust locally weighted regression(RLWR),wavelet threshold denoising,and simulated annealing-partial least squares(SA-PLS).The correlation model between preprocessed spectra and TVB-N was built by partial least squares regression and support vector regression.Finally,the optimal prediction model was established by RLWR combined with SA-PLS,and its decision coefficient(R^(2)_(p))and relative prediction deviation were 0.9428 and 4.005,respectively.The results showed that the established method with high accuracy and robustness provided important theoretical support for industrial online detection.

关 键 词：挥发性盐基氮 红外光谱 臭鳜鱼 无损检测 模型 

分 类 号：TS254.7[轻工技术与工程—水产品加工及贮藏工程] O657.33[轻工技术与工程—食品科学与工程]