ABSTRACT

In this paper, freshness monitoring model on small larimichthys polyactis based on multiple sensor array system (MSAS) combined with total volatile basic nitrogen (TVB-N) examination was studied. Larimichthys polyactis was obtained and prepared as detecting samples. MSAS was developed based on volatile gas content of the fish samples. Meanwhile, TVB-N was examined to provide quality reference for MSAS measurement. MSAS responding data were processed by principal component analysis (PCA) and non-linear signal analysis model. Larimichthys polyactis freshness deciding model was developed by non-linear fitting between signal processing features and TVB-N parameters. Results indicated that the method studied in this work presented good freshness deciding accuracy for larimichthys polyactis. This method also presented some advantages including rapid analysis, easy operation, and low cost. It is promising in aquatic products quality raped determination.

摘要

本文研究了基于多传感器阵列系统(MSAS)结合总挥发性碱性氮(TVB-N)检测的小海鱼新鲜度监测模型。获得并制备了松茸作为检测样品。MSAS 是根据鱼样品的挥发性气体含量开发的。同时对TVB-N进行检测，为MSAS测量提供质量参考。MSAS响应数据采用主成分分析(PCA)和非线性信号分析模型进行处理。Larimichthys polyactis 新鲜度判定模型是通过信号处理特征和 TVB-N 参数之间的非线性拟合开发的。结果表明，本文所研究的方法对海鱼的新鲜度判定准确度较高。该方法还具有分析速度快、操作简便、成本低等优点。在水产品质量油菜测定中具有广阔的应用前景。