电子鼻在芝麻酱品质识别中的应用

采用电子鼻对市售不同品牌及不同品种的芝麻酱进行识别,并在芝麻酱中分别添加不同比例的自制花生酱进行掺假,对电子鼻响应信号进行主成分分析、辨别因子分析、偏最小二乘回归分析和统计质量控制分析。结果表明:电子鼻能有效识别不同品牌的黑芝麻酱、白芝麻酱及混合芝麻酱;各掺假芝麻酱样品随着掺假比例的增加(0%、5%、10%、20%、40%、60%、80%、100%),样品的分布呈现出一定的规律性,电子鼻响应信号与掺假样品之间有较好的相关性,相关系数为0.99;对掺假芝麻酱建立的偏最小二乘回归模型,模型预测值误差在0.7%~2.7%之间。证明电子鼻检测技术能有效应用于芝麻酱品质的识别。

Discrimination of Sesame Paste Quality by Electronic Nose

Different commercial brands of sesame paste and sesame paste produced from different cultivars as well as sesame paste adulterated with various amounts of peanut paste were tested by electronic nose. The response signals were analyzed by principal component analysis (PCA), discriminant fact analysis (DFA), partial least-squares analysis regression (PLSR) and statistical quality control (SQC). The results showed that different brands of black sesame paste and white sesame paste and mixed sesame pastes could be effectively identified by electronic nose. The response to the addition of adulterant (0%, 5%, 10%, 20%, 40%, 60%, 80% and 100%) was linear with a high correlation coefficient (R2) of 0.99. The established partial least squares regression (PLSR) model gave a prediction error ranging from 0.7% to 2.7%. It was proved that electronic nose could be applied in sesame paste discrimination.