摘要
旨在探讨一种快速检测猪肉储藏时间的电子鼻方法。本研究采用德国Airsense公司的PEN2型便携式电子鼻对不同储藏时间(0～7d)的猪肉样品进行检测,每天检测42个样品,每个样品质量为10g,密封时间为5min。提取第60s数据进行线性判别分析,结果显示电子鼻能较好的区分不同储藏天数的猪肉样品。同时用逐步判别分析和BP神经网络对猪肉储藏时间进行预测,训练集的准确率,前者为100%,后者为94.17%,而预测集的准确率,前者为97.92%,后者为93.75%。研究表明电子鼻技术有望在猪肉新鲜度快速检测上得到广泛的应用。
In this study,a rapid detection method based on electronic nose for pork freshness was developed.An electronic nose（E-nose,PEN 2）was employed to classify pork groups with different storage time（0~7 d）,42 samples were tested everyday.The mass of each sample was 10 g,and the headspace-generated time was 5 min.The 60th data from the response of the E-nose was extracted for further analysis.After employing the Linear Discriminant Analysis（LDA）,samples could be well classified according to their storage time.Stepwise Linear Discriminant Analysis（Step-LDA）and Back Propagation Neural Network（BPNN）were also employed to predict the storage time of the samples.The result showed that Step-LDA got 100% training accuracy with 97.92% prediction accuracy,and BPNN got 94.17% training accuracy with 93.75% prediction accuracy.This study implied that electronic nose method could be expected to more wildly used on pork freshness detection.
出处
《传感技术学报》
CAS
CSCD
北大核心
2010年第10期1376-1380,共5页
Chinese Journal of Sensors and Actuators
基金
国家自然科学基金资助(30571076)
关键词
电子鼻
检测
逐步判别分析
BP神经网络
猪肉
electronic nose
detection
Stepwise Linear Discriminant Analysis（Step-LDA）
BPNN
pork
