| 电子鼻在牦牛肉和牛肉猪肉识别中的应用 |
| |
| 引用本文： | 贾洪锋,卢 一,何江红,潘 涛,肖 岚,张振宇,朱丽敏.电子鼻在牦牛肉和牛肉猪肉识别中的应用[J].农业工程学报,2011,27(5):358-363. |
| |
| 作者姓名： | 贾洪锋 卢 一 何江红 潘 涛 肖 岚 张振宇 朱丽敏 |
| |
| 作者单位： | 1. 四川烹饪高等专科学校食品科学系,成都,610100;烹饪科学四川省高等学校重点实验室,成都610100
2. Alpha M.O.S.,Toulouse,France 31400 亚太办事处,上海,200336 |
| |
| 基金项目： | 四川省科技厅科技支撑项目（09NZ0054）；食品加工四川省高校重点实验室科研项目（10S01） |
| |
| 摘 要： | 为了探索电子鼻对肉类掺假识别的可行性，利用电子鼻对牦牛肉、牛肉和猪肉样品进行了分析。通过对所获得的数据进行主成分分析（principal component analysis，PCA）、判别因子分析（discriminant factor analysis，DFA）和偏最小二乘回归分析（partial least-squares analysis，PLS）。结果表明：几种肉类在电子鼻传感器上有不同的特征性响应图谱，电子鼻能够有效识别猪、牛肉；同时电子鼻能够识别不同部位的牦牛肉和普通牛肉；但不能识别不同部位的猪肉。在牛肉馅中掺入不同比例的猪肉馅时，电子鼻也能进行识别。采用偏最小二乘回归分析对数据进行处理，电子鼻响应信号和猪肉馅掺入比例之间有很好的相关性（决定系数R2为0.9762），PLS模型预测误差在1.27%～7.00%之间。试验证明电子鼻可用于肉类的识别。
|
| 关 键 词： | 识别，传感器，农产品，电子鼻，牦牛肉，牛肉，猪肉，掺假 |
| 收稿时间： | 9/7/2010 12:00:00 AM |
| 修稿时间： | 2011/4/12 0:00:00 |
Recognition of yak meat, beef and pork by electronic nose |
| |
| Jia Hongfeng,Lu Yi,He Jianghong,Pan Tao,Xiao Lan,Zhang Zhenyu and Zhu Limin.Recognition of yak meat, beef and pork by electronic nose[J].Transactions of the Chinese Society of Agricultural Engineering,2011,27(5):358-363. |
| |
| Authors: | Jia Hongfeng Lu Yi He Jianghong Pan Tao Xiao Lan Zhang Zhenyu and Zhu Limin |
| |
| Institution: | Sichuan Higher Institute of Cuisine,Sichuan Higher Institute of Cuisine,Sichuan Higher Institute of Cuisine,Sichuan Higher Institute of Cuisine,Sichuan Higher Institute of Cuisine,Sichuan Higher Institute of Cuisine,Alpha M.O.S., Toulouse, France 31400 Asia Pacific, Shanghai |
| |
| Abstract: | In order to discuss the feasibility of meat adulteration recognition based on electronic nose, an electronic nose was used to analyze yak meat, beef and pork. The response signals were analyzed by principal component analysis (PCA), discriminant factor analysis (DFA) and partial least-squares analysis (PLS). The results indicated that yak meat, beef and pork samples had different characteristic response signals. Electronic nose could recognize yak meat, beef and pork, and also could recognize yak meat and beef samples at different growing locations, but this recognition was not suitable for pork at different growing locations. And it could also identify minced beef added with different ratio of minced pork. Coefficient of determination between sensors response signals and the ratio of minced pork of PLS model was 0.9762. The prediction error of PLS model was within 7.00%. It was proved that electronic nose could be applied in meat recognition. |
| |
| Keywords: | identification sensors agricultural products electronic nose yak meat beef pork adulteration |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
| 点击此处可从《农业工程学报》浏览原始摘要信息 |
| 点击此处可从《农业工程学报》下载免费的PDF全文 |
|
