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基于近红外光谱技术快速识别不同动物源肉品
引用本文:孟一,张玉华,王家敏,毕然,王国利.基于近红外光谱技术快速识别不同动物源肉品[J].食品科学,2014,35(6):156-158.
作者姓名:孟一  张玉华  王家敏  毕然  王国利
作者单位:1.山东商业职业技术学院 山东省农产品贮运保鲜技术重点实验室,山东 济南 250103; 2.国家农产品现代物流工程技术研究中心,山东 济南 250103
基金项目:济南市高校院所自主创新计划项目(201202060);山东省科技发展计划项目(2012GNC11009)
摘    要:利用傅里叶变换近红外光谱技术建立猪肉、牛肉和羊肉的定性识别模型。用主成分分析法将原始数据压缩为10 个主成分,在全波段9 881.46~4 119.20 cm-1范围内,利用附加散射校正技术结合Savitzky-Golay滤波法对光谱数据进行预处理,采用判别分析法建立模型。模型对训练集的识别准确率为100%,对预测集猪肉、牛肉和羊肉的识别准确率分别为99.28%、97.42%和100%。结果表明:近红外光谱结合模式识别方法能快速无损地识别猪肉、牛肉和羊肉。

关 键 词:近红外光谱  模式识别法  肉类识别  
收稿时间:2013-06-03

Rapid Identification of Meat of Different Animal Origins Based on Near Infrared Spectroscopy
MENG Yi,ZHANG Yu-hua,WANG Jia-min,BI Ran,WANG Guo-li.Rapid Identification of Meat of Different Animal Origins Based on Near Infrared Spectroscopy[J].Food Science,2014,35(6):156-158.
Authors:MENG Yi  ZHANG Yu-hua  WANG Jia-min  BI Ran  WANG Guo-li
Affiliation:1. Shandong Key Laboratory of Storage and Transportation Technology of Agricultural Products, Shandong Institute of Commerce and Technology, Jinan 250103, China; 2. National Engineering Research Center for Agricultural Products Logistics, Jinan 250103, China
Abstract:A qualitative identification model for pork, beef and mutton was established by Fourier transform near-infrared
spectroscopy (NIR). The raw data were compressed to 10 principal components using principal component analysis. The
spectral data were preprocessed by additional scattering correction combined with Savitzky-Golayfilter method in the range
of 9 881.46–4 119.20 cm-1. The model was established using discriminant analysis. Identification accuracy rate of the model
for training set was 100%. Identification accuracy rates of pork, beef and mutton for prediction set were 99.28%, 97.42% and
100%, respectively. These results showed that pork, beef and mutton could be rapidly and non-destructively identified by
near-infrared spectroscopy combined with pattern recognition method.
Keywords:near-infrared spectroscopy  pattern recognition method  identification of meat  
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