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基于高光谱成像技术的猪肉新鲜度评价
引用本文:张雷蕾,李永玉,彭彦昆,王 伟,江发潮,陶斐斐,单佳佳.基于高光谱成像技术的猪肉新鲜度评价[J].农业工程学报,2012,28(7):254-259.
作者姓名:张雷蕾  李永玉  彭彦昆  王 伟  江发潮  陶斐斐  单佳佳
作者单位:中国农业大学工学院,北京,100083
基金项目:公益性行业(农业)科研专项经费资助(项目编号:201003008)
摘    要:该文研究利用高光谱成像技术预测猪肉新鲜度参数,挥发性盐基氮(TVB-N)和pH值。在470~1000nm波长范围内,从高光谱图像中提取的反射光谱,分别经过2次Savitzky-Golay(S-G)平滑、多元散射校正(MSC)处理后,建立PLSR(偏最小二乘法)的预测模型。对TVB-N的预测,使用2次S-G平滑处理、MSC光谱建立的PLSR预测模型相关系数分别为0.90和0.89,预测模型标准差分别为7.80和8.05。对pH值的预测,经过MSC处理比2次S-G平滑处理的结果好,相关系数为0.79,预测模型标准差为0.37。同时综合2个参数利用MSC处理后的预测模型对猪肉新鲜度进行评定,准确率达91%。研究结果表明,高光谱成像技术可以用于猪肉新鲜度快速无损检测。

关 键 词:光谱分析  肉制品  pH值  无损检测  高光谱  猪肉新鲜度  挥发性盐基氮  偏最小二乘回归
收稿时间:4/7/2011 12:00:00 AM
修稿时间:2012/2/16 0:00:00

Determination of pork freshness attributes by hyperspectral imaging technique
Zhang Leilei,Li Yongyu,Peng Yankun,Wang Wei,Jiang Fachao,Tao Feifei and Shan Jiajia.Determination of pork freshness attributes by hyperspectral imaging technique[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(7):254-259.
Authors:Zhang Leilei  Li Yongyu  Peng Yankun  Wang Wei  Jiang Fachao  Tao Feifei and Shan Jiajia
Institution:(College of Engineering,China Agricultural University,Beijing 100083,China)
Abstract:The objectives of this research was to develop a hyperspectral imaging system to predict pork freshness based on quality attributes such as total volatile basic nitrogen (TVB-N) and pH value. Reflectance spectra were collected from the hyperspectral scattering images in the range of 470 to 1 000 nm, and pre-processed by Savitzky-Golay (S-G) based on five and eleven smoothening points and multiple scattering correlation (MSC) methods separately. Their prediction results were compared with prediction models developed by partial least square regression (PLSR) method. PLSR with S-G pre-processing could predict pork TVB-N with correlation coefficient (Rv) of 0.90 and standard error of prediction (SEP) of 7.80. Similarly PLSR with MSC pre-processing data predicted pork TVB-N with Rv of 0.89 and SEP of 8.0. The prediction model established using MSC as pre-processing method yielded better result for prediction of pH value, which Rv was 0.79 and SEP was 0.37. The result showed that, by the prediction models for TVB-N and pH value with MSC pre-processing method, the prediction accuracy for pork freshness classification could reach up to 91%. The research demonstrates that the hyperspectral imaging technique can be applied in rapid and non-destructive detection of pork freshness.
Keywords:spectrum analysis  meats  pH value  nondestructive examination  hyperspectral imaging technique  pork freshness  TVB-N  PLSR
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