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作 者:何鸿举[1,2,3] 王洋洋 王魏 蒋圣启 朱亚东 马汉军[1,2] 陈复生[2,3] 朱明明 赵圣明 HE Hong-ju;WANG Yang-yang;WANG Wei;JIANG Sheng-qi;ZHU Ya-dong;MA Han-jun;CHEN Fu-sheng;ZHU Ming-ming;ZHAO Sheng-ming(School of Food Science,Henan Institute of Science and Technology,Xinxiang 453003,China;Postdoctoral Research and Development Base,Henan Institute of Science and Technology,Xinxiang 453003,China;College of Grain,Oil and Food,Henan University of Technology,Zhengzhou 450001,China)
机构地区:[1]河南科技学院食品学院,河南新乡453003 [2]河南科技学院博士后研发基地,河南新乡453003 [3]河南工业大学粮油食品学院,河南郑州450001
出 处:《食品工业科技》2020年第8期236-241,共6页Science and Technology of Food Industry
基 金:河南省重大科技专项项目(161100110600);中国博士后科学基金(2018M632767);河南省科技攻关项目(182102310060);河南省青年人才托举工程项目(2018HYTP008);河南科技学院高层次人才引进项目(2015015);河南科技学院重大科研培育项目(2016ZD03)。
摘 要:利用近红外(NIR)高光谱成像技术结合连续投影算法(SPA)快速、无损检测五花肉的过氧化值。通过高光谱成像系统采集样品的光谱图像,提取其反射光谱信息,经过基线校正(BC)、高斯滤波平滑(GFS)、中值滤波平滑(MFS)、卷积平滑(SGS)、移动平均值平滑(MAS)、标准正态变量变换(SNV)、多元散射校正(MSC)七种预处理后,利用偏最小二乘(PLS)建立预测模型。使用SPA筛选最优波长,重新预算,构建优化的PLS模型和多元线性回归(MLR)模型。结果显示,经过BC预处理(RP=0.960,RMSEP=5.15×10-4 g/100 g)和原始数据RAW(RP=0.960,RMSEP=4.89×10-4 g/100 g)的全波段PLS模型(F-PLS)预测过氧化值效果较好。优化结果显示,RAW的MLR模型(RP=0.968,RMSEP=4.12×10-4 g/100 g)预测效果更好。研究表明,NIR高光谱成像技术联用SPA算法可潜在实现对五花肉过氧化值的快速无损检测。The peroxidation value of pork belly was rapidly and nondestructively detected by near infrared(NIR)hyperspectral technique combined with continuous projection algorithm(SPA).Spectral images of samples were acquired through the high spectral spectroscopy imaging system,and their reflection spectrum information was extracted,after seven kinds of pretreatment,including baseline correction(BC),gaussian filter smoothing(GFS),and median filtering smoothing(MFS),savitzky golay smoothing(SGS),moving average smoothing(MAS),standard normal variate(SNV),and multiplicative scatter correction(MSC),partial least squares(PLS)were used to establish the prediction model,and used the regression coefficient method(RC)and SPA to select the optimal wavelength,multiple linear regression(MLR)and PLS optimization model.The results showed that the full-band PLS model(F-PLS)with BC preconditioning(RP=0.960,RMSEP=5.15×10-4 g/100 g)and RAW data(RP=0.960,RMSEP=4.89×10-4 g/100 g)had better prediction effect on peroxidation value,and the optimization showed that the MLR optimization model of RAW(RP=0.968,RMSEP=4.12×10-4 g/100 g)had better prediction effect.The results showed that this method can predict the changes of pork under different refrigeration conditions.
关 键 词:高光谱成像技术 过氧化值 偏最小二乘 连续投影算法 多元线性回归
分 类 号:TS251.7[轻工技术与工程—农产品加工及贮藏工程]
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