基于欧式距离法或因子化法的近红外光谱技术对牛肉掺假鉴定的研究
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摘要
利用近红外光谱技术结合欧氏距离法或因子化法建立牛肉中掺入猪肉和鸡肉的快速、准确的技术方法,从而为保证牛肉制品品质和安全提供强有力的检测手段;以牛肉和掺假肉(掺入猪肉和鸡肉)按照相同程度进行均匀搅碎,按照掺假肉10%为梯度增量进行制备掺假肉,共分为10类样本(10%至100%),采用单通道,光谱范围为12 000 cm~(-1)～4 000 cm~(-1),扫描次数为64次,特征波段为7 351.92 cm~(-1)～6 824.83 cm~(-1)、5 578.24 cm~(-1)～5 075.21 cm~(-1),预处理方式为一阶导数或二阶导数+矢量归一化+9点平滑,结果表明:猪肉和鸡肉掺假因子化法的判别率分别为94%和96.67%;因子化法可以试现对牛肉掺假进行定性分析鉴定。
Near-infrared spectroscopy combined withthe Euclidean distance method or factorization model was used to establish a rapid and accurate method for the detection of adulterated beef,thus providing a powerful detection method for ensuring the quality and safety of beef products.Beef and adulteration meat(mixed with pork and chicken) were uniformly ground to the same degree,and adulterated meat was prepared with a gradient increment of 10 %. The adulterated meat was divided into 10 samples(10 % to 100 %).Using in single channel,spectral range of was 12 000 cm~(-1)-4 000 cm~(-1) and the scanning frequency was 64. Several characteristics of the band was 7 351.92 cm~(-1)-6 824.83 cm~(-1),5 578.24 cm~(-1)-5 075.21 cm~(-1). Under the conditions of 1 and 1 nd or 2 nd derivative + vector normalization + 9-point smoothing preconditions,The results showed that the factorization method had a discriminant rate of 94 % and 96.67 %;Factorization methods could be used to qualitatively identify adulteration of beef.
Near-infrared spectroscopy combined withthe Euclidean distance method or factorization model was used to establish a rapid and accurate method for the detection of adulterated beef,thus providing a powerful detection method for ensuring the quality and safety of beef products.Beef and adulteration meat(mixed with pork and chicken) were uniformly ground to the same degree,and adulterated meat was prepared with a gradient increment of 10 %. The adulterated meat was divided into 10 samples(10 % to 100 %).Using in single channel,spectral range of was 12 000 cm~(-1)-4 000 cm~(-1) and the scanning frequency was 64. Several characteristics of the band was 7 351.92 cm~(-1)-6 824.83 cm~(-1),5 578.24 cm~(-1)-5 075.21 cm~(-1). Under the conditions of 1 and 1 nd or 2 nd derivative + vector normalization + 9-point smoothing preconditions,The results showed that the factorization method had a discriminant rate of 94 % and 96.67 %;Factorization methods could be used to qualitatively identify adulteration of beef.
引文
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[2]张毅峰.亚硝酸盐在肉制品中的应用及趋势[J].肉类工业,2015(10):46-49
[3]李巧玲,刘景艳.市场鲜猪肉掺假状况的调查监测[J].食品科学,2004, 25(10):273-276
[4]李欣南,关一夫.掺假肉检验技术发展现状[J].食品研究与开发,2016, 37(5):189-193
[5]杨冬燕,李浩,杨永存.肉制品掺假鉴别与定量检测[J].卫生研究,2016, 45(2):324-328
[6]董洋洋.试时荧光PCR对牛肉中掺入鸭肉和猪肉的定量检测研究[D].大庆:黑龙江八一农垦大学, 2016
[7]王旭峰,马冰峰,石磊,等.利用近红外光纤分析技术检测饲料中粗纤维含量[J].食品工业科技, 2013, 34(2):75-77
[8]纪朋,冯剑,李志伟.近红外分析技术在烟草行业的应用研究进展[J].安徽农业科学, 2011, 39(16):9848-9850
[9]吴利敏.近红外光谱法快速检测某些中药及中成药品质的应用研究[D].重庆:西南大学,2013
[10]宋涛.基于近红外技术的石油含水测量系统研究[D].北京:中国石油大学(华东), 2007
[11]杨红菊,姜艳彬,候东军,等.注胶肉的近红外光谱快速判别分析[J].肉类研究,2008(11):67-69
[12]杨志敏,丁武,张瑶.应用近红外技术快速鉴别原料肉注水的研究[J].食品研究与开发,2012,33(5):118-120
[13]彭海根,彭云发,詹映,等.近红外光谱技术结合联合区间间隔偏最小二乘法对南疆红枣糖度的测定[J].食品科技,2014,39(6):276-280
[14]张丽华,相启森,李顺峰,等.基于支持向量机的近红外光谱技术鉴别掺假牛肉[J].西北农林科技大学学报(自然科学版), 2016,44(12):201-205
[15]周健,成浩,叶阳,等.基于近红外的Fisher分类法识别茶叶原料品种的研究[J].光学学报, 2009, 29(4):1117-1121