利用挥发物红外光谱鉴别牛肉变质状态

发布时间：2018-05-13 00:43

本文选题：牛肉变质 + FTIR光谱　；参考：《光谱学与光谱分析》2017年09期

【摘要】：牛肉在运输过程中极易受到微生物的感染而变质,对牛肉变质的监测十分重要。我们利用长光程FTIR光谱检测牛肉变质时产生的挥发性物质。证明了牛肉在变质过程中产生的主要挥发性物质是氨气和二氧化碳。并定量分析牛肉变质产生的氨气和二氧化碳的变化规律,以判断牛肉的状态。采用主成分分析法(PCA)实现对挥发性物质的红外光谱分类,进而可以准确的区分新鲜和变质的牛肉。我们采用化学计量学方法软独立建模聚类分析法(SIMCA)和偏最小二乘判别分析(PLS-DA)对特征波段内的光谱进行分类,两种方法具有很好的判断率。结果表明长光程FTIR结合化学计量学方法能够区分新鲜和变质的牛肉。
[Abstract]:Beef is vulnerable to microbial infection during transportation, so it is very important to monitor beef spoilage. Long-path FTIR spectra were used to detect volatile substances produced by beef spoilage. It is proved that the main volatile substances produced by beef during deterioration are ammonia and carbon dioxide. The changes of ammonia and carbon dioxide produced by beef spoilage were analyzed quantitatively to judge the state of beef. Principal component Analysis (PCA) was used to classify volatile substances in infrared spectrum, which could distinguish fresh beef from bad beef accurately. In this paper, we use the chemometrics method to classify the spectrum in the characteristic band by using the soft independent modeling cluster analysis (Simca) and the partial least squares discriminant analysis (PLS-DA). The two methods have a good judgment rate. The results showed that long-path FTIR combined with chemometrics could distinguish fresh beef from bad beef.
【作者单位】：桂林电子科技大学电子工程与自动化学院;北京农业智能装备技术研究中心北京市农林科学院;
【基金】：国家科技支撑计划(2014BAD21B01) 广西自然科学基金项目(2013GXNSFAA019328) 广西信息科学实验中心重点基金项目(2012-02,桂林电子科技大学创新团队项目)资助
【分类号】：O657.33;TS251.52

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