近红外光谱技术快速鉴别碱水浸泡鸡肉的研究
Study on rapid identification of alkali-soaked chicken meat by near-infrared spectroscopy
章明 1樊艳凤 1沈啸 1唐修君 1陆俊贤 1高玉时1
作者信息
- 1. 江苏省家禽科学研究所/江苏省家禽遗传育种重点实验室,江苏扬州 225125
- 折叠
摘要
采用近红外光谱分析技术并结合主成分分析法,建立碱水浸泡鸡肉快速鉴别模型.原始光谱经平滑、多元散射校正和一阶导数等预处理后进行系统主成分分析,结果显示正常鸡肉和碱水浸泡鸡肉能得到清晰的分类.通过不同光谱预处理方法,采用簇类的独立软模式法建立分类模型,结果显示通过对样品光谱采用7点卷积平滑方法预处理,分类模型综合正确率最高,校正回判正确率在77.08％～100％之间,预测正确率在81.25％～100％之间.综上,采用近红外光谱分析技术对碱水浸泡鸡肉进行快速鉴别可行.
Abstract
A rapid identification model of alkaline-soaked chicken meat was established by using near-infrared spectral analysis combined with principal component analysis.The raw spectra were pretreated by smoothing,multiple scattering correction and first-order derivatives,and then subjected to systematic principal component analysis.The results showed that normal chicken meat and alkaline-soaked chicken meat could be clearly classified.The classification models were es-tablished by different spectral preprocessing methods using the soft independent modeling method.The results showed that by preprocessing the sample spectra with the 7-point savizkg golag method,the classification models had the highest correct rate.The correct rate of correction back judgment was 77.08％-100％and the correct rate of prediction was 81.25％-100％.The study showed that the NIR spectral analysis technique is feasible for the rapid identification of alka-li-soaked chicken meat.
关键词
碱水浸泡鸡肉/近红外光谱技术/主成分分析Key words
alkali-soaked chicken meat/near-infrared spectroscopy/principal component analysis引用本文复制引用
基金项目
江苏省农业科技自主创新项目(CX212011)
扬州市社会发展项目(YZ2022090)
出版年
2024
国家科技期刊平台
NSTL
万方数据