食品科学

• 基础研究 • 上一篇    下一篇

基于介电频谱的枣果品种鉴别模型的建立

沈静波,李冬冬,张海红*,李子文,贾柳君   

  1. 宁夏大学农学院,宁夏 银川 750021
  • 出版日期:2017-02-15 发布日期:2017-02-28

Model Establishment for Variety Identification of Jujube Fruits Based on Dielectric Spectra

SHEN Jingbo, LI Dongdong, ZHANG Haihong*, LI Ziwen, JIA Liujun   

  1. College of Agriculture, Ningxia University, Yinchuan 750021, China
  • Online:2017-02-15 Published:2017-02-28

摘要: 利用LCR测试仪在1~1 000 kHz的频率范围内,选取55 个频率点,测定灵武长枣、冬枣和团枣的介电损耗因子?”频谱和相对介电常数?’频谱,通过主成分分析(principal component analysis,PCA)法和遗传算(geneticalgorithm,GA)法提取介电频谱的有效信息,并选取偏最小二乘判别分析(partial least squares discriminantanalysis,PLS-DA)、线性判别分析(linear discriminant analysis,LDA)和支持向量机(support vector machine,SVM)3 种方法进行枣果品种的鉴别模型研究。结果表明,频率和品种对枣果的介电参数均有显著性影响;用PCA与GA方法提取频谱有效信息的建模效果要优于原始频谱的建模效果;SVM法的建模效果要优于PLS-DA与LDA法的建模效果;以介电损耗因子?”建立的PCA-SVM模型优于介电常数?’的GA-SVM模型,其预测集的鉴别准确率为100%。因此,基于介电损耗因子?”频谱的PCA-SVM模型为枣果品种鉴别的最优模型。

关键词: 枣果, 介电频谱, 品种, 鉴别模型

Abstract: The dielectric loss factor ?’’ spectrum and relative dielectric constant ?’ spectrum of jujube fruits from three different varieties, Lingwu Changzao, Dongzao, and Tuanzao, were measured with an LCR meter at 55 selected frequency points in the frequency range of 1–1 000 kHz. Effective information from the dielectric spectra was extracted by principal component analysis (PCA) and genetic algorithm (GA). Models for variety identification of jujube fruits were established using partial least squares discriminant analysis (PLS-DA), linear discriminant analysis (LDA) and support vector machine (SVM), respectively. The results indicated that both the frequency and varieties had a significant influence on the dielectric parameters of jujube fruits. The model built using the effective information extracted by PCA and GA was better than that established the original spectra, and the SVM model was better than the PLS-DA and LDA models. The PCA-SVM model based on dielectric loss factor ?’’ was better than the GA-SVM model based on relative dielectric constant ?’, with the former model giving 100% correct discrimination for prediction set. Therefore, the PCA-SVM model based on dielectric loss factor ?’’ spectrum was optimal for variety identification of jujube fruits.

Key words: jujube fruit, dielectric spectrum, variety, identification model

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