食品科学 ›› 2019, Vol. 40 ›› Issue (8): 262-269.doi: 10.7506/spkx1002-6630-20180318-226

• 安全检测 • 上一篇    下一篇

高光谱成像技术快速预测鸡蛋液菌落总数

赵 楠,刘 强,孙 柯,王 瑶,潘磊庆,屠 康,张 伟   

  1. 1.南京农业大学食品科技学院,江苏 南京 210095;2.南京晓庄学院食品科学学院,江苏 南京 211171
  • 出版日期:2019-04-25 发布日期:2019-05-05
  • 基金资助:
    国家自然科学基金青年科学基金项目(C200701;31601544);江苏省高校自然科学研究面上项目(16KJD550001)

Rapid Prediction of Total Viable Count of Bacteria in Liquid Egg Using Hyperspectral Imaging Technology

ZHAO Nan, LIU Qiang, SUN Ke, WANG Yao, PAN Leiqing, TU Kang, ZHANG Wei   

  1. 1. College of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, China; 2. School of Food Science, Nanjing Xiaozhuang University, Nanjing 211171, China
  • Online:2019-04-25 Published:2019-05-05

摘要: 针对鸡蛋液中菌落总数分析方法操作繁琐、时效性低等问题,采用高光谱成像技术(400~1 000 nm)建立鸡蛋液中菌落总数的快速预测方法。于蛋清中接种铜绿假单胞菌后采集不同污染程度蛋液样本的原始高光谱信息,结合连续投影算法进行特征波段的提取,分别建立基于特征波段和全波段光谱信息下的偏最小二乘和支持向量机(support vector machine,SVM)预测回归模型。结果表明:标准化预处理效果相对最佳,蛋清、蛋黄以及全蛋液样本对应的相对最佳定量分析模型为基于特征波段下的SVM模型。其中蛋清预测集相关系数RP为0.81,预测集均方根误差(root mean square error of prediction,RMSEP)为0.63(lg(CFU/g));蛋黄预测集的RP为0.82,RMSEP为0.47(lg(CFU/g));全蛋液样本中RP为0.75,RMSEP为0.75(lg(CFU/g))。结果表明,高光谱成像技术结合化学计量学方法,可以实现对鸡蛋内部微生物污染程度的定量预测。

关键词: 鸡蛋液, 菌落总数, 高光谱成像, 模型, 快速预测

Abstract: The traditional method for detecting the total viable count of bacteria in liquid egg is laborious and time consuming. To overcome these drawbacks, the present study was undertaken to develop a fast method for predicting the total viable count of bacteria in liquid egg by using hyperspectral image technology (400–1 000 nm). The hyperspectral images of artificially inoculated liquid egg samples with different contamination levels of Pseudomonas aeruginosa were acquired. Then successive projections algorithm (SPA) was used to extract feature wavelengths, and partial least squares (PLS) and support vector machine (SVM) models were developed based on the feature wavelengths and the full spectra, respectively. Finally, the performance of the multivariate prediction models were compared and analyzed. The result showed that the Autoscale method was the best pretreatment method and the SVM model was the best prediction model for the total viable count of bacteria in liquid egg. The correlation coefficient of prediction (RP) and the root mean square error of prediction (RMSEP) was 0.81 and 0.63 (lg(CFU/g)) for egg white, 0.82 and 0.47 (lg(CFU/g)) for egg yolk, 0.75 and 0.75 (lg(CFU/g)) for liquid whole egg, respectively. Overall, hyperspectral imaging combined with chemometrics enables quantitative prediction of the degree of microbial contamination in liquid egg.

Key words: liquid egg, total viable count of bacteria, hyperspectral imaging technology, model, fast prediction

中图分类号: