食品科学 ›› 2017, Vol. 38 ›› Issue (24): 189-195.doi: 10.7506/spkx1002-6630-201724030

• 安全检测 • 上一篇    下一篇

基于近红外光谱定量分析花生牛奶可行性

范睿,孙晓凯,周欣,陈杰,牛金叶,孙发哲,孔玲,陈志伟   

  1. (1.山东理工大学生命科学学院,山东?淄博 255000;2.山东理工大学分析测试中心,山东?淄博 255000)
  • 出版日期:2017-12-25 发布日期:2017-12-07
  • 基金资助:
    国家自然科学基金面上项目(31071538);山东省自然科学基金重点项目(ZR2013FB001); 山东省大型科学仪器升级改造项目(2011SJGZ10)

Feasibility of Quantitative Analysis of Peanut Milk Based on Near Infrared Spectroscopy

FAN Rui, SUN Xiaokai, ZHOU Xin, CHEN Jie, NIU Jinye, SUN Fazhe, KONG Ling, CHEN Zhiwei   

  1. (1. School of Life Sciences, Shandong University of Technology, Zibo 255000, China;2. Analysis and Test Center, Shandong University of Technology, Zibo 255000, China)
  • Online:2017-12-25 Published:2017-12-07

摘要: 模拟花生牛奶生产工艺制备不同含量的花生牛奶,使用近红外光谱仪扫描建立定量分析模型,探索近红外光谱应用于花生奶定量分析的可行性。结果表明,花生牛奶使用PLS建模方法可以有效地对光散射、花生与奶粉之间的干扰做出补偿,适合用于花生牛奶复杂成分体系的分析;花生定量分析模型校正均方差(root-mean-square error of calibration,RMSEC)、预测均方差(root-mean-square error of predication,RMSEP)、相关系数R分别为0.573%、3.73%、0.999?7;奶粉定量分析模型RMSEC、RMSEP、R分别为0.066、0.183?g/L、0.955?7。近红外光谱可以应用于花生牛奶的定量分析,可以为花生牛奶提供产品质量控制和快速定量检测,为植物蛋白饮料提供一种新的检测思路。模型优化改进有待进一步研究。

关键词: 花生牛奶, 花生, 奶粉, 近红外, 定量分析

Abstract: This study focused on the feasibility of using near infrared (NIR) spectroscopy for quantitative analysis of peanut milk. Simulated peanut milk samples were prepared by mixing different amounts of milk powder with peanut slurry and they were scanned by NIR. A quantitative analysis model was established based on the spectra obtained. The results demonstrated that the PLS modeling method could effectively make up for the light scattering and the interference between peanut and milk powder, and thus it could be applied to analyze such complex systems as peanut milk. The root-mean-square error of calibration (RMSEC), root-mean-square error of predication (RMSEP) and correlation coefficient (R) of the quantitative analysis model were 0.573%, 3.73% and 0.999 7 for peanut and 0.066, 0.183 g/L, and 0.955 7 for milk powder, respectively. In conclusion, NIR spectroscopy could be used in the rapid quantitative analysis of peanut milk. However, further study is needed on the model.

Key words: peanut milk, peanut, milk powder, near infrared spectroscopy, quantitative analysis

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