基于近红外光谱定量分析花生牛奶可行性

发布时间：2019-02-28 16:49

【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。
[Abstract]:The different contents of peanut milk were prepared by simulating the production process of peanut milk. The quantitative analysis model was established by using near infrared spectrometer scanning, and the feasibility of applying near infrared spectroscopy to quantitative analysis of peanut milk was explored. The results showed that the PLS modeling method could effectively compensate the interference between peanut and milk powder, which was suitable for the analysis of the complex composition system of peanut milk. The calibration mean square deviation (root-mean-square error of calibration,RMSEC) and the predicted mean variance (root-mean-square error of predication,RMSEP) of the peanut quantitative analysis model were 0.573%, 3.73%, 0.999 7, and the correlation coefficients were 0.573%, 3.73% and 0.999 7, respectively. The RMSEC,RMSEP,R of quantitative analysis model of milk powder was 0.066, 0.183 g / L, 0.955 7, respectively. Near infrared spectroscopy (NIR) can be applied to quantitative analysis of peanut milk. It can provide product quality control and rapid quantitative detection for peanut milk and provide a new way to detect vegetable protein beverage. The optimization of the model needs to be further studied.
【作者单位】： 山东理工大学生命科学学院;山东理工大学分析测试中心;
【基金】：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)
【分类号】：O657.33;TS275.4
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本文编号：2431978