枣醋发酵液中pH值与总酸含量的高光谱图像技术定量分析

Determination of pH and total acid content in fermented liquid of jujube vinegar by hyperspectral image technology

利用高光谱图像技术(HS-IT)对灵武枣醋发酵过程中pH值和总酸含量进行定量分析,并通过偏最小二乘法(PLS)建立定量分析模型,同时采用竞争性自适应加权算法(CARS)和遗传算法(GA)对整个谱区进行特征波长筛选。以决定系数(R2)、预测均方根偏差(RMSEP)、相对分析误差(RPD)以及最佳主因子数作为模型质量的评价参数,其中使用CARS进行的波长筛选法对模型的优化效果最佳,pH值和总酸含量的R2分别达到0.928 4和0.935 1,RMSEP分别为0.122 6和0.301 5,RPD分别为3.75和3.91。结果表明,CARS-PLS法可提高枣醋发酵液中pH值与总酸含量预测模型的准确度和稳定性。

The pH and total acid content during Wuling jujube vinegar fermentation were quantitatively analyzed by hyperspectral image technology(HS-IT), and the quantitative analysis model was established by partial least squares(PLS). However, the characteristic wavelength of the whole spectrum region was screened by competitive adaptive reweighted sampling(CARS) and genetic algorithm(GA). Using the determination coefficient(R2),root mean square error of prediction(RMSEP), relative percent deviation(RPD) and number of prime factors as the evaluation parameters of model quality, the optimum optimization effect of the model was the wavelength screening method with CARS. The R2, RMSEP and RPD of pH and total acid content were 0.928 4 and 0.935 1, 0.122 6 and 0.301 5, 3.75 and 3.91, respectively. The results showed that CARS-PLS could improve the accuracy and stability of prediction models of pH and total acid content in fermented liquid of jujube vinegar.