浦城薏米粉水分和还原糖的近红外光谱快速检测模型优化

Optimization of model for rapid detection of moisture and reducing sugar in Pucheng semen coicis powders by near infrared spectroscopy

中文关键词:  薏米粉  近红外光谱  定量模型  快速检测

英文关键词:semen coicis powders  near infrared spectroscopy  quantitative model  rapid detection

中文摘要:

      目的 建立浦城薏米粉水分和还原糖的近红外光谱快速检测模型。方法 采集浦城薏米粉样品的近红外光谱图, 使用6种不同方法对样品的原始光谱分别进行预处理, 在全波段10000~4000 cm?1范围内建立薏米粉偏最小二乘法(partial least squares, PLS)的定量分析模型。结果 浦城薏米粉原始光谱在标准正态变换(standard normal variate, SNV)预处理后确定水分含量最佳模型的光谱波段(5944~5590 cm?1), 主因子数为7, 校正决定系数(determination coefficient of calibration, Rc2)为0.9904, 均方根误差(root mean square error, RMSEC)为0.0631; 在二阶导数法(second derivative, SD)预处理后确定还原糖含量最佳模型的光谱波段(9845~7386 cm?1), 主因子数为6, Rc2为0.9998, RMSEC为0.0187。在上述条件下, 水分和还原糖含量的验证集相关系数(determination coefficient of prediction, Rp2)分别为0.9902和0.9989, 验证均方根(root mean square of prediction error, RMSEP)分别为0.0693和0.0698。结论 经验证, 该模型可以实现浦城薏米粉中水分和还原糖含量的快速无损检测。

英文摘要:

      Objective To establish a near infrared spectroscopy rapid detection model of moisture and reducing sugar in Pucheng semen coicis powders. Methods The near infrared spectra of Pucheng semen coicis powders samples were collected, and the original spectra of the samples were pretreated by 6 kinds of different methods. The partial least squares (PLS) quantitative analysis model of the Pucheng semen coicis powders were established in the range of 10000-4000 cm?1. Results The spectral bands (5944-5590 cm?1) of the optimal model for moisture content were determined after the pretreatment of the original spectrum with standard normal variate (SNV) in Pucheng semen coicis powders. The principal factor number was 7, the correction determination coefficient of calibration (Rc2) was 0.9904, and the root mean square error (RMSEC) was 0.0631. The spectral bands (9845-7386 cm?1) of the optimal model for reducing sugar content were determined after second derivative (SD) pretreatment. The principal factor number was 6, Rc2 was 0.9998, and the RMSEC was 0.0187. Under the above conditions, the determination coefficient of prediction (Rp2) for moisture and reducing sugar content were 0.9902 and 0.9989, respectively, and the root mean square of prediction error (RMSEP) were 0.0693 and 0.0698, respectively. Conclusion It has been verified that this model can realize rapid and nondestructive detection of moisture and reducing sugar content in Pucheng semen coicis powders.