白酒基酒中酮类物质的近红外光谱检测方法

Rapid Detection of Ketones in Base Liquor by Near Infrared Spectroscopy

应用近红外光谱技术建立了白酒基酒中2,3-丁二酮和3-羟基-2-丁酮的快速检测模型。从洛阳杜康酒厂选取182个白酒基酒样品为材料,运用气相色谱法测得两种物质的化学值,同时采集其在12000~4000 cm^-1范围内的光谱数据,采用偏最小二乘法(PLS)结合内部交叉验证建立校正模型。通过对比不同光谱预处理下PLS模型效果对其进行优化,确定2,3-丁二酮和3-羟基-2-丁酮的最佳预处理方法分别为一阶导数+多元散射校正和二阶导数,最佳光谱区间分别为9403.2~7497.9 cm^-1和9403.2~7497.9 cm^-1+6101.7~5449.8 cm^-1。优化后2,3-丁二酮和3-羟基-2-丁酮校正集样品的化学值和近红外预测值的决定系数(R2)分别为0.9602和0.9632,交叉验证均方根误差(RMSECV)分别为0.39、0.22 mg/100 mL;通过外部检验,验证集样品的R2分别为0.9576和0.9578,预测均方根误差(RMSEP)分别为0.40、0.24 mg/100 mL。结果表明,应用近红外光谱技术结合化学计量学方法所建立的模型有较高的准确度,能够满足白酒生产中酮类物质的快速检测需要。

A rapid detection model for 2,3-butanedione and 3-hydroxy-2-butanone in base liquor was established using near infrared spectroscopy(NIR).182 base liquor samples from Dukang winery in Luoyang were selected as materials.The chemical values of the two ketones were detected by gas chromatography(GC).Meanwhile,the spectral data in the range of 12000-4000 cm^-1 were collected.The calibration models for 2,3-butanedione and 3-hydroxy-2-butanone were established by partial least square(PLS)combined with internal cross-validation.By comparing effects of the PLS models under different spectral pretreatments for optimization,the optimal preprocessing methods for 2,3-butanedione and 3-hydroxy-2-butanone were determined as first derivative with multiple scattering correction and second derivative,respectively,while the optimal spectral ranges are 9403.2-7497.9 cm^-1 and 9403.2-7497.9 cm^-1+6101.7-5449.8 cm^-1.The determination coefficients(R2)for the chemical values and the NIR predicted values of the 2,3-butanedione and 3-hydroxy-2-butanone calibration set samples after optimization were 0.9602 and 0.9632,while the corresponding root mean square errors of cross-validation(RMSECV)were 0.39 mg/100 mL and 0.22 mg/100 mL,respectively.Through external validation,the R2 for the validation set samples were 0.9576 and 0.9578,while the predicted root mean square errors(RMSEP)were 0.40 mg/100 mL and 0.24 mg/100 mL,respectively.Results showed that the model established by near infrared spectroscopy combined with chemometrics could meet the requirements for rapid detection of ketones in liquor production with high accuracy.