摘要
根据近红外光谱的振动吸收强度与有机分子官能团含量的线性关系 ,用偏最小二乘法 ,对啤酒的近红外光谱与其中的酒精度、原麦汁浓度以及总酸含量等 3种主要成分进行了线性回归 ,并建立起相关的模型。用该模型对未知啤酒样品中的上述 3种成分的含量进行预测 ,取得了令人非常满意的结果。可望作为啤酒厂的一种快捷而准确的检测方法予以推广。
Based on the proportional relationship between the intensity of the Fourier transform-near-infrared spectrum (FF-NIR) with the content of the functional groups in organic compound, the linear regression of partial least square (PLS) was applied to the NIR spectra of beer with their concentration of alcohol and original oast as well as total acids contents in beer, and a quantitative model for the determination of alcohol, original oast and total acids in beer has been established. Using this model to predict the contents of above 3 components of unknown beer samples, the very satisfactory results were obtained.
出处
《分析化学》
SCIE
EI
CAS
CSCD
北大核心
2004年第8期1070-1073,共4页
Chinese Journal of Analytical Chemistry
关键词
啤酒
成分分析
近红外光谱法
偏最小二乘法
线性回归
beer
quantitative analysis
Fourier transform-near infrared spectroscopy
partial least square
linear regression
