CAJ | 학술논문

利用傅里叶变换红外光谱法（FTIR）结合软独立模式分类法（SIMCA）对不同类别的牛奶进行识别。通过对光谱数据基线校正和Savitzky-Golay平滑处理后,在3100～850cm-1光谱区域,利用留一交互验证法建立获得主成分分析（PCA）最优模型。在α=5%显著水平下,最优模型对纯牛奶、低乳糖奶、低脂奶和高蛋白奶的识别率分别为80%、80%、100%和80%,拒绝率分别为93%、100%、100%和93%。表明FTIR结合SIMCA可成为快速识别牛奶类别的有效方法。
이용부리협변환홍외광보법（FTIR）결합연독립모식분류법（SIMCA）대불동유별적우내진행식별。통과대광보수거기선교정화Savitzky-Golay평활처리후,재3100～850cm-1광보구역,이용류일교호험증법건립획득주성분분석（PCA）최우모형。재α=5%현저수평하,최우모형대순우내、저유당내、저지내화고단백내적식별솔분별위80%、80%、100%화80%,거절솔분별위93%、100%、100%화93%。표명FTIR결합SIMCA가성위쾌속식별우내유별적유효방법。
Fourier transform infrared spectroscopy（FTIR） combined with soft independent modeling of class analogy（SIMCA） method was employed to the identification of different varieties of milk.The optimized PCA model was built by leave-one-out cross-validation（LOOCV） method after series of pre-treatments such as baseline correction and Savitzky-Golay smoothing in the region of 3100 — 850 cm-1.Under the α =5% significance level,the identification rates of this model for pure milk,low lactose milk,low fat milk and high protein milk were 80%,80%,100% and 80%,respectively,and the rejection rates were 93%,100%,100% and 93%,respectively.This indicates that FTIR combined with SIMCA is a valid method for rapid identification of different varieties of milk.