基于超快速电子鼻对生乳快速鉴别及应用OACSTPCD

The odor information of raw milk from different regions was quickly identified and the application of abnormal milk was detection by ultra-fast electronic nose detection.Raw milk samples selected from five different regions(Bayannur,Dalate County,Horinger,Liangcheng and Ningxia)were detected by ultra-fast electronic nose,and fingerprints were established.Combined with retention index and AroChemBase database,the aroma components of raw milk samples were qualitatively analyzed.The aroma characteristics of raw milk were classified,predicted and quickly identified by principal component analysis(PCA),soft independent modeling of class analysis(SIMCA)and discriminant factor analysis(DFA).The results showed that different samples could be quickly distinguished,and significant differences were observed in the peak area content of isopropanol and 2-butanone in raw milk samples from the five regions.In addition,compared with raw milk,the main differing compounds in abnormal milk were ethanol,3-methylbutanal,2-methylbutanal,2-ethyl furan and 3-methylbut-2-en-1-ol,and some unpleasant smells such as malt taste,fermented taste,sour taste and greasy taste were produced in abnormal milk.The cumulative discriminant index of DFA discriminant factor was 100%,which could effectively distinguish raw milk from abnormal milk.To sum up,ultra-fast electronic nose could well analyze the odor information of raw milk,and quickly and effectively identify the quality of raw milk.