食品科学2018，Vol.39Issue(6)：291-297,7.DOI:10.7506/spkx1002-6630-201806045
基于气味指纹图谱的玛咖品质快速鉴定方法
Rapid Identification of Maca Quality Based on Odor Fingerprint
摘要
Abstract
This work focused on 36 maca samples collected from 24 producing regions.Headspace odors from maca samples were collected and analyzed by an electronic nose (E-nose) and total glucosinolate content was determined by high performance liquid chromatography (HPLC).The correlation between glucosinolate contents and E-nose responses was analyzed by SPSS 22.0 statistical analysis software in an effort to build a model to rapidly identify maca quality using a soft independent modeling of class analogy (SIMCA) algorithm.The results showed a significant correlation between three sensors,T30/1,P30/1 and P30/2,and glucosinolates level.According to the resulting SIMCA models,the samples could be divided into three grades:grade 1 (glucosinolates content ≥ 10 mg/g),grade 2 (5 mg/g ≤ glucosinolates content ＜ 10 mg/g),and grade 3 (glucosinolates content ＜ 5 mg/g).The SIMCA models based on electronic nose data could allow rapid grading of maca quality according to its glucosinolates content.关键词
玛咖/芥子油苷/品质/电子鼻/气味指纹图谱/软独立建模分析Key words
maca/glucosinolate/quality/electronic nose/odor fingerprint/soft independent modeling of class analogy (SIMCA)分类
轻工纺织引用本文复制引用
党艳婷,段胜林,苑鹏,夏凯,韩晓峰,刘士伟,赵可心,周文萱,温霖,李爱民..基于气味指纹图谱的玛咖品质快速鉴定方法[J].食品科学,2018,39(6):291-297,7.基金项目
“十三五”国家重点研发计划重点专项(2016YFD0401303) （2016YFD0401303）
北京市科技重大专项(D171100001917003) （D171100001917003）
