基于气味指纹图谱的玛咖品质快速鉴定方法

摘要

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.%以玛咖为研究对象,通过高效液相色谱和电子鼻分别测定24个产区36个玛咖样品中芥子油苷的总含量和气味传感器的响应值原始数据.基于玛咖样品中芥子油苷的总含量和传感器响应值的相关性分析结果,采用软独立建模分析(soft independent modeling class analogy,SIMCA)算法建立玛咖品质快速鉴定模型.结果表明:T30/1、P30/1、P30/2三根传感器与芥子油苷含量之间存在显著相关性,根据3根传感器建立的SIMCA模型可以将不同玛咖样品分为3个等级:一等品(芥子油苷含量≥10 mg/g)、二等品(5 mg/g≤芥子油苷含量＜10 mg/g)、三等品(芥子油苷含量＜5 mg/g).运用电子鼻气味检测数据结合SIMCA模型可以快速鉴别玛咖的等级,还可推测出所测样品中芥子油苷的含量区间.