玛咖及其制品的真实性是保障品质的关键。为了研究玛咖及其制品的差异,对玛咖制品进行真实性鉴别,分别以不同产地、色型的玛咖及玛咖制品为供试材料,对其进行高效液相色谱(high performance liquid chromatography,HPLC)指纹图谱不同识别方法的研究。采用Waters Symmetry ShieldTM C18(250 mm×4.6 mm,5 μm)色谱柱,乙腈-水为流动相梯度洗脱,检测波长210 nm,体积流量0.80 mL/min,各成分得到较好分离。经方法学验证,方法具有较好的精密度、重复性和稳定性。对19个玛咖样品和6个玛咖制品HPLC指纹图谱进行分析,确定了15个色谱峰为玛咖和其制品的特征指纹峰,建立了玛咖及其制品的指纹图谱。以数字化指纹图谱为基础,分别进行主成分分析、判别分析和相似度分析。结果表明,3种方法均能使玛咖与玛咖制品得到较为一致的模式识别结果。主成分二维平面图和判别分析能够区分玛咖和玛咖制品,具有简便、直观的特点,玛咖与玛咖制品相似度分析差异显著(P<0.05),分别为0.916和0.668,不同来源和色型的玛咖、玛咖制品间相似度均无显著差异(P>0.05)。结果显示玛咖制品具有玛咖的特征峰,但含量存在差异。3 种方法均能准确地体现指纹图谱的一致性和特征性,为玛咖和玛咖制品的区分及玛咖制品真实性保障提供了参考。利用HPLC指纹图谱可对玛咖及其制品的真实性进行鉴别。

Maca has many health benefits and high price in China and the products may be adulterated, so authenticity is important to its quality.In order to identify the authenticity of maca products and analyze difference of maca and its products, chromatographic fingerprint peaks identification and difference analysis were used at Yunnan Academy of Agricultural Sciences(YAAS), Kunming city, Yunnan province, China, in 2015.Common maca products including tablets and dry film were purchased on Kunming markets and different ecotypes and regions maca collected from Lijiang, Tibet and Huize, which have big planting scale with representative.Fresh maca samples were by natural drying and smashed to powder less than 60 mesh, then dried to constant weight by drier at 70 ℃.About 1.000 g dried sample was ultrasonic extraction under 200 MHz with 10 mL petroleum ether for 30 min, then filtered with filter paper, rotary evaporator was used to concentrate dry, added 5 mL acetonitrile to dissolve extract, and filtered by 0.45 μm filter membrane.Chromatographic peaks of maca were separated effectively by use A Waters Symmetry ShieldTM C18 column with a detection wavelength of 210 nm and a gradient program with acetonitrile water, and under 0.80 mL/min flow rate.According to the method validation, method has high precision, good repeatability and stability, and same batch maca samples chromatographic peaks relative retention time and relative peak area standard deviation relative values were less than 3.5% and 5%, respectively.19 batches of maca samples and 6 maca products fingerprint were analyzed, and the number 9 peak was set as reference peak to correct retention time because of separated complete, moderate appearance time, and larger peak area and all samples were existed.15 common characteristic peaks were determined of maca and its products basis retention time, their area accounted 92.5%-97.8% for total peak area, established the high performance liquid chromatography (HPLC) fingerprint of maca and its products, and digital fingerprint was also established based on relative retention time and corresponding peak area.Maca products common chromatographic peaks area were smaller compared with maca, and also contained some non common peaks, this explained some components were lose in process and other components was added.Fingerprint for maca (Lepidium meyenii Walp.) and maca products was investigated based on three different recognition methods such as principal component analysis(PCA), discriminant analysis(LDA) and similarity analysis.PCA was performed based on digital fingerprint.PCA extracted characteristic root was greater than 1, then 5 principal components were extracted representing the information of sample, and cumulative contribution rate was 100% with component loading matrix.Two dimensional scatter plot was drawn by use principal component 1 and 2 loading, so maca and its products can be distinguished by scatter plot.LDA divided samples into two categories, then chromatographic peaks area were as independent variable and one cross validation was used, and the classification result had 97.4% correct recognition rate for maca and its products.Maca samples could be distinguished obviously from maca product samples by using method of either two dimensional map or LDA.Similarity were calculated by included angle, and similarity analysis indicated that maca and its products have difference(P≤0.05), and similarity value were 0.916 and 0.668, respectively, and not only no significant differences(P≥0.05) between different origins and ecotypes maca, but also between maca products.Maca from Huize, Lijiang, Tibet were 0.882, 0.928 and 0943, respectively.Different ecotypes Maca of yellow, purple and blank were 0.920, 0.922 and 0.904, respectively.Maca dry film and tablets were 0.737 and 0.598, respectively.The results showed that each of the three employed methods could reflect consistent pattern recognition results and characteristics of fingerprint.The results showed that maca products have characteristic components of maca, but their content had differences.This could provide an identification method and reference for guaranteeing the authenticity and quality of Maca products.

TS207.7

云南省科技惠民专项(农业)重点项目(2014RA054)