Research On Maca Authenticity Identification Based On Multispectral Imaging Technology And Metabolomics Technology

Maca(Lepidium meyenii Walp.)is a herbaceous plant of the Brassicaceae family,native to the high altitudes of the Andes mountains,it's rich in nutrients and health benefits.Since Maca powder was approved as new resource food by the former ministry of health of China in 2011,Maca industry has developed rapidly,but at the same time,the phenomenon of adulteration has also occurred frequently,which seriously affects the normal development of Maca market and damages the rights and interests of consumers.In order to solve the above problem,in this research,Maca as research object,low-cost turnip as adulterative object,the multispectral imaging technology was used for rapid identificationofMacaanditsadulterants,ultraperformanceliquid chromatography-quadrupole time-of-flight mass spectrometry(UPLC-QTOF-MS)based on metabonomics was applied to identify the origin and authenticity of Maca.The main results are as follows:1.The feasibility of authentication of Maca based on multispectral imaging technology combined with chemometrics was studied.Establishing the classification model based on support vector machine(SVM),back propagation neural network(BPNN)and genetic algorithm optimization support vector machine(GA-SVM)to distinguish Maca and its adulterants.The results showed that the classification accuracy of GA-SVM and BPNN models was 100%.Next,the adulteration ratio of adulterants mixed to Maca powder was quantitatively predicted by partial least squares(PLS)and least squares support vector machine(LS-SVM).The results showed that LS-SVM had better predictive effect than PLS,and the predictive decision coefficient(R_p~2)and root mean square error(RMSEP)were 0.994 and 2.675%,respectively.It has been proved that multispectral imaging technology combined with stoichiometry can be used as a rapid method to identify the authenticity of Maca.2.Authentication of Maca was carried out by UPLC-QTOF-MS.Metabolite fingerprinting was obtained and subjected to multivariate statistical analysis.Maca and its adulterants were distinguished by orthogonal partial least-squares discriminant analysis(OPLS-DA)chemometrics.Untargeted metabolomics method was used to identify the characteristic markers of Maca and its adulterants.Firstly,the biomarker was selected and the mass spectrometry information was extracted.Then the molecular formula and structure were identified by MS-FINDER software.The markers were compared with the primary and secondary mass spectral information of HMDB and Metlin online database.Standards were found to verify the markers.Finally,15 marker metabolites of Maca and its adulterants were identified,which can be used for authenticity identification of Maca.The results showed that the UPLC-QTOF-MS based on metabolomics technology could be used for the identification of Maca and its adulterants.3.Maca origin identification was researched based on the information dependent acquisition(IDA)directed UPLC–QTOF-MS,combined with OPLS-DA chemometrics method successfully distinguished five origins of Maca.According to the targeted metabolomics method,isotope pattern matched peak mining was performed using Extracted Ion Chromatogram(XIC)manager within the Peakview software,and 7 kinds of Maca metabolites were identified,including macamides,macaene,glucosinolates,alkaloids,sterols,polyphenols and flavonoids.The distribution of Maca metabolites in different origin was analyzed.The results showed that the quality and the content of Maca metabolites were influenced by the origin.