Maca (Lepidium meyenii, synonym L. peruvianum) was analyzed using a systematic approach employing principal component analysis of flow injection mass spectrometry fingerprints (no chromatographic separation) to guide the selection of samples for metabolite profiling and DNA next generation sequencing. Samples consisted of 39 commercial maca supplements from 11 manufacturers, 31 unprocessed maca tubers grown in Peru and China, and a historic non-tuber maca sample from Peru. Principal component analysis of flow injection mass spectrometry fingerprints initially placed all the maca samples in three classes with similar chemical composition: commercial maca samples, tubers grown in Peru, and tubers grown in China. Metabolite profiling identified 67 compounds in the negative mode and 51 compounds in the positive mode. Compounds identified by metabolite profiling (macamides, glucosinolates, amino acids, fatty acids, polyunsaturated fatty acids, saccharides, imidazoles) were then used to identify ions in the flow injection mass spectrometry fingerprints. The tuber fingerprints were analyzed by factorial multivariate analysis of variance revealing that black, red, and yellow maca from Peru and black and yellow maca from China were compositionally different with respect to color and country. Critical ions were identified that allowed for the differentiation of maca between colors from the same country or between two countries with the same color. Genetically, all samples were confirmed to be L. meyenii based on next generation sequencing at three gene regions (ITS2, psbA, and trnL) and comparison to recorded sequences of vouchered standards.