Plant identification is a key component in regulating plant trade and controlling the entry of weedy, invasive and noxious species affecting crop production, human health and the environment. Among their aggressive mechanisms of colonization are: adaptability, high reproduction rates and cross herbicide resistance. For example Amaranthus palmeri is a prolific weed that has evolved herbicide resistance in multiple populations in the United States, and has impacted the production of crops like corn and soybean. While DNA barcoding is now commonplace in plant identification, a universal DNA plant barcode is absent and some taxa are not sufficiently resolved by typical plant barcoding genes like ITS, psbA, matK or rbcL. Additionally, alternative identification methodologies like protein biotyping are mostly limited to identification of microorganisms so far. We performed genome skimming using Illumina reads on 15 Amaranthus species and achieved high coverage (>500X) assembly of full chloroplast genomes, allowing design of 7 novel barcodes. The full genomes were also used to build a well-supported phylogenetic tree for the tested species. We also tested Matrix Assisted Laser Desorption/Ionization (MALDI) protein biotyping to see if seeds would provide consistent and distinctive protein spectra for species classification. Preliminary analysis with seeds from Brassicaceae showed clustering success between 80 and 100% for samples from the same species. The methodology was then applied to seeds of 17 amaranth species showing that protein spectra correctly clusters species of regulatory concern (e.g., A. palmeri and A. tuberculatus). Blind samples tested with the novel DNA barcodes and a protein biotyping database show good consistency and prediction of the phenotypical classification of the specimens with a few exceptions. Currently we are planning to increase efficiency of our DNA barcode pipeline by generating Nanopore-length barcodes, and accuracy of our protein biotyping by enriching the protein spectra library with more species and populations.