Confirming the statement from Shlens (2009), that is, that the goal of PCA is to identify the most meaningful basis to reexpress a dataset, the results obtained in this work show that the careful selection and suitable preparation of samples together with the precise collection of spectral signature data and the application of an adequate statistical analysis like PCA conform a powerful and reliable technique to recognize and classify plants, allowing us to identify the origin of a given vegetable sample. That technique could be considerably improved by developing a database of standardized spectral signatures of the main crops in each stage and status. This could be the basis for higher level of plant and crop analysis, allowing us the prediction, diagnosis, and solution of different health and phenologic affections of plants.