Numerical classifications in biology have been based on genetics and phylogenetics. This research report presents the case of developing a strategy for an objective ordering and numerical classification in terms of fruit mass and shape (prickly pear, tuna, or nochtli) of the genus Opuntia. The advantages of principal components (PC’s) in ordering Opuntia accessions are described, and the convenience of using cluster analysis for the same purpose is discussed. A way of defining the number of groups on statistical fundaments is described. Likewise, the importance of involving fruit attributes with higher prediction value is considered, as well as a correct strategy attribute scale and weighing. The first two PC explain 62 % of the total variation from eight variables (total weight, skin weight, edible portion weight, polar diameter (PD), equatorial diameter (ED), volume ratio, and sugar content (°brix) of 29 accessions of prickly pear cactus. The orthogonal space defined by PC1 and PC3 identifies the accessions ‘Mango’, ‘Burrona 1’ and ‘Naranjón Legítimo’ as the genotypes with the most skin, an attractive feature for post-harvest handling. Cluster analysis, using Euclidean distance as a similarity index, helped to differentiate five statistically different groups, and the accession ‘Tapon Aguanoso’ made a group of its own, which was explained because it’s the only wild material of the 29 studied.

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