A statistical approach using sequentially principal component analysis (PCA) clustering and discriminant analysis was developed to disclose morphometric sperm subpopulations. In addition, we used a similar approach to disclose subpopulations of spermatozoa with different degrees of DNA fragmentation. It is widely accepted that sperm morphology is a strong indicator of semen quality and since the sperm head mainly comprises the sperm DNA, it has been proposed that subtle changes in sperm head morphology may be related to abnormal DNA content. Semen from four mongrel dogs (five replicates per dog) were used to investigate DNA quality by means of the sperm chromatin structure assay (SCSA), and for computerized sperm morphometry (ASMA). Each sperm head was measured for nine primary parameters: head area (A), head perimeter (P), head length (L), head width (W), acrosome area (%), midpiece width (w), midpiece area (a), distance (d) between the major axes of the head and midpiece, angle (θ) of divergence of the midpiece from the head axis; and four parameters of head shape: FUN1 (L/W), FUN2 (4π A/P2), FUN3 ((L – W)/(L + W)) and FUN 4 (π LW/4A). The data matrix consisted of 2361 observations, (morphometric analysis on individual spermatozoa) and 63 815 observations for the DNA integrity. The PCA analysis revealed five variables with Eigen values over 1, representing more than 79% of the cumulative variance. The morphometric data revealed five sperm subpopulations, while the DNA data gave six subpopulations of spermatozoa with different DNA integrity. Significant differences were found in the percentage of spermatozoa falling in each cluster among dogs (p < 0.05). Linear regression models including sperm head shape factors 2, 3 and 4 predicted the amount of denatured DNA within each individual spermatozoon (p < 0.001). We conclude that the ASMA analysis can be considered a powerful tool to improve the spermiogram.