The domestic donkey (Equus asinus) in Nigeria just like other donkeys around the World are being used as sources of transportation in carrying building materials like building stones, bricks, tiles, lime, sand, embankments, garbage (Madani et al., 2018) and for carrying farm produce (Blench, 2004b). In Nigeria, about 16,000 donkeys are annually transported from the north to the southern part of the country for the sole purpose to consumption as meat (Blench, 2004b). However, in China, this species has become an economically important animal because the meat has been found not to only have high nutritional value but most importantly, the collacoriiasini (donkey-hide glue) present is popularly used as a strong traditional Chinese medicine (Di et al., 2017). To the credit of this animal is also the production of milk for children who are allergic to bovine milk (Carrocio et al., 2000; Muraro et al., 2002) or who suffer from multiple food intolerances (Monti et al., 2012). Morphometric measurements have been found useful in contrasting size and shape of animals (Ibe and Ezekwe, 1994; Ajayi et al., 2008). These quantitative measurements for size and shape are essential for estimating genetic parameters in animal breeding activities (Chineke, 2000). Also, the morphological characteristics are inexpensive and assess the environmental influence on traits (Mondini et al., 2009). Some morphological characters such as morphometric traits are correlated with bodyweight (Ajayi et al., 2012). Thus, such morphometric traits could be used as markers in body weight improvement programmes and body weight predictors (Musa et al., 2018). However, correlations between body dimensions may be different if the dimensions are treated as bivariate rather than multivariate. This could be noticeable interrelatedness or lack of orthogonality of the explanatory variable. Therefore, employing the use of multivariate analysis like the principal component analysis (PCA) would be able to handle and cater for this limitation (Yakubu et al., 2009). Likewise, this technique of using PCA or multivariate method is capable of defining the underlying structure among variables through exploratory or confirmatory means (Hair et al., 2010) and yield more reliable predictions and classification.
Principal component analysis is a weighted linear combination of correlated variables, explaining a maximal amount of variance of the variable (Truxillo, 2000). Relationships from PCA analysis have been reported to exist among linear body traits in goats and other species which provide useful information on performance, productivity and carcass characteristics (Shoyombo et al., 2015). Animal breeders in particular are interested in the genetic zoo-diversity which represents a reason or resource to draw on to select, develop and improve exiting animals and new breeds. More broadly, genetically diverse livestock populations provide society with a wider range of options to meet the challenges of the future (Madani et al., 2018). It is on this basis therefore, that the study was conducted to have information on the effect of age and sex on the morphometric traits of donkeys reared on a research station in Shika, Zaria, Nigeria using principal component analysis.