Still, contextually, corresponding publications on male donkey remain scarce. Studies on equine testicular biometry are fairly common, and the correlation between testicular dimensions and the capacity for sperm production has frequently been addressed in the literature, allowing the establishment of a predictive formula for daily sperm output (DSO). Measuring testicular size reports an approximate measurement of the amount of testicular parenchyma present in a certain individual, which in turn determines the potential for sperm production. The application of the present models may be useful to gather relevant information that could be used hereafter for assisted reproductive technologies. Alternatively, the combination of predictors in model 2 evidenced higher predictive power for total sperm number (×10 9), morphologically normal spermatozoa (%), and total motile sperm count (×10 9).
Although goodness-of-fit was similar, the combination of predictors in model 1 evidenced higher likelihood to predict gel-free volume (mL), concentration (×10 6/mL), and motility (%). Predictive model 1 comprised the covariate of age and the independent factors testicular measurements (length, height and width), while model 2 included the covariate of age and the factors of BW, testicular volume, and gonadosomatic ratio. Bayesian linear regression analyses were considered to build two statistical models using gel-free volume, concentration, total sperm number, motility, total motile sperm, and morphology as dependent variables.
Testicular morphometry was ultrasonographically obtained from 23 donkeys (six juveniles and 17 adults), while 40 ejaculates from eight mature donkeys were analyzed for sperm output and quality assessment. The aim of the present study is to define and compare the predictive power of two different Bayesian models for donkey sperm quality after the evaluation of linear and combined testicular biometry indices and their relationship with age and body weight (BW). The application of these models may assist in the process of making decisions in respect to the reproductive/biological, clinical, and selection handling of the animals.
Results evidenced that the goodness-of-fit was similar for both models-hence, the combination of biometry and testicular factors presented improved predictive power. Models included combinations of age as a covariate and biometric and testicular measurements as independent factors. In the present work, two Bayesian models were built to predict for sperm output and quality parameters in donkeys. Although research on female reproductive physiology has made crucial advances, much less is known about the physiology of the male. Several donkey breeds in Europe face a compromising threat of extinction, which has been accelerated by the low renovation of populations and their inbreeding levels. Nevertheless, corresponding research in donkeys remains scarce. The prediction of sperm output and other reproductive traits based on testicular biometry is an important tool in the reproductive management of stallions. Alternatively, the combination of predictors in model 2 evidenced higher predictive power for total sperm number (×109), morphologically normal spermatozoa (%), and total motile sperm count (×109). Although goodness-of-fit was similar, the combination of predictors in model 1 evidenced higher likelihood to predict gel-free volume (mL), concentration (×106/mL), and motility (%).
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