Search

In endangered donkey populations, reproductive performance is one the most important areas to study, provided its connection with conservation opportunities. Among reproductive traits, testicular dimensions, their relationship with body weight and seminal qualitative and quantitative parameters is particularly notable. The aim of the present study was to model the evolution of body weight, testicular length, width and height, volume and gonadosomatic index in Miranda donkeys using in vivo ultrasonography. Data on the aforementioned variables of 23 Miranda donkeys, from 4 to 259 months of age, were fitted to eleven linear and nonlinear models. Cubic function modelling reported the best-fitting properties for almost all variables, except for body weight (sigmoid curve model). Cubic model presented a higher ability to capture interindividual variability (Adj. R2 from 0.795 to 0.922) for testicular height, width, length and volume measurements than the rest of fucntions tested. Bayesian information criterion (BIC) values suggest in vivo ultrasonography may be a rather efficient and accurate tool when predicting for the evolution of testicular volume or gonadosomatic index than three-dimensional testicular measurements. Cubic functions efficiently model testicular dimensions, volume and composite indices evolution. Ultrasonography objectively, accurately and reproducibly determines testicular volume. Testicular asymmetry physiologically occurs to balance bilateral testicular activity. [ABSTRACT FROM AUTHOR]

Simple Summary: The prediction of sperm output and other reproductive traits based on testicular biometry is an important tool in the reproductive management of stallions. Nevertheless, corresponding research in donkeys remains scarce. 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. Although research on female reproductive physiology has made crucial advances, much less is known about the physiology of the male. In the present work, two Bayesian models were built to predict for sperm output and quality parameters in donkeys. Models included combinations of age as a covariate and biometric and testicular measurements as independent factors. Results evidenced that the goodness-of-fit was similar for both models—hence, the combination of biometry and testicular factors presented improved predictive power. 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. 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). 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. 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. 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. 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 (%). 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). The application of the present models may be useful to gather relevant information that could be used hereafter for assisted reproductive technologies. [ABSTRACT FROM AUTHOR]