Records from the milk recording scheme of Spanish Murciano-Granadina goats were studied to estimate genetic (co)variance components and breeding values throughout the first and second lactations. The data used consisted of 49,696 monthly test-day records of milk (MY), protein (PY), fat (FY), and dry matter (DMY) yields from 5,163 goats, distributed in 20 herds, offspring of 2,086 does and 206 bucks. These records were analyzed by 2-trait random regression models (RRM) and a repeatability test-day model (RTDM). At the middle of lactation, heritability estimates for MY, DMY, and FY obtained with RTDM were larger than those estimated with RRM, and the opposite was true for PY. The RRM estimates of heritability for MY, FY, and PY were very similar throughout the trajectories of both lactations. Heritability estimates for DMY decreased through the lactation period. The genetic correlations between the first and second lactation records estimated for all traits by RRM were positive and ranged from 0.43 to 0.80 throughout the lactation curves. The correlation between BV estimated with RTDM and RRM was 0.742 for MY and 0.664 for DMY. The RRM could be a useful alternative to RTDM for the prediction of BV in this breed.
Monthly test-day records of milk yield and composition in Murciano-Granadina (MG) and Payoya (PYA) dairy goats were combined with weather data from meteorological stations, to analyse the effects of heat stress on dairy traits, measured with an index of temperature and relative humidity (THI). A 'repeatability animal model' and a 'reaction norm animal model' were used to estimate genetic (co)variance components. Estimates obtained with both models were very similar. The h(2) of daily yields in MG did not vary throughout the THI scale, but the pattern of variation of content traits showed negative trends for increasing THI values. In PYA, a slight positive tendency throughout the THI scale was observed for the same traits. The genetic correlations between subsequent points in the THI scale were lower than 0.80 when they were computed between low and high THI points. The same reaction norm was observed for all traits. Using the 'reaction norm animal model', it was possible to identify those animals that show the same performance throughout the THI trajectory (robust) and those with varying performances (tolerant and non-tolerant to heat stress). Results in this study also show that heat tolerance decreases, while the genetic level for milk traits increases. Losses because of heat stress were equivalent to 1.9 and 3.1% in the yearly yield of fat and protein for MG and PYA, respectively.
Aim:This study quantified the effects of season and photoperiodic treatment on semen and seminal plasma (SP) characteristics in 12 bucks of two Spanish goat breeds (Murciano-Granadina, and Payoya) for the past 1 year.Materials and Methods:A total of 6 bucks (three of each breed) were exposed to the natural day length and the other six males (three of each breed) were exposed to alternating conditions of 2 months of long days (16 h light) and 2 months of short days (8 h light). Weekly concentrations of glutamic oxaloacetic transaminase/aspartate aminotransferase (GOT/AST), lactate dehydrogenase (LDH), potassium, testosterone, and protein in SP were measured. Reaction time and scrotal circumference were recorded, and plasma testosterone concentrations were measured before semen collection.Results:Sperm volume, LDH, and potassium concentration in SP, and reaction time did not differ significantly between breeds, seasons, and photoperiodic treatment. Sperm concentrations were higher (p<0.001) in spring and summer than they were in autumn and winter. Mean percentage of positive hypo-osmotic swelling test sperm was the highest in summer and under the artificial photoperiod (p<0.01). GOT/AST concentrations differed (p<0.01) between breeds and seasons. Breed, season, and photoperiod had significant (p<0.001) effects on protein and testosterone levels in SP. Plasma testosterone concentrations were highest in summer (p<0.001), and differed significantly (p<0.01) between breeds. Scrotal perimeter differed significantly (p<0.001) between breeds and photoperiod.Conclusion:Recognition of those seasonal and breed-specific differences in the performance of bucks should help to improve the management of individual semen samples for use in artificial insemination programs.
A total number of 1092 artificial inseminations (AIs) performed from March to May were documented over four consecutive years on 10 Payoya goat farms (36° N) and 19,392 AIs on 102 Rasa Aragonesa sheep farms (41° N) over 10 years. Mean, maximum, and minimum ambient temperatures, mean relative humidity, mean solar radiation, and total rainfall on each insemination day were recorded. Overall, fertility rates were 58 % in goats and 45 % in sheep. The fertility rates of the highest and lowest deciles of each of the meteorological variables indicated that temperature and rainfall had a significant effect on fertility in goats. Specifically, inseminations that were performed when mean (68 %), maximum (68 %), and minimum (66 %) temperatures were in the highest decile, and rainfall was in the lowest decile (59 %), had a significantly (P < 0.0001) higher proportion of does that became pregnant than did the ewes in the lowest decile (56, 54, 58, and 49 %, respectively). In sheep, the fertility rates of the highest decile of mean (62 %), maximum (62 %), and minimum (52 %) temperature, RH (52 %), THI (53 %), and rainfall (45 %) were significantly higher (P < 0.0001) than were the fertility rates among ewes in the lowest decile (46, 45, 45, 45, 46, and 43 %, respectively). In conclusion, weather was related to fertility in small ruminants after AI in spring. It remains to be determined whether scheduling the dates of insemination based on forecasted temperatures can improve the success of AI in goats and sheep.
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