Impact on prime animal beef merit from breeding solely for lighter dairy cows.

As the proportion of prime carcasses originating from dairy herds increases, the focus is shifting to the beef merit of the progeny from dairy herds. Several dairy cow total merit indexes include a negative weight on measures of cow size. However, there is a lack of knowledge on the impact of genetic selection, solely for lighter or smaller-sized dairy cows, on the beef performance of their progeny. Therefore, the objective of this study was to quantify the genetic correlations among cow size traits (i.e., cow body weight (BW), cow carcass weight (CW)), cow body condition score (BCS), cow carcass conformation (CC), and cow carcass fat cover (CF), as well as the correlations between these cow traits and a series of beef performance slaughter-related traits (i.e., CW, CC, CF, and age at slaughter (AS)) in their progeny. After data editing, there were 52,950 cow BW and BCS records, along with 57,509 cow carcass traits (i.e., CW, CC, and CF); carcass records from 346,350 prime animals along with AS records from 316,073 prime animals were also used. Heritability estimates ranged from moderate to high (0.18 to 0.62) for all cow and prime animal traits. The same carcass trait in cows and prime animals were strongly genetically correlated with each other (0.76 to 0.85), implying that they are influenced by very similar genomic variants. Selecting exclusively for cows with higher BCS (i.e., fatter) will, on average, produce more conformed prime animals carcasses, owing to a moderate genetic correlation (0.30) between both traits. Genetic correlations revealed that selecting exclusively for lighter BW or CW cows will, on average, result in lighter prime animal carcasses of poor CC, while also delaying slaughter age. Nonetheless, selective breeding through total merit indexes should be successful in breeding for smaller dairy cows, and desirable prime animal carcass traits concurrently, because of the non-unity genetic correlations between the cow and prime animal traits; this will help to achieve a more ethical, environmentally sustainable, and economically viable dairy-beef industry.

Comparison of greenhouse gas emissions from sheep measured using both respiration and portable accumulation chambers.

Methane (CH4) is a potent gas produced by ruminants, and new measurement techniques are required to generate large datasets suitable for genetic analysis. One such technique are portable accumulation chambers (PAC), a short-term sampling method. The objectives of the current study were to explore the relationship between CH4 and carbon dioxide (CO2) output measured using both PAC and respiration chambers (RC) in growing lambs, and separately investigate the relationship among CH4, CO2 and measured ad libitum DM intake (DMI). Methane, CO2 and DMI were measured on 30 Suffolk and 30 Texel ewe lambs (age 253 ± 12 days) using the RC and PAC sequentially. The experiment was conducted over a 14-day period, with DMI measured from days 1 to 14; measurements in RC were conducted from days 10 to 12, while measurements in PAC were taken twice, the day immediately prior to the lambs entering the RC (day 9; PAC Pre-RC) and on the day lambs exited the RC (day 13; PAC Post-RC). Greater CH4 and CO2 output was measured in the RC than in the PAC (P < 0.01); similarly mean CH4 yield was greater when measured in the RC (15.39 ± 0.452 g CH4/kg DMI) compared to PAC (8.01 ± 0.767 g CH4/kg DMI). A moderate correlation of 0.37 was found between CH4 output measured in PAC Pre-RC and the RC, the corresponding regression coefficient of CH4 output measured in the RC regressed on CH4 output measured in PAC Pre-RC was close to unity (0.74; SE 0.224). The variance of CH4 and CO2 output within the measurement technique did not differ from each other (P > 0.05). Moderate to strong correlations were found between CH4 and CO2 per kg of live weight and CH4 and CO2 yield. Results from this study highlight the suitability of PAC as a ranking tool to rank animals based on their gaseous output when compared to the RC. However, repeated measurements separated by several days may be beneficial if precise rankings are required. Given the close to unity regression coefficient of CH4 output measured in the RC regressed on CH4 output measured in PAC Pre-RC suggests that PAC could also be potentially used to estimate absolute CH4 output; however, further research is required to substantiate this claim. When DMI is unknown, CH4 and CO2 per kg of live weight are a suitable alternative to the measurement of CH4 and CO2 yield.

Using milk mid-infrared spectroscopy to estimate cow-level nitrogen efficiency metrics.

Minimizing pollution from the dairy sector is paramount; one potential cause of such pollution is excess nitrogen. Nitrogen pollution contributes to a deterioration in water quality as well as an increase in both eutrophication and greenhouse gases. It is therefore essential to minimize the loss of nitrogen from the sector, including excretion from the cow. Breeding programs are one potential strategy to improve the efficiency with which nitrogen is used by dairy cows, but they rely on routine access to individual cow information on how efficiently each cow uses the nitrogen it ingests. A total of 3,497 test-day records for individual-cow nitrogen efficiency metrics along with milk yield and the associated milk spectra were used to investigate the ability of milk infrared spectral data to predict these nitrogen traits; both traditional partial least squares regression and neural networks were used in the prediction process. The data originated from 4 farms across 11 yr. The nitrogen traits investigated were nitrogen intake, nitrogen use efficiency, and nitrogen balance. Both nitrogen use efficiency and nitrogen balance were calculated considering nitrogen intake, nitrogen in milk, nitrogen in the conceptus, nitrogen used for the growth, nitrogen stored in body reserves, and nitrogen mobilized from body reserves. Irrespective of the nitrogen-related trait being investigated, the best predictions from 4-fold cross validation were achieved using neural networks that considered both the morning and evening milk spectra along with milk yield, parity, and DIM in the prediction process. The coefficient of determination in the cross validation was 0.61, 0.74, and 0.58 for nitrogen intake, nitrogen use efficiency, and nitrogen balance, respectively. In a separate series of validation approaches, the calibration and validation was stratified by herd (n = 4) and separately by year. For these scenarios, partial least squares regression generated more accurate predictions compared with neural networks; the coefficient of determination was always lower than 0.29 and 0.60 when validation was stratified by herd and year, respectively. Therefore, if the variability of the data being predicted in the validation datasets is similar to that in the data used to develop the predictions, then nitrogen-related traits can be predicted with reasonable accuracy. In contrast, where the variability of the data that exists in the validation dataset is poorly represented in the calibration dataset, then poor predictions will ensue.

Differences in the choice of beef artificial insemination sires used by dairy producers versus beef producers.

The growing demand among dairy producers for suitable beef sires to mate to their females creates the possibility of separate breeding programs to generate beef sires for the dairy sector versus those for the beef sector. Informing such a decision is the extent of the genetic differences among beef sires used by dairy producers relative to those used by beef producers. The objective therefore of the present study was to use a large national database of artificial insemination (AI) records in dairy and beef cow herds to establish the difference in mean genetic merit of beef AI sires used by dairy producers versus those used by cow-calf beef producers. The traits explored were gestation length, calving difficulty, and perinatal mortality as well as the 3 carcass traits of carcass weight, conformation, and fat score. Carcass conformation and fat score are mechanically assessed on a scale of 1 (poor conformation and low fat cover) to 15 (excellent conformation and high fat cover). Sire genetic merit differences for feed intake and docility were also examined. Estimates of genetic merit for all 8 traits on individual AI sires available at the time of service were used. A total of 1,230,622 AI records comprised 909,719 services from dairy herds and 320,903 services from beef herds were used. Of the 1,802 beef AI sires represented in the entire dataset, over half were used by both dairy and beef herds representing ≥98% of the services in each production system. However, the usage rate of individual AI sires differed between dairy and beef herds with the Spearman rank correlation between the quantity of inseminations per sire in dairy and beef herds being just 0.38. This correlation means that beef AI sires used heavily in the beef herd were not always those heavily used in dairy herds. A clear difference in the mean genetic merit of beef AI sires selected by dairy producers relative to those selected by beef cow-calf producers was obvious with the extent of the difference being a function of whether the female served was a nulliparous heifer or a cow. Much of the differences in genetic merit of chosen beef AI sires between dairy and beef producers was actually attributable to differences in breed choice, albeit some within-breed selection was also evident. Irrespective, dairy producers, on average, chose shorter gestation length sires whose progeny were genetically less predisposed to require intervention during the birthing process; these sires had genetic merit estimates expected to result in lighter and less conformed progeny carcasses relative to the beef AI sires used by beef producers. Results point to large differences in genetic merit of the beef AI sires chosen by dairy versus beef producers, much of which actually reflected differences in breed choice among dairy and beef producers.

Comparison of calving and revenue-generating qualities in beef-sired male and female progeny from dairy cows.

Although interest in beef-on-dairy breeding strategies is intensifying, little is actually known of the performance differences between beef-sired male and female progeny of dairy cows. The objective was therefore to use a large cross-sectional database of up to 1,389,670 animals to investigate if performance differences existed between male and female progeny generated from beef-on-dairy matings; the focus was on characteristics of interest to both the dairy producer (i.e., gestation length, calving performance, perinatal mortality, and calf sale value) and the beef producer (i.e., slaughter-related traits). While statistical differences existed between both sexes, the observed differences were not always biologically large, with some favoring females (e.g., calving traits and age at slaughter) and some favoring males (i.e., carcass weight). Beef-sired male calves had, on average, a 0.8 d longer gestation than their female counterparts; the sex difference in dairy-sired calves was, on average, 1.1 d, with the advantage to females. The odds of a difficult calving was 2.2 times greater for beef-sired male calves relative to beef-sired female calves; this translated to a difference in predicted probability of dystocia between the sexes of 1.8 percentage units. Male beef-sired calves sold at auctions <42 d of age were worth, on average, €32.40 more than beef-sired female calves. Focusing just on beef-sired progeny, relative to heifer carcasses (mean weight of 280.0 kg), the carcasses of steers (mean weight of 336.9 kg) and bulls (mean weight of 335.4) were 55.4 to 56.9 kg heavier. Based on a 15-point conformation scale, the carcasses of bulls were 1 unit superior to heifers, with the carcasses of the latter being 0.06 units better than steers. Heifers were slaughtered, on average, 79.1 d younger than steers although heifers were slaughtered, on average, 93.8 d older than bulls, the latter generally being finished on a more intensive diet relative to steers and heifers in Ireland. In conclusion, many benefits exist for beef-sired heifer calves in that they had, on average, shorter gestations with less expected assistance required at calving and, although their calf value was less and their carcasses were lighter than their male counterparts, they were slaughtered several months younger than steers.

The association between calf birth weight and the postcalving performance of its dairy dam in the absence of dystocia.

The objective of the study was to quantify the association between the birth weight of a calf and the subsequent performance of its dairy dam in the absence of any recorded calving assistance. A total of 11,592 lactation records from 4,549 spring-calving dairy cows were used. The association between a series of quantitative cow performance metrics (dependent variable) and calf birth weight (independent variable) was determined using linear mixed models; logistic regression was used where the dependent variable was binary. Nuisance factors in the models were calf sex, heterosis coefficient of both the cow and calf, dry period length immediately before the birth of the calf, cow age at calving relative to the median cow age per parity, breed proportion of the cow, cow live weight between 100 and 200 d of lactation relative to the mean cow weight per parity, and contemporary group. Calf birth weight was included in the model as either a continuous or a categorical variable. Primiparous and multiparous cows were analyzed separately. Mean (SD) calf birth weight was 36.2 (6.8) kg. In primiparous cows, calf birth weight was associated with milk yield in the first 60 d of lactation, calving to first service interval, calving body weight (BW), and both nadir BW and body condition score (BCS). In multiparous cows, calf birth weight was associated with total milk, fat, and protein yield in the first 60 and 305 d of lactation, peak milk yield, total milk solids, both calving and nadir BW, and BCS loss from calving to nadir. Relative to primiparous cows that gave birth to calves weighing 34 to 37 kg (i.e., population mean), their contemporaries who gave birth to calves that weighed 15 to 29 kg produced 9.82 kg more milk in the first 60 d of lactation, had a 2-d shorter interval to first service, and were 8.08 kg and 5.51 kg lighter at calving and nadir BW, respectively; the former was also 0.05 units lower in BCS (5-point scale, 1 = emaciated and 5 = obese) at nadir. Relative to multiparous cows that gave birth to calves that were 34 to 37 kg birth weight, multiparous cows that gave birth to calves that were 15 to 29 kg yielded 59.63 kg, 2.44 kg, and 1.76 kg less milk, fat, and protein, respectively, in the first 60 d of lactation; produced 17.69 kg less milk solids throughout the 305-d lactation; and were also 10.49 kg lighter at nadir and lost 0.01 units more BCS to nadir. In a separate series of analyses, sire breed was added to the model as a fixed effect with and without calf birth weight. When calf birth weight was not adjusted for, 60-d milk yield for multiparous cows who gave birth to calves sired by a traditional beef breed (i.e., Angus, Hereford) produced 59.63 kg more milk than multiparous cows who gave birth to calves sired by a Holstein-Friesian. Hence, calf birth weight is associated with some subsequent dam performance measures; however, where associations do exist, the effect is biologically small.