Prediction of genetic merit for live weight and body condition score in dairy cows using routinely available linear type and carcass data

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.

On-Barn Forecasting Beef Cattle Production Based on Automated Non-Contact Body Measurement System

The main task of selective breeding is to determine the early productivity of offspring. The sooner the economic value of an animal is determined, the more profitable the result will be, due to the proper estimation of high and low productive calves and distribution of the resources among them, accordingly. To predict productivity, we offer to use a systematic assessment of animals by using the main genetic parameters (correlation coefficients, heritability, and regression) based on data such as the measurement of morphological characteristics of animals, obtained using the automated non-contact body measurement system based on RGB-D image capture. The usefulness of the image capture system lies in significant time reduction that is spent on data collection and improvement in data collection accuracy due to the absence of subjective measurement errors. We used the RGB-D image capture system to measure the live weight of mother cows, as well as the live weight and body size of their calves (height at the withers, height in the sacrum, oblique length of the trunk, chest depth, chest girth, pastern girth). Cows and cattle of black-and-white and Holstein breeds (n = 561) were selected as the object of the study. Correlation analysis revealed the main indices for the forecast of meat productivity-live weight and measurements of animals at birth. Calculation of the selection effect is necessary for planning breeding work, since it can determine the value of economically beneficial traits in subsequent generations, which is very important for increasing the profitability of livestock production. This approach can be used in livestock farms for predicting the meat productivity of black-and-white cattle.

Associations of carcass weight and trimming loss with cull dairy cow health observations collected at slaughter

Cull dairy cows account for around 27 percent of total head EU beef and veal production. For the Netherlands specific, even 42 percent (European Commission, 2022). As they are primarily kept to produce milk, red meat production is an additional source of revenue for dairy farmers. Insights in postmortem health observations that are not always visible on the living animal such as heart or liver issues, bruises, adhesions and injuries on the locomotor system, may contain valuable information for farmers to increase revenue and reduce losses in red meat production from cull dairy cows. Our goal was to obtain insights in the association of postmortem health observations with carcass weight and trimming losses. Data of 592,268 slaughter cows were available for analysis and models were built to explain carcass and trimming loss by the postmortem health observations. Carcass weight is lower for younger cows (-3.2 to -84.9 kg), cows with multiple health observations (-7.4 to -34.3 kg) and specific observations for the locomotor system (-16.7 to -22.7 kg), back (-17.9 kg), hindquarter (-21.6 kg) and chest and ribs (-15.5 to -27.6 kg). Total number of health observations (+2.0 to +6.5 kg), observations on the locomotor system (+3.3 to +5.4 kg) and on the chest and ribs (+2.2 to +9.8 kg) were the main predictors for trimming loss. Carcass weight is more affected by systemic health issues and diseases prior to slaughter leading to a negative energy balance and consequently reduced carcass weight. Trimming loss is more a consequence of the focus on meat quality and food safety in the slaughter process. Better understanding of the effect of on-farm management, on health, carcass weight and trimming loss will provide new insights for farmers and veterinarians but will also give them more action perspective to improve dairy farm preventive management and reduce losses at slaughter.

Re-assessing the importance of linear type traits in predicting genetic merit for survival in an aging Holstein-Friesian dairy cow population

The cumulative improvement achieved in the genetic merit for reproductive performance in dairy populations will likely improve dairy cow longevity; therefore, it is time to reassess whether linear type traits are still suitable predictors of survival in an aging dairy cow population. The objective of the present study was therefore to estimate the genetic correlations between linear type traits and survival from one parity to the next and, in doing so, evaluate if those genetic correlations change with advancing parity. After edits, 152,894 lactation survival records (first to ninth parity) were available from 52,447 Holstein-Friesian cows, along with linear type trait records from 52,121 Holstein-Friesian cows. A series of bivariate random regression models were used to estimate the genetic covariances between survival in different parities and each linear type trait. Heritability estimates for survival per parity ranged from 0.02 (SE = 0.004; first parity) to 0.05 (SE = 0.01; ninth parity). Pairwise genetic correlations between survival among different parities varied from 0.42 (first and ninth parity) to 1.00 (eighth to ninth parity), with the strength of these genetic correlations being inversely related to the interval between the compared parities. The genetic correlations between survival and the individual linear type traits varied across parities for 9 of the 20 linear type traits examined, but the correlations with only 3 of these linear type traits strengthened as the cows aged; these 3 traits were rear udder height, teat length, and udder depth. Given that linear type traits are frequently scored in first parity and are genetically correlated with survival in older parities, they may be suitable early predictors of survival, especially for later parity cows. Additionally, the direction of the genetic correlations between survival and rear udder height, teat length, and udder depth did not change between parities; hence, selection for survival in older parities using these linear type traits should not hinder genetic improvement for survival in younger parities.

The response to genetic merit for milk production in dairy cows differs by cow body weight

•

Heavier cows yield more milk, fat, and protein.

•

The association between genetic merit for milk yield and actual yield differs by BW.

•

The association between genetic merit for milk composition and actual composition does not differ by BW.

Attention is increasing on both cow size and body weight (BW) as energy sinks and thus as contributors to differences in production efficiency among cows. What is not currently clear, however, is how cow BW affects the increase in yield per cow per unit increase in genetic merit for milk production. This void in knowledge was filled in the present study using BW data from 20,470 lactations on 16,980 Holstein-Friesian dairy cows stratified into 4 groups on BW adjusted for differences in parity, days in milk, and body condition score. Using linear mixed models that adjusted for nuisance factors, cow phenotypic milk production variables were regressed on estimates of parental average genetic merit for the respective trait within each stratum of BW defined within contemporary group; estimates of genetic merit were from the national genetic evaluations. Both the intercept and linear regression coefficients on genetic merit were compared across BW strata. The intercepts representing the mean phenotypic yield at a genetic merit of zero differed among BW strata; irrespective of yield trait, the least squares means yield per BW stratum increased numerically as cows got heavier, although not every stepwise increase in BW stratum was associated with significantly greater yield compared with the previous (lighter) stratum. Nonetheless, the yield of the cows in the lightest of the 4 strata was always less than that of the heaviest 2 strata; relative to the lightest stratum, cows in the heaviest BW stratum produced only 3 to 4% more yield. Furthermore, the association between phenotypic yield and its respective measures of genetic merit differed by BW stratum; the response to selection for each of the yield traits was 15 to 23% greater for the heaviest stratum of cows compared with their contemporaries in the lightest stratum. Although BW stratum was associated with mean fat and protein concentration after adjusting for differences in genetic merit for fat and protein concentration, the association did not differ by BW stratum for either fat or protein concentration. The effect of BW on efficiency should consider the association between BW and not only mean phenotypic yield at a given genetic merit, but also how the differences in yield diverge as genetic merit increases.

Commercial beef farms excelling in terminal and maternal genetic merit generate more gross profit

Validation of beef total merit breeding indexes for improving performance and profitability has previously been undertaken at the individual animal level; however, no herd-level validation of beef genetic merit and profit has been previously investigated. The objective of the present study was to quantify the relationship between herd profitability and both herd-average terminal and maternal genetic merit across 1,311 commercial Irish beef herds. Herd-level physical and financial performance data were available from a financial benchmarking tool used by Irish farmers and their extension advisors. Animal genetic merit data originated from the Irish Cattle Breeding Federation who undertake the national beef and dairy genetic evaluations. Herd-average genetic merit variables included the terminal index of young animals, the maternal index of dams, and the terminal index of service sires. The herds represented three production systems: 1) cow-calf to beef, 2) cow-calf to weanling/yearling, and 3) weanling/yearling to beef. Associations between herd financial performance metrics and herd average genetic merit variables were quantified using a series of linear mixed models with year, production system, herd size, stocking rate, concentrate input, and the two-way interactions between production system and herd size, stocking rate, and concentrate input included as nuisance factors. Herd nested within the county of Ireland (n = 26) was included as a repeated effect. Herds with young cattle excelling in terminal index enjoyed greater gross and net profit per hectare (ha), per livestock unit (LU), and per kg net live-weight output. The change in gross profit per LU per unit change in the terminal index of young animals was €1.41 (SE = 0.23), while the respective regression coefficient for net profit per LU was €1.37 (SE = 0.30); the standard deviation of the terminal index is €37. Herd-average dam maternal index and sire terminal index were both independently positively associated with gross profit per ha and gross profit per LU. Each one unit increase in dam maternal index (standard deviation of €38) was associated with a €1.40 (SE = 0.48) and €0.76 (SE = 0.29) greater gross profit per ha and per LU, respectively. Results from the present study at the herd-level concur with previous validation studies at the individual animal level thus instilling further confidence among stakeholders as to the expected improvement in herd profitability with improving genetic merit.