Despite substantial advances in milk production efficiency of dairy cattle over the last 50 years, rising feed costs remain a significant threat to producer profitability. There also is a greater emphasis being placed on reducing the negative impacts of dairy production on the environment; thus means to lower greenhouse gas (GHG) emissions and nutrient losses to the environment associated with cattle production are being sought. Improving feed efficiency among dairy cattle herds offers an opportunity to address both of these issues for the dairy industry. However, the best means to assess feed efficiency and make genetic progress in efficiency-related traits among lactating cows without negatively impacting other economically important traits is not entirely obvious. In this review, multiple measurements of feed efficiency for lactating cows are described, as well as the heritability of the traits and their genetic and phenotypic correlations with other production traits. The measure of feed efficiency, residual feed intake is discussed in detail in terms of the benefits for its selection, how it could be assessed in large commercial populations, as well as biological mechanisms contributing to its variation among cows, as it has become a commonly used method to estimate efficiency in the recent scientific literature.

Invited review: Improving feed efficiency in dairy production: challenges and possibilities*

Symposium review: Novel strategies to genetically improve mastitis resistance in dairy cattle

Genetic correlations between reproduction and production traits were estimated in swine. Reproduction traits investigated were age at first service (AFS), number of live-born piglets in the first litter (NBA1), interval from weaning to first service after first litter (WTS1), number of live-born piglets in the second litter (NBA2), and interval from weaning to first service after the second litter (WTS2). Females generating the data were Norwegian Landrace born in nucleus herds between 1990 and 2000, and the number of records ranged from 13,792 to 56,932. Genetic correlations were estimated among the main production traits in the breeding goal: adjusted age at 100 kg live weight (A100), percentage of lean meat content (LMC), individual feed consumption from 25 to 100 kg (FC), and bacon side quality (BSQ). Average adjusted backfat thickness (BF) was included as a production trait. The A100 and BF traits were recorded on gilts on-farm with 190,454 records, whereas LMC, BSQ, and FC were recorded on-station with the number of records ranging from 12,487 to 12,992. Analyses were carried out with a multivariate animal model using average information restricted maximum likelihood procedures by first running each reproduction trait with A100 and BF, followed by each reproduction trait with LMC, BSQ, and FC. Average heritabilities for reproduction traits were as follows: AFS (0.38), NBA1 (0.11), WTS1 (0.06), NBA2 (0.12), and WTS2 (0.03); and for production traits: A100 (0.30), BF (0.44), FC (0.22), LMC (0.58), and BSQ (0.23). The highest genetic correlation was estimated between A100 and AFS (r(g)= 0.68), also resulting in a positive genetic correlation between FC and AFS. Growth (A100) was negatively (i.e., unfavorably) genetically correlated to NBA1 and NBA2 (r(g) = 0.60 and rg = 0.42 respectively), and so the genetic correlation to FC also became unfavorable (r(g)= 0.23 and r(g) = 0.20). Single-trait selection for enhanced LMC would also affect NBA1 and NBA2 unfavorably (r(g)= -0.12 and r(g)= -0.24). Correlations between BF at 100 kg live weight and reproduction traits were close to zero; however, a low genetic correlation between BF and WTS1 was obtained (r(g)= -0.12), indicating that selection toward reduced BF at 100 kg live weight may have an unfavorable impact on WTS1.

Genetic correlations between reproduction and production traits in swine.

Invited review: Incidence, risk factors, and effects of clinical mastitis recurrence in dairy cows.

A genome scan to detect QTL influ- encing growth and carcass-related traits was conducted in a Charolais × Holstein crossbred cattle population. Phenotypic measurements related to growth and car- cass traits were made on the 235 second-generation crossbred males of this herd (F2 and reciprocal back- crosses), which were born in 4 consecutive annual co- horts. Traits measured in vivo were related to birth di- mensions, growth rates, and ultrasound measurements of fat and muscle depth. The animals were slaughtered near a target BW of 550 kg, and a wide range of post- mortem traits were measured: visual assessment of car- cass conformation and carcass fatness, estimated sub- cutaneous fat percentage, weights of kidney knob and channel fat, and weights of carcass components after commercial and full-tissue dissections. The whole popu- lation, including grandparents, parents, and the cross- bred bulls, was genotyped initially for 139 genome-wide microsatellite markers. Twenty-six additional markers were subsequently analyzed to increase marker density on some of the chromosomes where QTL had been ini- tially identified. The linear regression analyses based on the 165 markers revealed a total of 51 significant QTL at the suggestive level, 21 of which were highly signifi- cant (F-value ≥9; based on the genome-wide thresholds obtained in the initial scan). A large proportion of the highly significant associations were found on chromo- somes 5 and 6. The most highly significant QTL was localized between markers DIK1054 and DIK082 on chromosome 6 and explained about 20% of the pheno- typic variance for the total bone proportion estimated after the commercial dissection. In the adjacent marker interval on this chromosome, 2 other highly significant QTL were found that explain about 30% of the phe- notypic variance for birth dimension traits (BW and body length at birth). On chromosome 5, the most sig- nificant association influenced the lean:bone ratio at the forerib joint and was flanked by markers DIK4782 and BR2936. Other highly significant associations were detected on chromosomes 10 (estimated subcutaneous fat percentage), 11 (total saleable meat proportion), 16 (prehousing growth rate), and 22 (bone proportion at the leg joint). These results provide a useful starting point for the identification of the genes associated with traits of direct interest to the beef industry, using fine mapping or positional candidate gene approaches.

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M. Wolfová

Papers

Selection for Profit in Cattle: I. Economic Weights for Purebred Dairy Cattle in the Czech Republic

Breeding objectives for beef cattle used in different production systems

Incidence and economics of clinical mastitis in five Holstein herds in the Czech Republic.

Economic values of production and functional traits, including residual feed intake, in Finnish milk production.

Selection for profit in cattle: II. Economic weights for dairy and beef sires in crossbreeding systems.