Estimation of genetic parameters using health, fertility and production data from a management recording system for dairy cattle

Abstract

The Dairy Information System (DAISY) was developed to record fertility and health information for use in research and to help farmers manage their farms. Data from 33 herds recording health and fertility over a 6-year period were used to study genetic relationships of several health, fertility and production traits. There were 10 569 records from 4642 cows of all parities. These were used to estimate genetic parameters for health: mastitis, lameness and somatic cell score (SCS), for fertility: calving interval, days to first service, conception to first service and for production: 305-day milk, butterfat and protein yields. Heritabilities for these traits were also estimated for the first three lactations. (Co)variances were estimated using linear, multitrait restricted maximum likelihood (REML) with an animal model. Mastitis and lameness were treated as all-or-none traits. The incidence of these diseases increased with lactation number, which may lead to variance component estimation problems, as the mean is linked to the variance in binomial distributions. Therefore, a method was used to fix the within-lactation variance to one in all lactations while maintaining the same mean. The heritability for SCS across lactations was 0·15. Heritabilities for other health and fertility traits were low and ranged between 0·013 and 0·047. All genetic correlations with the production traits were antagonistic implying that selection for yield may have led to a deterioration in health and fertility. The genetic correlation between SCS and mastitis was 0·65 indicating that indirect selection for improvements in mastitis may be achieved using somatic cell counts as a selection criterion. The potential use of linear type scores as predictors of the health traits was investigated by regressing health traits on sire predicted transmitting abilities for type. The results indicate that some type traits may be useful as future selection criteria.

Genetics of resistance to mastitis in dairy cattle

“…[27]. Similar values were reported in other countries [59,68,97]. To some extent, these consistently low values obtained on the observed binary scale, could be due to the too general definition of the trait, without any reference to the pathogens.…”

“…Furthermore, although the phenotypic correlation between test-day is rather low (about 0.3), the genetic correlation between adjacent test-day SCS is higher than 0.95 and decreases slightly to 0.7 between the beginning and the end of the lactation. The lactation measure of SCS (LSCS), obtained by averaging the individual test-day records, show a consistent higher heritability estimate around 0.15 with a range from 0.10 to 0.18 [51,59,68]. Genetic correlation of LSCS across lactations is rather high (higher than 0.8 in most breeds) so that genetic determinism of SCC is close within and across lactations.…”

Genetic parameters for production, health, fertility and longevity traits in dairy cows

“…Lower genetic correlations of 0.13 in Swiss Holsteins (Kadarmideen 2004) and 0.16 in UK dairy cattle (Pryce et al, 1998) were obtained for the correlation between SCS and DFS. In contrast, a higher genetic correlation of 0.28 between SCS and CI was obtained in the same study of Pryce et al (1998). In addition to clinical mastitis, subclinical mastitis also has a negative effect on fertility.…”

Risk factors and milk yield losses associated with lameness in Holstein-Friesian dairy cattle

“…Intensive dairy farms are characterised by highyielding cows fed high levels of concentrates and housed indoors much (if not all) of the year. The genetic correlation between production and health traits is generally unfavourable (Pryce et al, 1998) and selection for yield has resulted in increased mastitis, fertility problems and lameness. Research into the effects of intensive management on -E-mail: O.M.Onyiro@sms.ed.ac.uk health traits is not well documented but, with the increase in high-input farming systems, is an area that requires monitoring.…”