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Robustness can be defined as “the capacity to handle disturbances in common and sustainable, e.g. economically, systems”. To achieve a robust farming system, a broad perspective is needed (Napel 2005), but here we focus on genetic selection for robust cows and the origin of the need for such animals.
Genetic associations were estimated between pathogen-specific cases of clinical mastitis (CM), lactational average somatic cell score (LACSCS), and patterns of peaks in somatic cell count (SCC) which were based on deviations from the typical lactation curve for SCC. The dataset contained test-day records on SCC in 94 781 lactations of 25 416 cows of different parities. Out of these 94 781 lactations, 41 828 lactations had recordings on occurrence of pathogen-specific CM and on SCC, and 52 953 lactations had recordings on SCC only. A total of 5 324 lactations with cases of CM were recorded. Analysed pathogens were Staphylococcus aureus, coagulase negative staphylococci, Escherichia coli, Streptococcus dysgalactiae, Streptococcus uberis, and culture-negative samples. Pattern definitions were based on three or five consecutive test-day recordings of SCC. They differentiated between short or longer periods of increased SCC, and also between lactations with and without recovery. Occurrence of pathogen-specific CM and presence of patterns of peaks in SCC were both scored as binary traits. Variance components for sire, maternal grandsire, and permanent animal effects were estimated using AS-REML. The estimated heritability for overall CM was 0·04, and similar heritabilities for pathogen-specific CM were estimated. Heritabilities for the patterns of peaks in SCC ranged from 0·01 to 0·06. Heritabilities for LACSCS were 0·07 to 0·08. Genetic correlations with patterns of peaks in SCC differed for each pathogen. Generally, genetic correlations between pathogen-specific CM and patterns of peaks in SCC were stronger than the correlations with LACSCS. This suggests that genetic selection purely on diminishing presence of peaks in SCC would decrease the incidence of pathogen-specific CM more effectively than selecting purely on lower LACSCS.
Since evidence is present that genetic correlations between start of luteal activity and energy balance, milk yield and live weight exist (Veerkamp et al., 2000), it could be hypothesised that polymorphisms at the leptin gene locus might play a role. The first objective of this study was to associate plasma leptin levels during late pregnancy with genetic differences in the leptin gene. The second objective was to relate these polymorphisms with variations in energy balance, milk production, dry matter intake and fertility.
The objective of this study was to estimate the effects of genetic merit for milk yield on energy balance (EB), dry matter intake (DMI), and fertility for cows managed on three different grass based feeding systems, and to estimate possible interactions between genetic merit and feeding system. Individual animal intake estimates were obtained at pasture on 11 occasions across three grazing seasons. The data set contained 96 first lactation animals in 1995, 96 second lactation animals in 1996, and 72 third lactation animals in 1997. Half of these animals were of high (HG), and half of medium genetic merit (MG) for milk solids production. Genetic effects for the traits of interest were estimated as the contrast between the two genetic groups, and by the genetic regression of phenotypic performance on the estimated breeding value for fat and protein yield, based on pedigree information alone (PI). Significant effects of feeding system were observed on yields, DMI and EB, whereas there was no effect on live weight, condition score or reproductive performance. The interaction between genetic merit and feeding system was not significantly different from zero for any of the traits. Yields, grass DMI, and total DMI were all higher for HG than for MG, and also positively correlated (P<0.001) with PI. Furthermore, condition score, conception to first and second service, and pregnancy rate were significantly negatively correlated with PI. While at pasture, EB was positively (P<0.01) correlated with PI, although the contrast between HG and MG was not significantly different from zero. Condition score changes during very early lactation, demonstrated that HG had a more negative EB than MG. The results clearly illustrate the production potential of HG cows on grass based systems, however the reduced reproductive performance questions their suitability for seasonal calving systems.
In recent years there has been considerable genetic progress in milk production. Yet, increases in yield have been accompanied by an apparent lengthening of calving intervals, days open, days to first heat and a decline in conception rates, which appears to be both at the genetic and phenotypic level. Fertility has a high relative economic value compared to production traits such as protein, making it attractive to include in a breeding programme. To do this there needs to be genetic variance in fertility. Measures of fertility calculated from service dates have a small genetic compared to phenotypic variance, hence heritability estimates are small, typically less than 5%, although coefficients of genetic variance are comparable to those of production traits. Heritabilities of commencement of luteal activity determined using progesterone profiles are generally higher, and have been reported as being from 0.16 to 0.28, which could be because of a more precise quantification of genetic variance, as management influences such as delaying insemination and heat detection rates are excluded. However, it might not be the use of progesterone profiles alone, as days to first heat observed by farm staff has a heritability of 0.15. The most efficient way to breed for improved fertility is to construct a selection index using the genetic and phenotypic parameter estimates of all traits of interest in addition to their respective economic values. Index traits for fertility could include measures such as calving interval, days open, days to first service, or days to first heat but there may also be alternative measures. Examples include traits related to energy balance, such as live weight and condition score (change), both of which have higher heritabilities than fertility measures and have genetic correlations of sufficient magnitude to make genetic progress by using them feasible. To redress the balance between fertility and production, some countries already publish genetic evaluations of fertility including: Denmark, Finland, France, Germany, Israel, The Netherlands, Norway and Sweden.
Getting reliable genetic parameter estimates for dry matter intake is difficult because recording it is expensive, hence it is tempting to combine data from research herds. However, there are large differences in feeding and management systems, which causes differences in means across herds. Furthermore, variances or heritabilities may differ and genetic correlations may be less than one between herds. This is one of the reasons why it is important to investigate effects of genotype by environment interaction (GxE). Another reason is that it is important to understand how high genetic merit cows perform in different feeding systems. The objective of this study was to estimate the effect of GxE for three feeding systems at two research herds belonging to ID-Lelystad (ID) and to SAC/University of Edinburgh (Langhill).
The economic pressures on the dairy industry may force more farmers to consider reducing the amount of concentrates fed to cows in order to keep costs down. We have been testing whether the long-term performance of daughters of sires progeny tested in high concentrate systems maintain their advantage over cows of average genetic merit when managed in a lower input feeding system. This paper extends the scope of our initial report (Chalmers et al., 1997) and includes data on reproductive performance.
Data were from Holstein-Friesian cows managed at the Langhill Dairy Cattle Research Centre. Sires of the Selection (S) line are among the highest available in the UK for predicted transmitting abilities of weight of fat plus protein (PTA F+P). Sires of Control (C) line cows are about UK average for PTA F+P.
High producing dairy cows have been found to be more susceptible to disease (Jones et al., 1994; Göhn et al., 1995) raising concerns about the welfare of the modern dairy cow. Genotype and number of lactations may affect various health problems differently, and their relative importance may vary. The categorical nature and low incidence of health events necessitates large data-sets, but the use of data collected across herds may introduce unwanted variation. Analysis of a comprehensive data-set from a single herd was carried out to investigate the effects of genetic line and lactation number on the incidence of various health and reproductive problems.
In many countries there has been an interest in including measures of liveweight and/or size in dairy cattle breeding goals, with the main aim of decreasing food costs. Whilst opinions about the right size of a dairy cow seem to differ among countries, it has been argued that because of the strong associations between liveweight, intake(-capacity) and condition score, the whole complex of these traits should be considered simultaneously (Veerkamp 1996). To do so, genetic parameters (and economic values) are required. Hence, the objective of this study is to estimate genetic parameters for yield, food intake, liveweight and condition score in first lactation heifers.
Performance characteristics of high genetic merit cows on different feeding systems are not only important to establish the biological and economic consequences of current genetic selection practices, but can be used also to establish ‘standards’ which will be helpful to people who want to develop breeding, management or feeding strategies for high genetic merit cows. Whereas the performance of high and average genetic merit cows on two different feeding systems has been presented before (Veerkamp et al. 1995), the aim of this study is to define if some of the advantages of high genetic merit cows persist throughout the first three lactations of a cow's lifetime.
An earlier study at Langhill (Veerkamp et al, 1995) showed that selection for yield in dairy cows increases body tissue mobilisation during lactation, since high genetic merit animals had a lower average condition score (CS) compared with low genetic merit animals. However, in this study no diet effect for condition score and no interaction between diet and genetic merit was found. The reasons for this might have been that average condition scores during lactation were analysed, and therefore the objective of this study was to evaluate the effects of genotype and diet during lactation using weekly observations.
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