Effect of strain of Holstein–Friesian and feed system on udder health and milking characteristics

Livestock Science 107 (2007) 19 – 28 www.elsevier.com/locate/livsci

Effect of strain of Holstein–Friesian and feed system on udder health and milking characteristics S. McCarthy a,b,⁎, D.P. Berry a , P. Dillon a , M. Rath b , B. Horan a,b b

a Teagasc, Dairy Production Research Centre, Moorepark, Fermoy, Co. Cork, Ireland School of Agriculture, Food Science and Veterinary Medicine, UCD, Belfield, Dublin 4, Ireland

Received 18 May 2006; received in revised form 14 August 2006; accepted 22 August 2006

Abstract The objective of this study was to quantify the effect of three alternative strains of Holstein–Friesian dairy cows, parity and feed system on udder health and milk flow characteristics. The three strains of Holstein–Friesian compared were, high production North American (HP), high durability North American (HD) and New Zealand (NZ). The three feed systems compared were, a high grass allowance feed system typical of spring calving herds in Ireland (MP), a higher concentrate system (HC), and a higher stocking rate system (HS). The data comprised up to 584 lactations from 240 cows across 5 years, from one research herd. The NZ stain had significantly higher average lactation somatic cell count (87,553 cells/ml) than the HP (60,475 cells/ml) or HD strains (59,278 cells/ml). Nonetheless, differences between strains were not biologically important. No significant strain effect on incidence of clinical mastitis was observed; average lactation incidence of clinical mastitis was 26%. The NZ strain had the highest peak milk flow (5.45 kg/min) and the shortest average milking duration (6.60 log sec/day). Feed system had no significant effect on udder health while significant feed system effects were observed on milking characteristics including average milk flow and average and maximum milking duration. This study indicates significant variation in somatic cell count and milking characteristics between strains, which when coupled with their economic importance, suggest the necessity to include these in overall breeding objectives. © 2006 Elsevier B.V. All rights reserved. Keywords: Dairy; Udder health; Milking characteristics; Strain of Holstein–Friesian

1. Introduction In recent years, milk bulk tank somatic cell count (SCC) on Irish dairy farms has increased (Berry et al., 2006). This increase, coupled with the milk payment system in Ireland, tiered on monthly bulk tank SCC, has increased the importance of improved milk quality in ⁎ Corresponding author. Teagasc, Dairy Production Research Centre, Moorepark, Fermoy, Co. Cork, Ireland. Tel.: +353 2542222; fax: +353 2542340. E-mail address: [email protected] (S. McCarthy). 1871-1413/$ - see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.livsci.2006.08.014

Irish herds. Furthermore, mastitis increases veterinary and labour costs (Berry and Amer, 2005), increases replacement rates and reduces milk sales through yield reduction (Coulon et al., 2002) and milk exclusion during the treatment period. Irish dairy farmers also incur financial penalties when trace antibiotic residues are found in milk, a consequence of poor animal health and in particular the prevalence of mastitis on farms. As with most infectious agents, mastitis incidence is a function of managerial, environmental, and animal effects (Mrode and Swanson, 1996; Barkema et al., 1998; Pryce et al., 1999; Lacy-Hulbert et al., 2002). The

20

S. McCarthy et al. / Livestock Science 107 (2007) 19–28

significant genetic variance in mastitis incidence has been widely reported previously (Mrode and Swanson, 1996). A positive relationship has also been reported between mastitis and milk yield (Gröhn, 2000), while Pryce et al. (1999) documented an increased incidence of clinical mastitis (CM) with pedigree index for fat plus protein yield. Importantly, Mrode and Swanson (1996) reported a positive genetic correlation between SCC and milk yield which suggest that aggressive selection for milk yield will result in increased SCC. Although not consistent across all years of the study, Lacy-Hulbert et al. (2002) reported a generally lower SCC in New Zealand cows compared to cows not of New Zealand origin; similarly cows not of New Zealand descent had a higher incidence of CM and subclinical infection. Milking speed has also been associated with SCC, with faster milking cows having higher average lactation SCC (Grindal and Hillerton, 1991). Recent studies (Berry et al., 2004) have documented a positive genetic correlation between milk yield and milking speed. This implies that aggressive genetic selection for milk production without cognisance of other traits will increase milking speed to the detriment of udder health; this trend may be further exacerbated by conscious phenotypic selection against slower milking cows. Milking speed also impacts farm profitability with increasing milk flow rates resulting in reduced milking time and decreased labour and energy costs associated with milking (Prins, 2002). Several countries now include milking speed as a goal trait in their total merit index (Miglior et al., 2005). Previous research on the effect of feeding level on udder health is inconsistent. Higher levels of concentrate feeding have been associated with poorer udder health (Lacy-Hulbert et al., 2002) while Pryce et al. (1999) found no significant difference between groups on differing concentrate input levels. Pryce et al. (1999) also reported an increase in mastitis while Weller et al. (1992) found an increase in lactation SCC as parity number increased. Increased milk flow with increasing parity number has also been reported (Petersen et al., 1986). The objective of this study was to quantify the effect of three alternative strains of Holstein–Friesian (HF) dairy cattle, differing in milk production potential and selected under different breeding goals, as well as parity and contrasting pasture-based feed systems (FS) on udder health and milk flow characteristics. Identification of such differences would facilitate inferences to be made on the effect of breeding programs and feeding systems on traits related to udder health and milking characteristics which are of economic and/or social importance.

2. Materials and methods 2.1. Animals Three strains of Holstein–Friesian cow were compared. These strains are outlined in more detail by Horan et al. (2005). In summary, the three strains compared were high production North American (HP), high durability North American (HD) and New Zealand (NZ). The pedigree index for each cow was calculated as 0.50 × sire predicted transmitting ability + 0.25 × maternal grand sire predicted transmitting ability + 0.125 × maternal granddam's sire predicted transmitting ability and the mean for each strain is outlined in Table 1. Predicted transmitting abilities were those from the February 2004 international evaluations of the INTERBULL Animal Center for milk production and from the February 2004 domestic genetic evaluation for calving interval, survival and somatic cell score (i.e., logeSCC). The HP strain was created by inseminating the top 50% of Holstein–Friesian cows in the Moorepark herds (based on pedigree index for milk production) with semen from five North American Holstein–Friesian sires. These sires were the highest available in Ireland at that time based on combined predicted transmitting ability for milk, fat, and protein yields. This strain illustrates the outcome of continuous aggressive selection for increased milk production. The HD strain was initially created using the bottom 50% of Holstein–Friesian cows in the Moorepark herds (based on pedigree index for milk production) and semen from five North American Holstein–Friesian sires, selected on a combination of their pedigree indices for milk production, fertility and linear traits. Therefore this strain is representative of a more balanced breeding policy. The NZ cows originated from embryos imported from New Zealand from the mating of high genetic merit New Zealand Holstein–Friesian cows to five high genetic merit New Zealand Holstein–Friesian sires. Table 1 Mean predicted transmitting ability (and SD) for the three strains of Holstein–Friesian cows studied for milk production, survival, calving interval and somatic cell score Strain

High production High durability New Zealand

Milk (kg) +194 (90.8) Fat (kg) +9.0 (2.96) Protein (kg) +8.8 (2.39) Fat (g/kg) +0.3 (0.53) Protein (g/kg) +0.4 (0.23) Survival (%) − 0.5 (1.11) CI (days) +0.44 (1.57) SCS (SCS units) +0.03 (0.05)

+76 (61.4) +6.3 (2.84) +5.7 (1.58) +0.7 (0.56) +0.6 (0.30) +0.4 (0.51) −1.2 (0.71) +0.00 (0.06)

CI = calving interval; SCS = somatic cell score.

+52 (56.0) +8.6 (2.66) +4.2 (1.33) +1.3 (0.58) +0.5 (0.21) +1.2 (0.62) −1.6 (0.86) +0.09 (0.06)

S. McCarthy et al. / Livestock Science 107 (2007) 19–28

21

Primiparous animals entering the herd from the spring 2003 onwards were bred from within each strain using sires concurrent to the different breeding objectives relative to that strain. Each strain therefore represented on average, thirteen sires over the 5 years of the study. The data consisted 99, 117, 117, 125 and 126 cows in the years 2001 to 2005, respectively. Animals were divided equally between strain of HF and FS (Table 2). In 2001 all animals were primiparous; in 2002, 45 were parity one and 72 parity two; in 2003, 9 animals were parity one, 45 parity two and 63 parity three; in 2004, 27 animals were parity one, 12 parity two and 86 of parity three and above, and in 2005, 27 animals were parity one, 18 parity two, while 81 were of parity three and above. In the present study parity was recoded as 1, 2, 3, and 4+.

designed to allow each strain to express its potential within each feed system largely unrestricted by limitations in feed supply while the aim of the HS was to reduce feed allowance. In all 5 years, animals were turned out to grass during the day in early February. Animals grazed grass day and night until mid-November, when they were housed only at night. After approximately December 1, they were housed day and night. During the housing period (mid-November to early February), animals from all feed groups were housed together as one group on cubicles and subdivided based on expected calving date. Cubicles were cleaned and covered with calcium carbonate daily.

2.2. Feed systems

Cows were milked twice daily at 07:00 and 15:30 in a 14-unit highline milking parlour. Entrance to the parlour was carried out according to feed system with animals in the MP feed system milked first and those in the HC feed system last. Milk yield was measured at each milking for each cow using electronic milk meters. Additionally, milking duration (in s) and milk flow (kg/min) were recorded at each milking for the years 2003 to 2005 inclusive. Milking duration was measured from clusters attachment until removal, carried out through automatic cluster removal. This eliminates possible effects of over milking on milkability variables measured. Clusters were automatically removed when cow milk flow fell below 0.2 kg/min. Individual cow milk samples were taken every other week at one morning milking and SCC determined using the Bentley 300 (Bentley Instruments Incorporated, USA). On average 17 samples were taken from each cow over the lactation period. All animals were forestripped prior to morning and evening milking to determine the presence of milk clots as an indicator of clinical mastitis (CM). The udder was also observed for redness, soreness and/or inflammation as indicators of CM. Clinical mastitis was assessed over the entire intercalving period. On identification of a case of CM, a sample of milk from the individual quarter was aseptically taken and sent to the laboratory for bacteriological analysis. These recorded cases are referred to in the present study as cases of CM and are based solely on the herdsman's interpretation of CM which is typical of CM as defined in most other studies (Pryce et al., 1999). In addition to individual quarter samples taken on observation of CM, quarter milk samples were also routinely taken on all cows at calving, drying off (average days in milk was 296) and at two other intermediate dates (average days in milk was 85 and 178, respectively)

There was a separate farmlet for each of the three feed systems. The three systems compared were: a high grass allowance feed system typical of spring calving herds in Ireland (MP, control); a higher concentrate feed system (HC) and a higher stocking rate system (HS). The MP feed system had an overall stocking rate of 2.47 cows/ha, nitrogen fertiliser input of 290 kg N/ha (from early January to late September) and received 325 kg concentrate/cow in early lactation with the remainder of the diet comprised of grazed grass. The HC feed system had a similar overall stocking rate and nitrogen fertiliser input as the MP feed system but a concentrate input of 1445 kg/cow. The HS group had similar concentrate (327 kg/cow) and nitrogen fertiliser inputs as the MP but had an overall stocking rate of 2.74 cows/ha. The MP and HC feed systems were Table 2 Number of dairy cows included in the 5-year analysis Strain a

Feed system b

Group

HP

HD

NZ

MP

HS

HC

No. of animals Year 1 Year 2 Year 3 Year 4 Year 5

33 39 39 41 42

33 39 39 42 42

33 39 39 42 42

33 39 39 41 42

33 39 39 42 42

33 39 39 42 42

69 49 41 36

69 49 41 36

69 49 41 35

69 49 41 36

69 49 41 36

No. of lactation records Parity 1 69 Parity 2 49 Parity 3 41 Parity 4+ 35 a

HP = high production; HD = high durability; NZ = New Zealand. MP = Moorepark feed system; HS = high stocking rate feed system; HC = high concentrate feed system. b

2.3. Animal measurements

22

S. McCarthy et al. / Livestock Science 107 (2007) 19–28

during the 4 years 2002 to 2005; only calving date samples were recorded in 2001. Milk samples were collected in an aseptic manner from all udder quarters into individual sterile plastic containers after drawing of foremilk. These samples were sent to the laboratory for bacteriological analysis as well as SCC quantification. In total 6888 quarter samples from 561 lactations were available where a bacteriological analysis had been performed. A total of 5007 quarter samples were analysed for level of SCC; the lower number of quarter samples with information on SCC compared to bacteriology was because routine samples at calving were never analysed for SCC. 2.4. Data handling Somatic cell count data consisted 10,336 SCC test day records across 584 lactations from 240 cows. Test day records were restricted to between 6 and 305 days in milk; 10,110 records remained. The natural logarithm transformation of SCC was used to normalise the distribution of SCC; the transformed variable will be herein referred to as somatic cell score (SCS). Lactation average SCS was calculated as the mean of all SCS test day records within cow-lactation. Mean SCS was also determined within three stages of lactation: 6 to 60 days in milk, 61 to 120 days in milk and 121 to 305 days in milk. Clinical mastitis was coded as either one if infection occurred in at least one udder quarter during the intercalving period or otherwise zero. Similarly lactations were considered to have incurred intramammary infection (IMI) if a positive bacteriological result occurred in at least one of the routine udder quarter analyses within lactation. Intramammary infection in the present study was dichotomised as the presence (IMI = 1) or absence (IMI = 0) of pathogens in only the routinely recorded quarter samples with a corresponding SCC greater than 250,000 cells/ml. An additional variable, high SCC (HSCC), was created for each routinely taken quarter sample and was defined as SCC of N250,000 cells/ml. As with CM and IMI, a lactation received a HSCC score of one if at least one udder quarter exhibited a SCC of N250,000 cells/ml within lactation; lactations not fulfilling this criteria received a value of zero. A total of 368 lactation milkability records were available for analysis. Only records between 6 and 305 days in milk were retained. Milking characteristic variables were only retained if both morning and evening records were present. Average milk flow is the milk yield divided by the time spent milking. Average daily milk flow (AMF; kg/min), peak daily milk flow (PMF; kg/min) and daily milking duration (in s) were positively skewed.

Outliers were therefore identified as those more than two interquartile ranges greater than 75% percentile or less than the 25% percentile for individual measurements. Following the removal of outliers (3.5% of records), AMF and PMF followed a normal distribution; milking duration persisted in being positively skewed. The natural logarithm of milking duration was used in order to achieve a normal distribution. Peak daily milk flow and maximum milking duration were firstly averaged across each week of lactation within cow in order to minimise the effect of any potential remaining outliers. Lactation maximum milking duration was identified and also the week in lactation when this occurred. Average daily milking duration (AMD) and average milk flow were estimated over the entire lactation and also within each stage of lactation: weeks 1 to 8 of lactation, weeks 9 to 17 of lactation and week 18 onwards. Average milk flow and maximum milking duration were also calculated within each stage of lactation. 2.5. Statistical analysis A mixed model using PROC MIXED (SAS, 2005) was used to determine the factors affecting average lactation SCS; cow was included as a repeated effect. Class variables tested in the model included strain, feed system and parity. Continuous covariates considered for inclusion in the model were predicted transmitting ability for milk yield, fat yield, protein yield, fat concentration and protein concentration as well as calving day of year, calving to conception interval and lactation length which were all centered within strain by parity. The relationship between SCS and the continuous covariates were visually assessed to identify the appropriate order of the polynomial. Higher order polynomials on the covariates were also tested in the model based on the F-test. Only factors significantly (P b 0.05) affecting SCS were retained in the model with the exception of strain and feed system which were forced into the model. Biologically plausible interactions were also tested for significance in the model. Differences between least squares means were tested using the t-test following the Bonferroni adjustment for multiple comparisons. An additional analysis was undertaken whereby arithmetic average of SCS within three stages of lactation was the dependent variable. The analysis was identical to that previously outlined with the addition of stage of lactation and its interactions, which were tested as fixed effects in the model. The binary nature of the quarter sample data coupled with the presence of repeated records per cow across

S. McCarthy et al. / Livestock Science 107 (2007) 19–28

23

Table 3 Effect of strain of Holstein–Friesian 1 and feed system 2 on average lactation somatic cell score (SCS) and SCS at different stages of lactation Strain

Lactation SCS b61 DIM 61–120 DIM N120 DIM ab

Feed system

HP

HD

NZ

P-value

S.E.M.

11.01b 10.77ab 10.82a 11.31a

10.99b 10.65a 10.78a 11.30a

11.38a 11.00b 11.19b 11.70b

0.01 0.001 0.001 0.001

0.075 0.096 0.096 0.096

3

MP

HS

HC

P-value

S.E.M.

11.09 10.82 10.87 11.38

11.23 10.85 10.95 11.56

11.07 10.75 10.97 11.38

NS 4 NS NS NS

0.072 0.090 0.089 0.089

Means with different superscripts within the same row are significantly (P b 0.05) different. HP = high production; HD = high durability; NZ = New Zealand. 2 MP = Moorepark feed system; HS = high stocking rate feed system; HC = high concentrate feed system. 3 S.E.M. is the average standard error of the mean. 4 NS = non-significant. 1

years, necessitated the use of generalised-estimating equations (GEE) in PROC GENMOD (SAS, 2005) to model the logit of the probability that a cow exhibited CM, IMI, or HSCC; cow was included as a repeated effect. A model was derived separately for each dependent variable with strain and feed system always forced into the model as class variables. Parity, also treated as a class variable, was also tested for significance in the model. Predicted transmitting ability for milk, fat and protein yield and fat and protein content, as well as calving day of year, calving to conception interval and lactation length were tested for significance in the model where each variable was treated as continuous and centered within strain by parity. Higher order polynomials were tested for significance in the model. Only significant (P b 0.05) variables were retained in the model. Significance was based on the GEE score. Interactions between significant main effects were also tested. Odds ratios were calculated as the exponent of the model solutions. The HP strain, the MP feed system and parity one animals were used as the reference classes within the respective variables.

Mixed model methodology in PROC MIXED (SAS, 2005) was used to analyse each of the milkability variables; AMF, PMF, AMD, maximum milking duration, and week of maximum milking duration. Cow was included as a repeated effect. Procedures and criteria used for the generation of the model of analysis were the same as outlined for the analysis of SCS. 3. Results Lactation average SCS across the entire dataset was 11.00 SCS (59,874 somatic cells/ml). In the current dataset 258 cases of CM were observed across 150 lactations (from the total of 584 lactations) over the 5 years. The number of lactations exhibiting at least one case of HSCC or IMI was 335 and 224, respectively. Mean (±S.D.) AMF, PMF, AMD, maximum milking duration, and week of lactation when maximum milking duration occurred, across the entire dataset, were 1.8 (±0.40) kg/min, 4.7 (±1.21) kg/ min, 6.7 (±0.20) log sec/day, 6.9 (±0.23) log sec/day, and week 21 (±11.3) of lactation, respectively.

Table 4 Effect of strain of Holstein–Friesian a, feed system b and parity on selected udder health traits Clinical mastitis Odds ratio Strain

Feed system

Parity

a b c

HP HD NZ MP HS HC 1 2 3 4+

1.00 1.80 1.30 1.00 0.98 1.10 1.00 0.91 1.09 1.21

95% CI

High somatic cell count P-value

Odds ratio

0.07

1.00 1.77 1.58 1.00 1.67 1.20 1.00 2.40 6.99 5.42

1.10–2.95 0.79–2.15 NS c 0.61–1.60 0.56–1.47 NS 0.51–1.65 0.57–2.09 0.67–2.18

95% CI

Intra-mammary infection P-value

Odds ratio

0.08

1.00 0.55 0.91 1.00 0.76 0.75 1.00 1.11 1.35 1.05

1.09–2.90 0.90–2.78 NS 0.95–2.94 0.71–2.02 b0.001 1.47–3.92 3.57–13.70 2.85–10.35

HP = high production; HD = high durability; NZ = New Zealand. MP = Moorepark feed system; HS = high stocking rate feed system; HC = high concentrate feed system. NS = non-significant.

95% CI

P-value b0.05

0.34–0.90 0.58–1.43 NS 0.48–1.22 0.47–1.20 NS 0.73–1.70 0.82–2.22 0.58–1.91

24

S. McCarthy et al. / Livestock Science 107 (2007) 19–28

Table 5 Effect of strain of Holstein–Friesian 1, feed system 2 and parity on average milk flow (AMF; kg/min), peak milk flow (PMF; kg/min), average milking duration (AMD; log sec/day), maximum milking duration (MMD; log sec/day) and the week of lactation when maximum milking duration (WMMD; week) occurred

Strain

HP HD NZ P-value S.E.M. 4 Feed HS system MP HC P-value S.E.M. Parity 1 2 3 4+ P-value S.E.M.

AMF

PMF

1.89 1.78 1.87 NS 3 0.046 1.74a 1.84a 1.96b b0.01 0.044 1.51a 1.67b 1.91c 2.18d b0.001 0.042

4.60a 6.68a 6.92a 6.70a 6.91a 4.47a 5.45b 6.60b 6.76b b0.05 b0.001 b0.05 0.141 0.021 0.032 4.73 6.66ab 6.90a 4.86 6.63a 6.84b 4.94 6.69b 6.85b NS b0.05 b0.001 0.177 0.019 0.018 3.89a 6.58a 7.00a 4.40b 6.70b 6.99a 5.01c 6.69b 6.83b d c 5.72 6.64 6.70c b0.001 b0.001 b0.001 0.108 0.020 0.018

AMD

MMD

matic cells/ml) strains. Throughout the first stage of lactation the HD strain had the lowest SCS, the NZ strain the highest, while the HP strain was intermediate. In the middle and final stages of lactation the NZ strain again exhibited the highest SCS, while the HD and HP strains were not significantly different from each other. An interaction between stage of lactation and strain was not significant. Table 4 shows the effect of strain of Holstein–Friesian on CM, HSCC and IMI. While having a greater likelihood of showing CM and HSCC, the HD and NZ strains had a reduced likelihood of incurring IMI. High durability animals were 1.80 times more likely to exhibit CM than HP animals and 1.38 times more likely than NZ animals. High durability animals were 1.77 times more likely to exhibit HSCC than HP animals and 1.12 times more likely than NZ animals; the odds of a NZ animal having a HSCC was 1.58 times that of a HP animal. Intra-mammary infection was also affected by strain of Holstein–Friesian (P b 0.05) with the odds of a HD animal showing IMI 0.55 and 0.61 times that of the HP and NZ animals, respectively. Strain of Holstein–Friesian had a significant effect on milkability (Table 5). There were no significant interaction between strain of HF and feed system for any of the milkability variables measured and therefore only the main effects are reported. The NZ strain had a higher PMF and shorter maximum milking duration and AMD than both the North American strains. The trend for maximum milking duration persisted even after animal daily milk yield was adjusted for in the model (results not shown). Table 6 shows the interaction of strain of Holstein–Friesian and feed system with stage of lactation. Peak milk flow was unaffected by stage of lactation and is therefore omitted. Again, no interaction between strain of HF and feed system was observed.

WMMD 20.6 21.2 21.2 NS 0.152 21.0 21.0 21.1 NS 0.149 20.8a 21.2a 21.7b 20.1c 0.001 0.14

abcd

Means with different superscripts within the same column are significantly different. 1 HP = high production; HD = high durability; NZ = New Zealand. 2 MP = Moorepark feed system; HS = high stocking rate feed system; HC = high concentrate feed system. 3 NS = non-significant. 4 S.E.M. is the average standard error of the mean.

3.1. Effect of strain of Holstein–Friesian No interaction was observed between strain of HF and FS and therefore only the main effects are displayed in Table 3. Average lactation SCS for the NZ strain (87,553 somatic cells/ml) was significantly higher than both the HP (60,475 somatic cells/ml) and HD (59,278 so-

Table 6 Effect of strain of Holstein–Friesian 1, feed system 2 and parity on average milk flow (kg/min), average milking duration (log sec/day), and maximum milking duration (log sec/day) across three stages of lactation 3 Average milk flow

Average milking duration

Week of lactation 1–8 Strain

Feed system

abcdefg 1 2 3 4

HP HD NZ HS MP HC

9–17 ad

2.13 2.09a 2.24d 2.06a 2.20d 2.20d

abd

2.11 2.01b 2.15a 1.96b 2.11ae 2.19de

Pvalue

18+ c

1.73 1.66c 1.67c 1.55c 1.66c 1.84b

0.01

0.001

Week of lactation 1–8

9–17 a

6.83 6.81ab 6.66d 6.78 6.75 6.77

bf

6.79 6.78f 6.62e 6.73 6.71 6.74

Maximum milking duration Pvalue

18+ e

6.59 6.57ce 6.50c 6.55 6.53 6.58

0.01

NS 4

Week of lactation 1–8

9–17 a

6.89 6.92b 6.78c 6.90a 6.84b 6.85b

d

6.86 6.89a 6.74c 6.87e 6.81f 6.81f

Means with different superscripts between treatments are significantly different. HP = high production; HD = high durability; NZ = New Zealand. MP = Moorepark feed system; HS = high stocking rate feed system; HC = high concentrate feed system. Reported levels of significance are for the two-way interaction with stage of lactation. NS = feed system by stage of lactation interaction not significant; feed system had no significant effect within stage.

18+ 6.74c 6.78c 6.67e 6.76c 6.68d 6.74g

Pvalue 0.001

0.001

S. McCarthy et al. / Livestock Science 107 (2007) 19–28

3.2. Effect of feed system Feed system had no significant effect on SCC (Table 3). Clinical mastitis, HSCC and IMI were also unaffected by feed system (Table 4). Animals on the HC feed system had a higher AMF and AMD while those on the HS feed system had a greater maximum milking duration (Table 5). On adjustment for milk yield, differences in AMD were no longer present, however animals in the HS feed system maintained the longest (P b 0.001) maximum milking duration. During the first two stages of lactation, animals in the HS feed system displayed a lower AMF compared to animals in both the MP and HC feed systems (Table 6). In the final stage of lactation, animals in the both the HS and MP feed systems had lower AMF than those in the HC feed system. Maximum milking duration was highest for animals in the HS feed system across all stages of lactation. 3.3. Effect of parity First parity animals had the lowest average lactation SCS (47,572 somatic cells/ml), fourth parity animals the highest (120,572 somatic cells/ml), while second and third parity animals were intermediate (56,387 somatic cells/ml and 66,836 somatic cells/ml, respectively). A significant interaction between parity and stage of lactation (P b 0.001) was observed (Fig. 1). Parity had no significant effect on CM or IMI but older animals were more likely to incur HSCC (Table 4). First parity animals had the lowest AMF and PMF (Table 5) while fourth parity animals were significantly higher than all other parities for both variables. First parity animals had the shortest AMD and longest maximum milking duration. Parity trends on AMD

Fig. 1. Average somatic cell score for parity 1 (♦), 2 (●), 3 (▴), 4+ (■) across stage of lactation.

25

and maximum milking duration persisted when milk yield was adjusted in the model (results not shown). 4. Discussion Average lactation SCS across the entire dataset was 11.00 SCS (59,874 cells/ml), which is similar to the findings of Laevens et al. (1997) who reported mean lactation SCC of 51,000 cells/ml, but lower than those reported by others (Lopez-Villalobos et al., 2003). The incidence of clinical mastitis (percentage of cows calving during the study with at least one case) in the study was low at 26% which is similar to that reported by Lacy-Hulbert et al. (2002) and Kossaibati et al. (1998) for other pasture-based systems but much lower than other international, predominantly confinement based studies (Bartlett et al., 2001; White, 2000). Washburn et al. (2002) reported higher incidence of CM in confinement compared to pasture based systems in the US with the latter incidence being similar to that observed in the present study. Peak milk flow rate of 4.74 kg/min across the entire study is similar to that reported by Weiss et al. (2004). 4.1. Effect of strain of Holstein–Friesian on udder health and milking characteristics Using a subset of the current dataset, Horan et al. (2005) reported significantly higher milk yields in both the HP and HD strains compared to the NZ strain. Nonetheless, on correction for 305 days' milk yield in the present study, the effect of Holstein–Friesian strain on lactation average SCS persisted, therefore eliminating a “dilution effect” as the sole contributor to the higher SCS in the NZ animals. Differences in SCS may therefore be a consequence of the greater relative emphasis traditionally placed on mammary conformation in North American and European breeding programs. Lund et al. (1994) concluded that selection for improved udder conformation will lessen the increase in SCC associated with selection for increased milk production. The predicted transmitting abilities for SCS of the three strains (Table 1) are also in agreement with the current findings, all strains being significantly different with the NZ strain highest and the HD strain lowest. The constantly higher SCS throughout lactation in the NZ animals indicates that the causative factor of the higher SCS is consistent over lactation. One contributing factor may relate to the higher PMF observed in this strain relative to both North American strains. Grindal and Hillerton (1991) reported an increased incidence of mastitis in cows with a higher PMF. Naito et al. (1964)

26

S. McCarthy et al. / Livestock Science 107 (2007) 19–28

reported a negative correlation between tonus of the sphincter muscle and maximum rate of flow, therefore the higher PMF of the NZ strain may reflect reduced tension of the sphincter muscle in the teat canal. Nonetheless, the higher SCS of the NZ strain is in contrast to studies reported by Turner et al. (2003) who in a comparison of overseas and New Zealand Holstein– Friesians, found no strain effect on SCC in late lactation while Lacy-Hulbert et al. (2002) reported that Holstein– Friesian cows, not of NZ origin, had higher SCC than NZ cows. Despite the association between SCS and clinical and sub-clinical mastitis (Sheldrake et al., 1983), no significant strain difference was observed in the incidence of CM, similar to previous studies (Lacy-Hulbert et al., 2002). Clinical mastitis is influenced by both management and non-management effects such as parity (Laevens et al., 1997), stage of lactation (Berry and Meaney, 2005), and udder conformation (Lund et al., 1994). While differences in SCS in the present study were not biologically significant (i.e. were not reflected in CM incidence), one can not ignore the significant difference found between strains. It is hypothesised that in an environment of greater infection risk or challenge, such genetic differences would be of considerable importance (Peeler et al., 2000; Barkema et al., 1998, 1999) and therefore would materialize as differences in CM. Furthermore, the inconsistency between average lactation SCS and CM incidence may also arise through differences in bacterial cell type as environmental pathogens are more highly correlated with mastitis than contagious pathogens (De Haas, 2003). On examination of CM, predominant pathogens included Staphylococcus aureus, Streptococcus uberis and Escherichia coli while Staphylococcus aureus and Staphylococcus epidermidis were predominant in IMI samples. Bacteriology data showed no differences in the causative agents between strains (results not shown). These results suggest that the observed strain difference in average lactation SCS in the present study arises through a difference in severity or duration of the infection (De Haas, 2003). These data also suggest that the frequency of HSCC, which approached significance between the strains, reflected the likelihood of CM more accurately than SCS. The shorter milking duration in the NZ strain is partly attributed to the conscious phenotypic selection against slower milking cows in New Zealand. However, milking speed is not explicitly included in the New Zealand total merit index (Harris et al., 1996), Berry et al. (2005) reported a strong influence of milking speed in the risk of voluntary culling in New Zealand

commercial dairy herds. This is a consequence of the high cow throughput sought in New Zealand milking parlours. 4.2. Effect of feed system on udder health and milking characteristics Feed system was found to have no significant effect on udder health, corroborating findings of Turner et al. (2003). The authors are unaware of any complete lactation study investigating the impact of concentrate feeding level on udder health where all production originated from within a grazing environment (HC vs MP), or any study investigating the effect of grazing intensity (HS vs MP) on udder health. Previous studies were of short duration (Lacy-Hulbert et al., 1999), based on total mixed ration (TMR) diets (Pryce et al., 1999), or results were confounded with environmental differences (Lacy-Hulbert et al., 2002). Wicks and Leaver (2006) documented a significant effect of concentrate in the diet on SCC in animals within a confinement system, while Lacy-Hulbert et al. (2002) reported significantly more clinical and subclinical mastitis in late lactation cows on a TMR diet compared to cows grazing pasture. However, differences in feed systems in the latter study were confounded with housing, as animals receiving the TMR diet were kept in confinement areas. A higher rate of CM has been reported for cows on confinement feeding systems than on pasture (Washburn et al., 2002). All animals in this study completed almost the entire lactation from within a grazing environment; with animals in the HC feed system receiving their concentrate allowance at AM and PM milking. A negative effect of reduced total daily dry matter intake on Log SCC was realised in a short duration study by Lacy-Hulbert et al. (1999) where cows in late lactation received 16 and 8 kg dry matter/cow/day of pasture and grass silage, respectively. Differences in total dry matter intake of such a magnitude were not encountered in this study. In agreement with the present study, Waage et al. (1998) found no effect of concentrate proportion in the diet on CM in heifers. However, a direct influence of feeding level on veterinary assisted CM has been reported in relation to the amount fed on the day of calving (Arvidson et al., 2005). Nonetheless, in this study, no difference was imposed on the level fed on the day of calving across the feed systems. Therefore results of the present study along with the lack of impact of concentrate feeding level on fertility (Horan et al., 2004) suggests that concentrate feeding level within the range

S. McCarthy et al. / Livestock Science 107 (2007) 19–28

adopted on most Irish farms, does not impact on the health or fertility of animals. Despite reported differences in milk yield across feed systems (Horan et al., 2005), no feed system effect on PMF was observed, agreeing with the poor relationship between milk yield and PMF observed in other studies (Weiss et al., 2004); the correlation between daily milk yield and PMF in the present study was 0.27 (P b 0.001). The similarity in PMF between feed systems is consistent with the absence of significant differences in udder health between animals across the feed systems given the previously reported association between PMF and udder health (Grindal and Hillerton, 1991). However, a significantly higher AMF was observed for animals in the HC feed system, confirming the positive correlation between AMF and milk yield as reported by Weiss et al. (2004). The correlation between AMF and milk yield in the present study was 0.64 (P b 0.001). When adjusted for daily milk yield, feed system differences in AMF and AMD were no longer realised, however animals in the HS feed system maintained a significantly higher maximum milking duration. 4.3. Effect of parity on udder health and milking characteristics Although no significant effect of parity on CM or IMI was observed there was a tendency for a greater likelihood of either CM or IMI in older parities. Pryce et al. (1999) reported an increase in disease incidence, including mastitis, while Weller et al. (1992) and De Haas (2003) found higher lactation SCC as parity number increased, corroborating results of the present study. Older cows have a longer time period at risk to infection therefore leading to a higher SCS, on average, in later parities. Berry and Meaney (2005) also reported a higher likelihood of CM in animals that previously experienced a case of CM. This was attributed to an increased susceptibility in older animals or due to the persistence of infection throughout the dry period. Another factor pertaining to poorer udder health in older animals may relate to the increased PMF with parity number observed in the present study. The significant effect of parity on all milk flow variables was realised both prior to and after correction for milk yield. Hence, independent of milk yield primiparous cows had lower AMF and PMF and had a longer maximum milking duration. Correction for daily milk yield indicates differences in milking duration to be a consequence of the observed differences in milk flow. Increased AMF with parity corroborates previous reports (Firk et al., 2002), while Petersen et al. (1986) also reported increasing PMF with increasing parity number. Higher

27

PMF in older animals may be associated with the possible weakening of the teat end with age or as a result of damage of the teat sphincter as parity number increases due to harmful effects of machine milking (Maltz et al., 2000). 5. Conclusions This study identified somatic cell count and milking characteristic differences between three strains of Holstein–Friesian dairy cows. While the study highlights an important genetic influence on somatic sell count, differences in average lactation SCC on the study did not materialise as differences in clinical mastitis incidence between genetic groups due to the generally excellent udder health status of the research herd. Feed system influenced milking characteristics while having no effect on udder health. Higher parity animals had higher SCC and peak milk flow rate than lower parities. Acknowledgements This study is part of a joint project between Dexcel (New Zealand), Massey University (New Zealand), and Teagasc (Moorepark). We would like to acknowledge the support of Professor Colin Holmes (Massey University). We thank the staff of Curtin's farm for their co-operation, care and management of the experimental animals and Mr. Jim Flynn for technical assistance over the course of the study. References Arvidson, A.K., Ekma, T., Emanuelson, U., Gustavsson, A.H., Sandgren, C.H., Holtenius, K., Waller, K.P., Svensson, C., 2005. Feeding factors associated with clinical mastitis of first parity cows. Proceedings of the 4th IDF International Mastitis Conference, pp. 629–634. Barkema, H.W., Van Der Ploeg, J.D., Schukken, Y.H., Lam, T.J.G.M., Benedictus, G., Brand, A., 1998. Management style and its association with bulk milk somatic cell count and incidence rate of clinical mastitis. J. Dairy Sci. 82, 1655–1663. Barkema, W.H., Schukken, Y.H., Lam, T.J.G.M., Beiboer, M.L., Benedictus, G., Brand, A., 1999. Management practices associated with the incidence rate of clinical mastitis. J. Dairy Sci. 82, 1643–1654. Bartlett, P.C., Agger, J.F., Houe, H., Lawson, L.G., 2001. Incidence of clinical mastitis in Danish dairy cattle and screening for nonreporting in a passively collected national surveillance system. Prev. Vet. Med. 48, 73–83. Berry, D.P., Amer, P.R., 2005. Derivation of a health sub-index for the Economic Breeding Index in Ireland. Technical report to the Irish Cattle Breeding Federation. (August). Berry, D.P., Meaney, W.J., 2005. Cow factors affecting the risk of clinical mastitis. Irish J. Agric. Food Res. 44, 147–156. Berry, D.P., Buckley, F., Dillon, P., Evans, R.D., Veerkamp, R.F., 2004. Genetic relationships among linear type traits, milk yield, body weight, fertility and somatic cell count in primiparous dairy cows. Irish J. Agric. Food Res. 43, 161–176.

28

S. McCarthy et al. / Livestock Science 107 (2007) 19–28

Berry, D.P., Harris, B.L., Winkelman, A., Montgomerie, W., 2005. Phenotypic associations between traits other than production and longevity in New Zealand dairy cattle. J. Dairy Sci. 88, 2962–2974. Berry, D.P., O'Brien, B., O'Callaghan, E.J., O'Sullivan, K., Meaney, W.J., 2006. Temporal trends in bulk tank somatic cell count and total bacterial count in Irish dairy herds during the past decade. J. Dairy Sci. 89, 4083–4093. Coulon, J.B., Gasqui, P., Barnouin, J., Ollier, A., Pradel, P., Pomies, D., 2002. Effect of mastitis and related germ on milk yield and composition during naturally occurring udder infection in dairy cows. Anim. Res. 51, 383–393. De Haas, 2003. Somatic cell count patterns. Improvement of udder health by genetics and management. Ph.D. Thesis. Wageningen University, The Netherlands. Firk, R., Stamer, E., Junge, W., Krieter, J., 2002. Systemic effects on activity, milk yield, milk flow rate and electrical conductivity. Arch. Tierz. Dummerstorf 45, 213–222. Grindal, R.J., Hillerton, J.E., 1991. Influence of milk flow rate on new intramammary infection in dairy cows. J. Dairy Res. 58, 263–268. Gröhn, Y.T., 2000. Milk yield and disease: towards optimising dairy herd health and management decisions. Bov. Pract. 34 (1). Harris, B.L., Clark, J.M., Jackson, R.G., 1996. Across breed evaluation of dairy cattle. Proc. N.Z. Soc. Anim. Prod. 56, 12–15. Horan, B., Mee, J.F., Rath, M., O'Connor, P., Dillon, P., 2004. The effect of strain of Holstein–Friesian cow and feed system on reproductive performance in seasonal-calving milk production systems. Anim. Sci. 79, 453–468. Horan, B., Dillon, P., Faverdin, P., Delaby, L., Buckley, F., Rath, M., 2005. The interaction of strain of Holstein Friesian cows and pasture based feed systems on milk yield, body weight and body condition score. J. Dairy Sci. 88, 1231–1243. Kossaibati, M.A., Hovi, M., Esslemont, R.J., 1998. Incidence of clinical mastitis in dairy herds in England. Vet. Rec. 143, 649–653. Lacy-Hulbert, S.J., Woolford, M.W., Nicholas, G.D., Prosser, C.G., Stelwagen, K., 1999. Effect of milking frequency and pasture intake on milk yield and composition of late lactation cows. J. Dairy Sci. 82, 1232–1239. Lacy-Hulbert, S.J., Kolver, J.H., Williamson, J.H., Napper, A.R., 2002. Incidence of mastitis among cows of different genotypes in differing nutritional environments. Proc. N.Z. Soc. Anim. Prod. 62, 24–29. Laevens, H., Deluyker, H., Schukken, Y.H., De Meulemeester, L., Vandermeersch, R., De Muelenaere, E., De Kruif, A., 1997. Influence of parity and stage of lactation on somatic cell count in bacteriologically negative dairy cows. J. Dairy Sci. 80, 3219–3226. Lopez-Villalobos, N., Scott, J., Smith, Z., Holmes, C.W., Shadbolt, N.M., Harvey, T.G., 2003. Frequency of mastitis and variation in somatic cell counts throughout the lactation in cows managed organically or conventionally; year 1. Proc. N.Z. Soc. Anim. Prod. 63, 138–139. Lund, T., Miglior, F., Dekkers, J.C.M., Burnside, E.B., 1994. Genetic relationships between clinical mastitis, somatic cell count, and udder conformation in Danish Holsteins. Livest. Prod. Sci. 39, 243–251.

Maltz, E., Renemann, D.J., Davis, M.A., 2000. A study of blood flow and oxygen concentration of teat end tissue before and after machine milking. ASAE Annual International Meeting, Paper # 003012. Milwaukee, Wisconsin. Miglior, F., Muir, B.L., van Doormaal, B.J., 2005. Selection indices in Holstein cattle of various countries. J. Dairy Sci. 88, 1255–1263. Mrode, R.A., Swanson, G.J.T., 1996. Genetic and statistical properties of somatic cell count and its suitability as an indirect means of reducing the incidence of mastitis in dairy cattle. Anim. Breed. Abstr. 64, 847–857. Naito, M., Shoda, Y., Nagai, J., Nagasawa, H., Shinohara, H., Terada, T., 1964. Relationship between various characters of teats and milking characteristics in Jersey cows. Jpn. J. Zootech. Sci. 35, 52–60. Peeler, E.J., Green, M.J., Fitzpatrick, J.L., Morgan, K.L., Green, L.E., 2000. Risk factors associated with clinical mastitis in low somatic cell count British dairy herds. J. Dairy Sci. 83, 2464–2472. Petersen, M.L., Hansen, L.B., Young, C.W., Miller, K.P., 1986. Rates of milk flow and milking times resulting from selection for milk yield. J. Dairy Sci. 69, 556–563. Prins, D., 2002. Economic value of milkability in dairy Cattle. MSc. Thesis, Wageningen University, The Netherlands. Pryce, J.E., Nielsen, B.L., Veerkamp, R.F., Simm, G., 1999. Genotype and feeding system effects and interactions for health and fertility traits in dairy cattle. Livest. Prod. Sci. 57, 193–201. SAS Institute, 2005. User's Guide Version 8.2.0 Edition. SAS Institute, Inc., Cary, NC. Sheldrake, R.F., McGregor, G.D., Hoare, R.J.T., 1983. Somatic cell count, electrical conductivity, and serum albumin concentration for detecting bovine mastitis. J. Dairy Sci. 66, 548–555. Turner, S.A., Williamson, J.H., Thomson, N.A., Roche, J.R., Kolver, E.S., 2003. Diet and genotype affect milk lactoferrin concentrations in late lactation. Proc. N.Z. Soc. Anim. Prod. 63, 87–90. Waage, S., Sviland, S., Odegaard, S.A., 1998. Identification of risk factors for clinical mastitis in dairy heifers. J. Dairy Sci. 81, 1275–1284. Washburn, S.P., White, S.L., Green, J.T., Benson, G.A., 2002. Reproduction, mastitis, and body condition of seasonally calved Holstein and Jersey cows in confinement or pasture systems. J. Dairy Sci. 85, 105–111. Weiss, D., Weinfurtner, M., Bruckmaier, R.M., 2004. Teat anatomy and its relationship with quarter and udder milk flow characteristics in dairy cows. J. Dairy Sci. 87, 3280–3289. Weller, J.I., Saran, A., Zeliger, Y., 1992. Genetic and environmental relationships among somatic cell count, bacterial infection, and clinical mastitis. J. Dairy Sci. 75, 2532–2540. White, S.L., 2000. Investigation of pasture and confinement dairy feeding systems using Jersey and Holstein cattle. Master thesis submitted to North Carolina State University. Wicks, H.C.F., Leaver, J.D., 2006. Influence of genetic merit and environment on somatic cell counts of Holstein–Friesian cows. Vet. J. 172, 52–57.