Feed intake, body weight and milk production: genetic analysis of different measurements in lactating dairy heifers

Livestock Production Science, 37 (1993) 37-51

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Elsevier Science Publishers B.V., Amsterdam

Feed intake, body weight and milk production: genetic analysis of different measurements in lactating dairy heifers Peter J.M. van Elzakker and Johan A.M. van Arendonk Department of Animal Breeding, WageningenAgricultural University, Wageningen,Netherlands (Accepted 28 April 1993)

ABSTRACT Phenotypic and genetic correlations between measurements of feed intake, body weight and production within and between 4 periods in the first 15 weeks of lactation have been estimated. Measurements were available on 358 dairy heifers during 2 week periods starting at 2, 5, 9 and 13 weeks after calving. Heifers were progeny of 38 sires. The diet consisted of 6 kg concentrates and roughage ad libitum. Genetic parameters were estimated by REML fitting an animal model. Heritability of roughage intake decreased from 0.32 in week 2 to 0.18 in week 13. Fat protein corrected milk production (FPCM) had a heritability of 0.33 in week 2 which increased to 0.47 in week 13. Heritability of feed conversion changed from 0.17 to 0.29 from week 2 to 13. The largest differences in heritability were found between week 2 and week 5. The genetic correlation between roughage intake and feed conversion changed from 0.24 in week 2 to - 0.57 in week 13. The genetic correlation between measurements in week 2 and 9 was 0.47 for energy intake, 0.80 for roughage intake and 0.99 for FPCM production. Estimated genetic correlations and heritabilities have been used to determine the relative efficiency of single trait selection using measurements in one single period. It is concluded that for an accurate evaluation of animals for feed intake and feed conversion measurement during at least two periods are needed. Key words: Feed intake; Feed conversion; Genetic parameter; Selection

INTRODUCTION

Feed costs are the most important variable costs in milk production. Despite this recognition selection at this moment is only based on milk production and no attention is paid to differences in feed costs between the individual cows. Heritabilities for feed intake, body weight and feed efficiency found by Gravert (1985), Hooven et al. (1972), Miller et al. ( 1971 ), Persaud et al. Correspondence to: Johan van Arendonk, Department of Animal Breeding, Wageningen Agricultural University, P.O. Box 338, 6700 AH Wageningen, Netherlands.

0301-6226/93/$06.00 © 1993 Elsevier Science Publishers B.V. All fights reserved.

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P.J.M. VAN ELZAKKENAND J.A.M. VAN ARENDONK

( 1991 ) and Svendsen et al. (1990) varied between 0.20 and 0.80. This indicates that possibilities for selection are present. Incorporating feed intake and efficiency in selection programmes is hindered by the fact that measuring feed intake of lactating cows on commercial farms is too expensive. Averdunk et al. (1987) reviewed the possibilities to use measurements on growing young bulls. Nucleus breeding schemes offer the opportunity for recording and hence selecting for feed intake and feed conversion of potential bull dams. The cost of recording feed intake can be reduced by using a part lactation measurement. Measurement during an early part of lactation will lower costs and will result in a shorter generation interval and higher selection intensity given selection capacity. The relative efficiency of selection on part lactation measurements depends on the genetic correlation between part and whole lactation and the heritability of both measurements. For milk production, Wilmink (1987) concluded that selection on part lactation measurements is more efficient than selection on 305-day productions. Persaud et al. (1991 ) estimated the genetic correlations for feed intake, feed efficiency and milk production measured in different periods in first parity cows. Little is known about the heritabilities and correlations between feed intake, feed conversion and production traits during the initial part of lactation. Bines ( 1976 ) indicated that physiological changes occur as a result of onset of lactation, negative energy balance and the peak in milk production. This might affect the correlations between traits, when measured at different times in early lactation. These effects are expected to be largest during the first 100 days of lactation. Analyses of measurement at different moments in early lactation could give information about the behaviour of correlations during early lactation. This information is important in determining the optimum moment of measurement. This study is aimed at estimating phenotypic and genetic correlations between feed intake, body weight, weight change, feed conversion and production within and between 4 periods in the first 15 weeks of lactation in dairy heifers. The information on the behaviour of heritabilities and correlations during the first 15 weeks of lactation will be used to determine the optimum moment of measurement. MATERIAL AND METHODS

Animals Sires used in the experiment were selected from 800 potential AI bulls tested for feed intake (120-365 days of age) at a central test station from 1979 through 1985. During the test period, bulls were fed roughage (hay) ad lib. and a restricted amount of concentrates, according to age. Bulls were selected for either high or low dry matter roughage intake and only bulls that entered

FEED INTAKE, BODY WEIGHT AND MILK PRODUCTION

39

the progeny test were eligible for selection. Every year, five to eight sires were used in each group, and most sires were used for more than one year to avoid completely confounding sires with years. During the experiment 19 sires were used in each selection group. The effective phenotypic selection differential between groups was 3.12 units of phenotypic standard deviation of dry matter roughage intake. The selection experiment was more extensively described by Korver and Vos ( 1986 ). Three generations of cows were produced, the first by random mating of sires with cows in the University's dairy herd. Animals of second and third generations were produced by random mating of previous generation animals with sires selected in the same direction. A total of 358 lactating heifers, born in 1983 through 1987, was used in the analyses of feed intake and production measurements in early lactation of which 231 were in the first, 113 were in the second, and 14 were in the third generation. Traits

The heifers used in this experiment calved between December 1984 and April 1989 at an average age of 732 days. After calving, the heifers were placed in a pen and fed a diet of roughage ad lib. and 6 kg of concentrates per day for the first 15 weeks of lactation. During four periods of two weeks cows were placed in a pen equipped with electronic feeding gates which allowed measurement of individual roughage intake; periods started at 2, 5, 9 and 13 weeks after calving. Each two-week period consisted of three days for adaptation and 11 days in which intake of both roughage and concentrate was measured on a daily basis. Concentrate intake was measured using an electronic feeding station. Daily energy intake during each period was calculated as the sum of roughage and concentrate intake weighted by their energy content. The average of the daily intake during the four periods is used as the measure for intake during 105 days of lactation. Body weight was measured at the start and end of each period of measurement. Body weight used in the analysis refers to the average of these two measurements. Weight gain during a two week period was calculated as the change in body weight during that period divided by 14 days. Weight gain during 105 days of lactation was calculated as the difference in average body weight between the last period of measurement and the first divided by 77 days, that being the difference in number of days in lactation between the two periods. Milk production and fat and protein percentage was measured weekly for every cow during the first fifteen weeks of lactation. The 105-days production is calculated from records during all 15 weeks while only 2 records are used to calculate the production during each period. Fat and protein corrected milk (FPCM), which reflects energy contents of milk produced, was calculated with the formula given by Korver ( 1982 ):

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P.J.M. VAN ELZAKKEN AND J.A.M. VAN ARENDONK

FPCM = (0.349 + 0.107*%fat + 0.067*%protein )*milk yield

( 1)

Feed conversion was calculated as energy intake divided by FPCM production. Residual feed intake per animal, which is the energy intake after adjustment for metabolic weight, weight gain and FPCM production, was calculated as: RFIi = MEtoti - b l ' W E I G H T °'75 - b2*FPCMi - b 3*GAINi

(2)

with RFIi MEtoti

residual feed intake of animal i ( i = 1..... 358) (MJ ME d -1 ); = average daily energy intake from roughage and concentrate (MJMEd-1); WEIGHTi = average body weight (kg); FPCMi = average daily FPCM production (kg d-1 ); GAINi = average daily weight gain (kg d - 1 ); b 1,b2,b3 = energy requirements per unit of metabolic body weight (MBW), FPCM and GAIN, estimated by using MBW, FPCM and GAIN as covariables in model (3) (see below). =

In addition to measurements during the lactation, feed intake and body weight were also measured during a 2 week period starting at approximately 50 days before calving. During that period heifers were fed roughage ad lib. and no concentrates. Daily samples of roughage were analyzed for dry matter content. A combined sample of a week was analyzed for energy (ME) and digestible protein (dgp) content by the method described by Van Es (1978). The unweighed average of dry matter content of the roughage was 46%, whereas it contained on average 10.5 MJ ME and 142 g dgp per kg dry matter. The standard deviation was 8%, 1.0 MJ and 12 g, respectively. In the whole experimental period the concentrate had a dry matter content of 90% and contained 11.7 MJ ME and 133 g dgp per kg dry matter.

Method of analysis Traits were analyzed with the following animal model: Yijka = Y*Sj + HFk + SEL*GEN1 + baseAGEi + ANIMALi + eijkl

(3)

with Yijkl

Y*Sj HFk SEL*GENI

trait on cow i, calving in year-season j in breed class k and selection generation 1; = effect of year-season of calving j (j = 1, .... 25 ); = effect of breed of animal class k ( k = 1..... 5 ); = effect of selection by generation group 1 (1 = 1,...,4 ); ----

FEED INTAKE, BODY WEIGHT AND MILK PRODUCTION

ba~e AGEi ANIMALi eijk~

= = = =

41

regression on age at calving; age at calving of animal i; random effect of animal i ( i = 1,...,358); error term.

Pedigree information comprised sire for each animal in generation 1 and sire and dam for second and third generation animals. Five seasons of calving were considered: December, January, February, March, and April-May. Five classes of breed of animal were defined: ( I ) 0% (2) > 0-40% (3) > 40-60% (4) > 60-80% and ( 5 ) > 80-100% of Holstein Friesian genes. Crosses were between Dutch and Holstein Friesians. Breed of animal was included in the model to ensure that animal effects would reflect within breed difference. The distribution of cows over breed groups (%HF) can be found in Van Arendonk et al. ( 1991 ). Groups were formed according to selection group of the sire (high, low) and generation of the animal. Due to the low number of animals in generation 3, only two generations (1 and/> 2) were distinguished. The four selection-generation groups were used to account for the differences in average merit of sires as a result of selection on roughage intake in sires. The choice of model ( 3 ) is discussed by Korver et al. ( 1991 ) who used that model, excluding AGEi, in the analysis of data from growing heifers during the same experiment. Heritabilities, covariables and fixed effects were estimated using univariate Restricted Maximum Likelihood (REML) fitting an animal model. Estimates were obtained using a derivative-free REML algorithms (DFREML) (Meyer, 1989, 1991 ). Phenotypic and genetic correlations were obtained from bivariate analyses. Starting values were obtained from sire-model analyses. Iteration was stopped when the variance of -2*log (likelihood) for the simplex points was less than 10 -8. To ensure that the global maximum of the function was found, another round of iterations was started using results of the previous round as starting values as suggested by Meyer (pers. com.). When estimates did not change convergence was confirmed. In addition, the estimated heritabilities in the bivariate analyses were required to be close to the estimates from the univariate analyses. RESULTS

Heritabilities per period Means, adjusted phenotypic standard deviations and univariate estimates for heritabilities for traits at different moments during the lactation are shown in Table 1 and Table 2. Heritabilities of the average measurement (105-days) during the period were higher than those of individual measurements (Table 2 ). The lower heritabilities were partly caused by a higher phenotypic standard deviation (Table 1 ). The heritability for roughage intake decreased from

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P.J.M. VAN ELZA

N AND J.A.M. VAN ARENDONK

TABLE1 Overall mean (~) and adjusted phenotypic standard deviation (av) for feed intake, feed conversion, and production traits in 4 different weeks and the average of these measurements during early lactation (105d) Period

105d

Trait

~

week 2 ap

~

week 5 av

Roughage intake (kgDM/d) 9.68 0.79 8.97 1.04 Energyintake(MJME/d) 1 6 0 . 5 8 8.77 153.46 12.04 Bodyweight'(kg) 489.74 32.19 482.55 32.54 Weight gainb (kg/d) 0.22 0.23 0.02 ncd FPCM c (kg/d) 19.55 2.32 19.73 2.68 Feed conversion (MJ ME/kg) 8.37 1.05 7.95 1.11 Residual feed intake (MJME/d) 62.17 7.29 41.47 10.50

week 9

~

ap

9.66 162.62 484.57 0.40 19.79

1.06 9.88 1 . 0 4 1 0 . 2 0 1.09 12.30 165.62 12.06 165.59 13.08 32.84 491.93 32.94 499.73 34.58 1.01 0.37 ncd 0.23 ncd 2.56 19.69 2.28 19.21 2.22

8.41

~

week 13

1.18

~v

8.59

1.09

:~

ap

8.79

1.13

69.47 11.32 78.54 11.13 72.74 ncd

"Body weight=aveage of weights taken in four periods of measurement in case of 105 d and average of weights taken at start and end of single period of measurement (week 2, 5, 9, 13 ). bWeight gain in 105 d is calculated from difference between average weight in last and first period of measurement and weight change for single periods is difference between weight at beginning and end. cFPCM = fat- and protein-corrected milk = (0.349 + 0.107% fat + 0.067% protein )*kg milk. %c = estimates did not converge. TABLE2 Heritabilities (h 2) for feed intake, feed conversion, and production traits in 4 different periods and the average during early lactation ( 105 d) Period

105d

week 2

week 5

week 9

week 13

Trait

b2

h2

h2

h2

h2

Roughage intake (kg D M / d ) Energy intake (MJ M E / d ) Body weight (kg) Weight gain (kg/d) FPCM (kg/d) Feed conversion (MJ ME/kg) Residual feed intake (MJ M E / d )

0.49 a 0.33 0.85 0.26 0.51 0.41 0.18

0.32 0.32 0.86 nc d 0.33 0.17 0.15

0.20 0.15 0.75 0,09 0.41 0.22 0.05

0.19 0.20 0.80 nc d 0.49 0.29 0.12

0.18 0.01 0.77 nc d 0.47 0.29 nc d

aStandard errors (s.e.) of heritabilities varied between 0.09 and 0.17.

0.32 in week 2 to 0.20 in week 5 and remained constant thereafter. The heritability for 105-d roughage intake was 0.49. The heritability for FPCM production increased from 0.33 in week 3 to 0.47 in week 13. For feed conversion the heritability changed from 0.17 in week 2 to 0.29 in week 9 and 13. During week 2, 5 and 9 heritability estimates for roughage and energy intake were comparable. This was not the ease for week 13 where a very low heritability for energy intake was found. The reason for this low estimate is not clear.

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43

Body weight and roughage intake were also measured in pregnant heifer approximately 5 weeks before calving. On average the heifers had a body weight of 522 kg and a daily roughage dry matter intake of 8.38 kg, where phenotypic standard deviation was 33.08 and 1.01, respectively. The estimated heritability was 0.82 for body weight and 0.25 for roughage intake. This is comparable with the values found for roughage intake and body weight after calving in the separate periods of measurement. Estimates for daily gain and residual feed intake did not converge in some periods. Measurement of daily gain per period was not very accurate because animals were only weighted once at the start and end of a period. The problems for residual feed intake in week 13 were very probably caused by the low heritability for energy intake during that period.

Correlations per period The genetic and phenotypic correlations between traits in different periods are given in Tables 4 to 7.No correlations have been estimated for traits for which the univariate heritability estimates did not converge. Correlations for the 105-d measurements are in Table 3. Genetic correlations between some traits were found to change between periods, some of which will be discussed hereafter. Genetic correlation between roughage and energy intake was higher than 0.84 during the different weeks of measurement. This high correlation is to be expected given that all animals were offered a fixed amount of concentrates. The fact that correlation is not unity is likely caused by the variation in energy content of the roughage. Except for week 13, during which a very low heritability for energy intake was found, correlations of roughage intake with other traits were very similar to those for energy intake. From the average measurements over all periods it can be concluded that roughage intake has a slight positive genetic correlation (0.27) with feed conTABLE 3 Phenotypic (above) and genetic (below diagonal) correlations for average feed intake, body weight, and conversion traits from week 2 upto week 15 and body weight and roughage intake as pregnant heifer Trait

1

l Roughage intake 2 Energy intake 3 FPCM 4 Body weight 5 Weight gain 6 Feed conversion 7 Residual feed intake 8 Body weight pregnant heifer 9 Roughage intake pregnant heifer

1.00 0.43 0.55 0.10 0.27 0.98 0.48 0.54

2 0.40 0.50 0.63 0.23 0.03 0.95 0.21 0.76

3

4 0.32 0.37

5

6

7

8

9

0.32 0.03 0.11 0.59 0.29 0.29 0.35 0.08 0.11 0.11 0.13 0.28 -0.03 -0.42 -0.89 0.01 0.21 0.18 -0.04 0.14 0.22 -0.01 0.82 0.42 -0.96 0.27 0.47 -0.01 0.05 0.00 -0.97 0.38 1.00 0.39 - 0 . 0 6 - 0 . 0 4 0.02 - 0.02 - 0 . 0 2 0.17 - 0.08 0.11 0.32 0.92 0.12 - 0 . 0 5 - 0 . 1 8 0.46 0.46 0.83 0.39 - 0 . 0 9 0.11 0.94

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P.J.M. VAN ELZAKKENAND J.A.M. VAN ARENDONK

TABLE 4 Phenotypic (above) and genetic (below diagonal) corrleations for average feed intake, body weight, and conversion traits in week 2 Trait

1

2

1 Roughage intake 2 Energy intake 3 FPCM 4 Body weight 5 Feed conversion 6 Residual feed intake 7 Body weight pregnant heifer 8 Roughage intake pregnant heifer

0.85 0.42 0.68 0.24 0.97 0.62 0.72

3 0.41

0.65 0.70 -0.07 0.96 0.62 0.99

0.28 0.35 0.29 -0.80 -0.06 0.49 0.78

4

5

6

7

8

0.34 0.38 0.16

0.18 0.01 -0.81 0.07

0.34 0.90 -0.01 0.00 0.14

0.30 0.33 0.26 0.85 -0.05 -0.03

0.36 0.30 0.21 0.45 -0.03 0.09 0.46

0.19 0.01 0.94 0.88

0.99 0.11 -0.08

-0.08 0.37

0.94

TABLE 5 Phenotypic (above) and genetic (below diagonal) correlations for average feed intake, body weight, and conversion traits in week 5 Trait

1

2

3

4

5

6

7

8

9

1 Roughage intake 2 Energy intake 3 FPCM 4 Body weight 5 Weight gain 6 Feed conversion 7 Residual feed intake 8 Body weight pregnant heifer 9 Roughage intake pregnant heifer

0.39 0.27 0.24 0.03 0.24 0.53 0.10 0.23 0.95 0.29 0.27 0.07 0.26 0.90 0.18 0.24 0.60 0.62 0.03 - 0 . 1 0 -0.81 0.01 0.22 0.20 0.67 0.79 0.06 0.18 0.14 0.01 0.81 0.41 0.20 0.45 -0.46 0.57 0.15 0.00 0.13 0.05 - 0 . 1 9 -0.15 -0.89 0.37 0.12 0.38 - 0 . 1 0 - 0 . 0 4 0.99 0.99 0.21 0.02 -0.03 0.82 -0.05 0.09 0.46 0.53 0.36 0.92 0.43 -0.22 -0.23 0.46 0.62 0.62 0.64 0.87 0.38 - 0.28 0.22 0.94

TABLE 6 Phenotypic (above) and genetic (below diagonal) correlations for average feed intake, body weight, and conversion traits in week 9 Trait

1

2

3

4

5

6

7

8

1 Roughage intake 2 Energy intake 3 FPCM 4 Body weight 5 Feed conversion 6 Residual feed intake 7 Body weight pregnant heifer 8 Roughage intake pregnant heifer

0.29 0.31 0.23 0.26 0.17 0.19 0.17 0.84 0.31 0.21 0.30 0.87 0.16 0.14 0.70 0.59 -0.06 -0.78 -0.03 0.13 0.14 0.55 0.50 0.10 0.20 0.00 0.78 0.40 -0.26 -0.19 -0.89 0.40 0.28 - 0 . 0 2 - 0 . 0 5 0.99 0.89 - 0 . 0 9 0.01 0.99 -0.05 -0.00 0.49 0.41 0.20 0.90 - 0 . 0 4 - 0 . 1 6 0.46 0.18 0.20 0.31 0.80 - 0 . 2 0 - 0 . 2 3 0.94

FEED INTAKE, BODY WEIGHT AND MILK PRODUCTION

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TABLE 7 Phenotypic (above) and genetic (below diagonal) correlations for average feed intake, body weight, and conversion traits in week 13 Trait

1

1 Roughage intake 2 Energy intake 3 FPCM 4 Body weight 5 Feed conversion 6 Body weight pregnant heifer 7 Roughage intake pregnant heifer

0.99 0.52 0.58 -0.57 0.54 0.38

2

3 0.34

0.93 1.00 -0.75 0.94 0.98

4

5

6

7

0.20 0.16 -0.15

0.25 0.33 -0.63 0.26

0.21 0.15 0.09 0.75 0.58

0.15 0.14 0.08 0.36 0.02 0.46

0.26 0.08 0.25 - 1.00 0.15 0.22

0.52 0.90 0.76

- 0.01 -0.13

0.94

version (Table 3). This correlation, however, differs from the correlation in the different periods. The genetic correlation between roughage intake and feed conversion changed from 0.24 in week 2 to -0.57 in week 13. This means that a genetic improvement in feed intake from week 5 to week 13 produces a more efficient cow. The genetic correlation between body weight and FPCM production changed from 0.29 in week 3 to -0.25 in week 13. A similar change was found in the phenotypic correlation. This indicates that heavier cows produce more milk in the first weeks of lactation. The negative correlation during the later periods, however, indicate that cows with a higher body weight after the production peak produce less milk. This change in correlation might be the result of differences between cows in the priority of energy for gain and production, respectively (Bauman et al., 1985 ). The genetic correlation between body weight and roughage intake before calving is 0.94 which is higher then the correlation between these traits after calving (0.55 to 0.68 ). The genetic correlation in pregnant heifers is equal to the correlation found in growing dairy heifers (Korver et al., 1991 ). The lower correlation in lactating heifers is to be expected because body weight and roughage intake after calving are also affected by milk production. Body weight and roughage intake before calving showed a high genetic relation with body weight in the different periods after calving. Genetic correlations of body weight and roughage intake in pregnant heifers with FPCM production and to a lesser extent with roughage and energy intake decreased during the lactation. This indicates that body weight and roughage intake before calving is reasonable predictors for FPCM production, energy and roughage intake in early lactation.

Correlations for traits measured in different periods In Table 8 the genetic and phenotypic correlations between traits measured in week 2, week 9 and 105 days are given. The correlations between measure-

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P.J.M. VAN ELZAKKEN AND J.A.M. VAN ARENDONK

TABLE 8 Phenotypic (above) and genetic (below diagonal) correlations for feed intake, body weight, and conversion traits over periods Period

GEMVweek 2

GEMVweek 9

week 2week 9

GEMVweek 2

rg Trait Roughage intake Energy intake Body weight FPCM Feed conversion

0.90 0.75 0.99 0.98 0.99

0.91 0.99 0.99 0.99 0.98

GEMVweek 9

week 2week 9

rp

0.80 0.47 0.98 0.99 1.00

0.28 0.62 0.92 0.83 0.30

0.73 0.74 0.95 0.90 0.74

0.36 0.26 0.91 0.44 0.48

ments in week 2 and 9 is 0.47 for energy intake and 0.80 for roughage intake. For the other traits the correlation between week 2 and 9 was larger than 0.98. These correlations indicate that roughage and energy intake later in lactation differs from intake in early lactation. From the correlation of measurements in individual periods and the average measurement ( 105 days), it can be concluded that energy intake in week 2 is genetically different from later measurements. DISCUSSION

Heritabilities In this study heritabilities for intake and conversion in the separate periods were lower than the estimate for the average 105 day trait. By averaging measurements in the four periods the environmental variance was reduced as can be seen from the phenotypic standard deviations (Table 1 ). The difference in environmental variance will be the main reason for the lower heritabilities in separate periods when compared to the estimate of the average 105 day trait. For FPCM production and feed conversion an increase in heritability during the lactation was found while heritabilities decreased for energy and roughage intake (Table 2 ). Heritability estimates for roughage intake and energy intake within the first 12 weeks of lactation in literature varied between 0.29 and 0.49 whereas estimates after week 12 vary between 0.19 and 0.25 (Persaud et al., 1991; Svendsen et al., 1990). These values are comparable with the estimates found in this study. The results are further in line with Korver (1988 ) who concluded from literature that genetic variation for intake appeared to be more fully expressed early in lactation. Heritabilities for FPCM individual periods in this study are comparable

FEED INTAKE, BODY WEIGHT AND MILK PRODUCTION

47

with estimates for FCM-yield found by Hooven et al. ( 1972 ). They found the lowest values to be in the first 60 days (0.48). Studies by Persaud et al. ( 1991 ) and Wilmink (1987) presented estimates of 0.16 for production in the first 30 days and values between 0.25 and 0.30 thereafter. FPCM yield and energy intake are used to calculate feed conversion and, therefore, the relative rather than the absolute value of heritability estimates for these traits should be used in comparing literature. The estimated heritabilities for food conversion (Table 2 ) were increased from 0.17 in week 2 to 0.29 in week 9. This increase is similar to that in FPCM yield which demonstrates the large influence of FPCM yield on food conversion which was to be expected given the genetic correlations (Tables 4 and 6). In the literature (Hooven et al., 1972; Persaud et al., 1991 ) heritability for feed conversion remained rather constant during lactation. In those experiments concentrates were fed according to milk production which might have caused the difference with results found in this study. Results for weight gain were based on single measurements of live weight at the beginning and end of each period which is not very accurate due to variation in rumen fill. A better measure for weight change can be derived when cows are weighted more frequently. Better estimates of weight gain would also result in better estimates for residual feed intake. The heritabilities for residual feed intake in this study should be regarded with care since the regression coefficients for FPCM and weight gain used in the model (2) differed greatly from values in literature (Van Arendonk et al., 1991 ). Genetic correlations Clear changes over time were found for the genetic correlation between FPCM and body weight and between roughage intake and feed conversion. The genetic correlation between roughage intake and feed conversion changed from 0.24 in week 2 to - 0 . 5 7 in week 13. Similar results were found by Hooven et al. (1972) who estimated a genetic correlation between energy intake and efficiency of 0.07 in early lactation (30-60d) and 0.67 in mid lactation ( 121-150d). Svendsen et al. (1990) found a correlation of 0.45 and 0.40 between FCM and roughage intake in the first and second trimester of lactation. Estimation of heritabilities for body weight and roughage intake before calving did not differ much from estimates after calving. The correlations ofprepartum weight with milk production (Tables 4 to 7 ) show that especially in early lactation a high prepartum body weights result in cows that produce more FPCM. Linet al. (1985) reported heritabilities of 0.22 and 0.27 for prepartum and postpartum body weights, which are much lower than estimates in this study. They found a negative correlation between prepartum weight and milk yield during first lactation. Standard errors of estimates of genetic correlations are expected to be high

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P.J.M. VAN ELZAKKENAND J.A.M. VAN ARENDONK

given the small number of animals used in the analysis. Experiments involving feed intake measurements on individual animals will, however, always be relatively small in size. Estimates of different experiments need to be combined in drawing conclusions. In combining estimates it is important to account for the differences between experiments in feeding regimen and time of measurement (Korver, 1988 ).

Relative efficiency Measurement of food intake during a short period may well be possible under practical breeding programmes. The reduced costs of such measures must be weighted against the reduced accuracy of prediction of whole lactation performance. To compare the relative efficiency of selection on measurements during one individual period instead of the average of 4 periods ( 105 d), a procedure given by Falconer (1989 ) was used. The efficiency of selection was defined as: rGpcwhp/hw where r~p~w is the genetic correlation between the individual period and the 105-day period, and hp and hw are the square roots of the heritabilities in the individual and 105 d period. It is assumed that the intensity of selection is the same for both part and whole lactation. Efficiencies for different traits and periods in Table 9. These results show that selection for intake and weight traits is relatively most efficient when measurements from week 2 were used. For FPCM yield and feed conversion the maximum was found in week 9 and week 13, respectively. Measurement of FPCM yield after the production peak is also recommended by Wilmink ( 1987 ). Hooven et al. (1972) calculated a relative efficiency of selection for whole lactation feed efficiency of 0.72 and 0.89 when using 31-60 days and 121-150 days part lactation records. The values for feed conversion were smaller in this study. The difference can be caused by the fact that animals in this study were not fed according to production. The relative efficiencies of selection based on measurements during an individual period are high for body weight and FPCM yield in week 9 and 13. For intake and efficiency TABLE9 Relative eficiency of selection for 15-weeks lactation of intake weight or conversion, using the 2-week periods as the criteria for selection Part lactation Trait

Week 2

Week 5

Week 9

Week 13

Roughage intake Energy intake Body Weight FPCM yield Feed conversion

0.59 0.73 1.00 0.63 0.41

0.40 0.45 0.87 0.80 0.53

0.35 0.60 0.93 0.95 0.69

0.37 0.03 0.90 0.91 0.71

FEED INTAKE, BODY WEIGHT AND MILK PRODUCTION

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traits the relative efficiency of using measurements during an individual period are much smaller. For these traits measurement during a single period is not sufficient. The relative efficiencies for FPCM and feed conversion in Table 9 show that measurements should be taken later in lactation (week 9 or 13 ). For the other traits, measurements should be taken early in lactation (week 3 ). Measurement of intake and body weight in early lactation is supported by Korver ( 1988 ) and Simm et al. ( 1991 ). Gibson ( 1987 ) found the best prediction of lactation feed efficiency when mid lactation measurements were used. This result, however, refers to prediction of phenotypes rather than genotypes as was used in this study. Persaud et al. ( 1991 ) found a genetic correlation of feed intake between week 3 and 8 with total lactation of 0.85. When comparing this with the value of 0.98 between week 15 and 20 one can see that there is quite some difference. It should be kept in mind that the results in Table 9 do not present the efficiency of selection for whole lactation performance because feed intake after 15 weeks in lactation were not available. It can be concluded that for feed intake and feed conversion more than one period of measurement during the lactation are needed. The heritabilities of measurements in individual periods (Table 2) and the genetic correlations between periods (Table 8 ) can be used to determine the optimum periods of measurement. In addition it needs to be defined what traits are included in the breeding goal and what economic weights are appropriate for the given price and production circumstances. Feed intake is a limiting factor during the first part of the lactation and it can be argued that this trait should be improved by selection (Korver, 1988 ). For a reduction of feed costs for cows with a given level of production, feed conversion and feed intake capacity during the entire lactation including the dry period are of importance. In improvement in feed conversion will reduce the amount of energy required while an improvement in feed intake capacity will allow for a greater proportion of cheaper roughages in the diet. ACKNOWLEDGEMENTS The authors greatfully acknowledge the contributions of Arnoud van der Lugt and Henk Vos in analyzing the data.

REFERENCES Averdunk, G., Korver, S. and Andersen, B.B., 1987. Performancetesting of young bulls for efficiencyand beeftraits in dairy and dual-purposecattle. Report of E.A.A.P.workinggroup. Livest. Prod. Sci., 20: 287-298. Bauman, D.E, McCutcheon,S.N., Steinhour,W.D., Eppard. P.J. and Sechen,S.J., 1985. Sources

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of variation and prospects for improvement of productive efficiency in the dairy cow: a review. J. Dairy Sci., 60: 583-592. Bines, J.A., 1976. Regulation of food intake in dairy cows in relation to milk production. Livest. Prod. Sci., 3:115-128. Falconer, D.S., 1989. Introduction to quantitative genetics. Longman Scientific & Technical, 3rd ed.: 438. Gibson, J.P., 1987. Part-lactation predictors of complete lactation milk-energy yield, food intake and food conversion efficiency. Livest. Prod. Sci., 17: 323-335. Graven, H.O., 1985. Genetic factors controlling feed efficiency in dairy cows. Livest. Prod. Sci., 13: 87-99. Hooven, N.W., Miller, R.H. and Smith J.W., 1972. Relationships among whole- and part-lactation gross feed efficiency, feed consumption and milk yield. J.Ddairy Sci., 55: I 113-1122. Korver, S., 1982. Feed intake and production in dairy breeds dependent on the ration. PhDthesis, Wageningen Agricultural University, Wageningen. Korver, S., 1988. Genetic aspects of feed intake and feed efficiency in dairy cattle: a review. Livest. Prod. Sci., 20: 1-13. Korver, S. and Vos, H., 1986. Selection on feed intake in dairy cattle. Proc. 3~a World Congr. Genet. Applied to Livest. Prod. Lincoln, Nebraska. Vol. 11: 285-290. Korver, S., van Eekelen, E.A.M., Vos, H., Nieuwhof G.J. and van Arendonk, J.A.M., 1991. Genetic parameters for feed intake and feed efficiency in growing dairy heifers. Livest. Prod. Sci., 29:49-59. Lin, C.Y., McAllister, A.J. and Lee, A.J., 1985. Multitrait estimation of relationships of firstlactation yields to body weight changes in holstein heifers. J. Dairy Sci., 68: 2954-2963. Meyer, K., 1989. Restricted Maximum Likelihood to estimate variance components for animal models with several random effects using a derivative-free algorithm. Genet. Sel. Evol., 21: 317-340. Meyer, K., 1991. Estimating variances and covariances for multivariate animal models by Restricted Maximum Likelihood. Genet. Sel. Evol. 23: 67-78. Miller, R.H., Hooven, N.W., Smith, J.W. and Creegan, M.E., 1971. Feed consumption differences among lactating cows. J. Dairy Sci., 55: 454-459. Persaud, P. and Simm, G., 1991. Genetic and phenotypic parameters for yield, food intake and efficiency of dairy cows fed ad lib. Anim. Prod., 52: 445-450. Simm, G., Persaud, P., Neilson, D.R., Parkinson, H. and McGuirk, B.J., 1991. Predicting food intake in dairy heifers from early lactation records. Anim. Prod., 52: 00-00. Svendsen, M., Skipenes, P. and Mao, I.L., 1990. Milk production'as a composite trait. Heritabilities, repeatabilities and trends during first semester of lactation in primiparous cows. Proc. 4 th World Congr. Genet. Applied to Livest. Prod., Edinburgh. Vol 14:147-150. Van Arendonk, J.A.M., Nieuwhof, G.J., Vos, H. and Korver, S., 1991. Genetic aspects of feed intake and efficiency in lactating dairy heifers. Livest. Prod. Sci., 29: 263-275. Van Es, A.J.H., 1978. Feed evaluation for ruminants. I. The systems in use from May 1977 onwards in The Netherlands. Livest. Prod. Sci., 5:331-345. Wilmink, J.B.M., 1987. Efficiency of selection for different cumulative milk, fat and protein yields in first lactation. Livest. Prod. Sci., 17:211-224.

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RESUME van Elzakker, P.J.M. et van Arendonk, S.A.M., 1993. Quantit6s Ing6r6es, Poids Vif et Production Laiti~re: Analyses G6n6tiques de Diff6rentes Mesures Effecctu6es chez des G6nisses Laiti~res. Livest. Prod. Sci., 37:37-51 (en anglais). Des corr61ations ph6notypiques et g6n6tiques entre les quantit6s ing6r6es, le poids corporel et al production laiti~re ont 6t6 effectu6es ~ l'int6rieur de et entre 4 p6riodes durant les 15 premieres semaines de lactation. Ces mesures ont 6t6 effectu6es sur 358 g6nisses laiti~res pendant des p6riodes de 2 semaines d6marrant 2, 5, 9 et 13 semaines apr~s le v~lage. Les g6nisses provenaient de 38 reproducteurs. Le r6gime consistait en 6 kg de concentr6 et du fourrage ~ volont6. Les param~tres g6n6tiques avaient 6t6 estim6s par REML simulant un module animal. L'h6ritabilit6 de la quantit6 de fourrage ing6r6e a diminu6 de 0.32 pendant la semaine 2 ~ 0.18t pendant la semaine 13. La production de lait corrig6e des mati~res grasses et des mati~res azot6es (FPCM) a eu une h6ritabilit6 de 0.33 pendant la semaine 2 qui a augment6 jusqu'h 0.47 pendant la semaine 13. L'h6ritabilit6 de l'indice de consommation a vari6 de 0.17 ~ 0.29 de la semaine 2 ~ la semaine 13. Les plus grandes diff6rences dans l'h6ritabilit6 ont 6t6 observ6es pendant la semaine 2 et la semaine 5. La corr61ation g6n6tique entre les quantit6s de fourrage ing6r6es et rindice de consommation a vari6 de 0.24 pendant la semaine 2 ~ 0.57 pendant la semaine 13. La corr61ation g6n6tique entre les mesures effectu6es pendant la semaine 2 et la semaine 9 at 6t6 de 0.47 pour les quantit6s d'6nergie ing6r~es, de 0.80 pour les quantit6s de fourrage ing6r6es et de 0.99 pour la production de FPCM. Les corr61ations g6n~tiques et les h6ritabilit~s ont 6t6 utilis6es pour d~terminer l'efficacit6 relative de la s61ection sur un caract6re prenant en compte les mesures d'une p6riode donn6e. En conclusion il apparait que, pour une bonne pr6diction de la capacit6 d'ingestion et de l'indice de consommation des animaux, il est n6cessaire d'avoir recours ~t au moins deux p6riodes de mesure. KURZFASSUNG Van Elzakker, P.J.M. und van Arendonk, J.A.M., 1993. Futteraufnahme K/Srpergewicht und Milchproduktion: Genetische Untersuchungen unterschiedlicher Messungen bei laktierenden F~irsen. Livest. Prod. Sci, 37:37-51 (aufenglisch). Fiir die Merkmale Futteraufnahme, K6rpergewicht und Milchleistung wurden ph~itnotypische und genetische Korrelationen zwischen und innerhalb yon vier Zeitabschnitten w~ihrend der ersten 15 Laktationswochen geschiitzt. Von 358 F~irsen standen Daten iiber zweiw/Schige MeBperioden, jeweils beginnend mit der Woche 2, 5, 9 und 13 nach der Kalbung, zur Verf'tigung. Die F~irsen stammten von 38 Bullen ab. Die Ration bestand aus Grundfutter ad libitum und 6 kg Kraftfutter. Die genetischen Parameter wurden mit einem Tiermodell nach der REML-Methode gesch~itzt. Die Heritabilit~it der Grundfutteraufnahme nahm yon 0,32 f'tir die zweite Woche auf0,18 in Woche 13 ab. Die auf Fett- und Proteingehalt korrigierte Milchleistung (FPCM) hatte eine Heritabilit~it von 0,33 in Woche 2, die auf0,47 in der 13. Woche anstieg. Die Heritabilitiit der Futterverwertung ~inderte sich von Woche 2 auf 13 von 0,17 auf 0,29. Die gr6gten Unterscheide in der Heritabilit~it wurden zwischen der zweiten und fiinften Woche gefunden. Die genetische Korrelation zwischen der Grundfutteraufnahme und der Futterverwertung ~inderte sich von 0,24 in der zweiten auf - 0 , 5 7 in der 13. Woche. Die genetischen Korrelationen zwischen den Messungen der Wochen 2 und 9 betrugen 0,47 ftir Energieaufnahme, 0,80 fiir Grundfutteraufnahme und 0,99 f'tir die FPCM-Leistung. Die geschiitzten genetischen Korrelationen und Heritabilit~iten wurden verwendet, um die relative Effizienz einer Einmerkmalsselektion mit Messungen in nur einem Zeitabschnitt zu bestimmen. Es wird gefolgert, dab ftir eine genaue Zuchtwertsch~itzung der Tiere f'tir die Merkmale Futteraufnahme und Futterverwertung Messungen von mindestens zwei Zeitabschnitten erforderlich sind.