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Livestock Production Science 63 (2000) 39–54

www.elsevier.com / locate / livprodsci

Crossbreeding for dairy production in the lowland tropics of

Kenya

I. Estimation of individual crossbreeding effects on milk production and

reproductive traits and on cow live weight

a ,

_*

b c b

A.K. Kahi

, W. Thorpe , G. Nitter , R.L. Baker

a

Institute of Animal Production in the Tropics and Subtropics, Hohenheim University, 70593 Stuttgart, Germany

b

International Livestock Research Institute, P.O. Box 30709, Nairobi, Kenya

c

Institute of Animal Breeding and Husbandry, Hohenheim University, 70593 Stuttgart, Germany

Received 13 November 1998; received in revised form 5 May 1999; accepted 24 May 1999

Abstract

Crossbreeding parameters for milk production and reproductive traits and for cow live weight (LW) of crosses of Ayrshire (A), Brown Swiss (B), Friesian (F) and Sahiwal (S) cattle were estimated using data from a dairy herd in the lowland coastal tropics of Kenya. An individual animal model was fitted to the data to estimate the breed cross means of 25 genotypes. The means were then regressed on gene proportion of breeds and on the coefficients of heterosis (or dominance) and recombination (or epistasis) using the dominance, Dickerson and Kinghorn models and a model that included dominance and

additive3additive interaction effects (Model D). When comparing models, estimates of crossbreeding parameters showed

similar patterns, although the magnitude of the estimates differed between models. Relative to A, F showed significantly positive breed effects for lactation milk yield (MY) (ranging from 1033 to 1139 kg for different models), annual milk yield

(AMY) (884 to 1210 kg), calving interval (CI) (217 to245 days) and MY expressed per unit of metabolic weight (12.45 to

13.36 kg). B showed favourable, but smaller than F, additive breed effects for these traits. S showed the smallest additive

breed effects for MY (2768 to 2795), AMY (2551 to 2562 kg) and MY expressed per unit of metabolic weight (25.89 to

26.08). Significant heterosis in the cross B3S was only found for MY (296 to 426 kg), AMY (382 to 409 kg), CI (215 to

222 days) and MY expressed per unit of metabolic weight (3.07 to 3.30 kg) in the dominance and Dickerson models.

Negative recombination and additive3additive interaction effects were obtained for MY and MY expressed per unit of

metabolic weight in the crosses A3B and B3S in the Dickerson model and Model D. Epistasis effects were also negative

for MY and MY expressed per unit of metabolic weight in the Kinghorn model. The Dickerson model or Model D seem

Keywords: Crossbreeding; Cow live weight; Crossbreeding parameters; Dairy cattle; Tropics

1. Introduction *Corresponding author. Tel.: 149-711-4593294; fax: 1

49-Crossbreeding has become increasingly accepted

711-4593290.

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40 A.K. Kahi et al. / Livestock Production Science 63 (2000) 39 –54

production in the tropics. Crossbreeding allows for Early assessment is required to avoid at the early considerable flexibility in matching complementary stages the problems associated with making sub-breed types to local environmental resources and optimal choices of breeds for crossbreeding. When constraints (Gregory and Cundiff, 1980). Previous selecting among B. taurus breeds for systems in studies have shown that the first generation (F )1 which the smallholder sector is a major contributor cross is superior to lower grades (Madalena et al., to dairy production, more emphasis should be on 1990; Thorpe et al., 1993; Rege et al., 1994; Syrstad, milk yield per unit of metabolic weight (MW) and 1996). Results from 80 reports summarised by Rege not the MY per se (Thorpe et al., 1993). Therefore, (1998) showed that grades higher that 50% exotic information on LW and on milk production ex-did not perform any worse than the F in most traits,1 pressed per unit of LW and of MW is needed in except calving interval which was longer in higher order to design efficient mating systems for improve-grades. ment of biological efficiency.

The Sahiwal (S) has been the B. indicus breed Design of efficient crossbreeding systems requires most frequently used in tropical dairy crossbreeding reliable estimates of crossbreeding parameters. By because it is considered unequalled in additive breed extrapolating the existing estimate of crossbreeding effects for milk production (Cunningham and Syr- parameters, the merit of crossbred genotypes can be stad, 1987). Trail and Gregory (1981) reported predicted. If the genetic model is inappropriate so is excellent pure-bred and crossbred performances of the extrapolation (Kinghorn and Vercoe, 1989). the S breed in a range of tropical production systems Therefore the choice of analysis models is important and environments. The B. taurus breeds that have for the analysis of crossbred populations. In cattle been used in crossbreeding with the S include breeding, the most commonly applied model was Ayrshire (A), Brown Swiss (B), Friesian (F) and derived by Dickerson (1969, 1973). This model Jersey (Cunningham and Syrstad, 1987). The choice accounts for heterosis and epistasis interactions of B. taurus breeds has been determined by several expressing the loss of favourable genetic interaction factors. For example, in production systems in which within gametes. However, heterosis in this model milk volume has a higher monetary value than milk includes a part of the additive3additive epistasis in fat yield (as is the case in Kenya), A, B and F cattle addition to dominance. Kinghorn (1980, 1982) de-are most suitable. However, Ahlborn-Breier and veloped a model where heterosis effects are only Hohenboken (1991) reported small breed differences based on dominance effects but which accounts for between the F and Jersey breeds for first lactation various kinds of epistasis effects. Of the epistasis milk fat yield in pastoral systems in New Zealand. effects, the additive3additive interactions are the At Kilifi Plantations in coastal Kenya, the source most important. Therefore the most important effects of data for this study, the A, B and most recently the would be captured by a model with additive popula-F have been used for crossbreeding with S for dairy tion differences together with heterosis effects production. During the 1960s and early 1970s, the caused by dominance gene effects and additive3

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A.K. Kahi et al. / Livestock Production Science 63 (2000) 39 –54 41

additive3additive effects. In most of the tropics, In the early 1990s a fourth breed, the F, was current consensus in dairy development is that efforts introduced and mated to the above genotypes with are best targeted at the smallholder dairy sector. the aim of replacing the A breed in the crosses. In Therefore a complete estimation of crossbreeding the present analysis only data from the first genera-parameters should also include prediction of per- tion crosses of Friesians (F) are included.

formance of alternative crossbreeding strategies in Generally matings were by artificial insemination relation to their implementation in the smallholder (AI); they were not influenced by relative body size dairy sector. This is the subject of a companion of the breed. The A, F (the European strain) and S paper (Kahi et al., 2000). semen was from the Kenya National AI service, while B semen was imported from the USA. In cases where the cows did not conceive after two AI

2. Materials and methods services, they were grazed together with crossbred bulls for at least two natural services. These bulls 2.1. Data source, herd description and were bred in the Kilifi herd and belonged to any of

management the above genotypes.

Herd management has been described by Gregory Data were made available by a private dairy ranch and Trail (1981), Thorpe et al. (1994), Kahi et al. (Kilifi Plantations) in Coast Province, Kenya. The (1995) and Mackinnon et al. (1996). Briefly, the ranch is located in Kilifi District 60 km north of general management practices were as follows: each Mombasa. The region has an average annual rainfall calf was identified to its dam within 24 h of birth, of 1000 mm and relative humidity of 80%. The first trained to suck on an artificial teat over the first 4 rains generally fall towards the end of March. They days, and fed colostrum from its dam during that are heavy in April and May and decrease gradually period. The calf was reared subsequently on whole until October. The second rains start towards the end milk at a rate of 1.5 kg three times a day until of October and last until December or January. The attaining 55 kg LW. Thereafter, and up to weaning at highest temperatures (monthly average, 308C) occur about 90 kg, they were fed 1.5 kg whole milk in two during January and February, while the lowest rations. Fresh concentrate and clean water were temperatures (monthly average, 228C) occur in June always available ad libitum. The calves were vacci-and July (Jaetzold vacci-and Schmidt, 1983). nated against viral diseases, and sprayed regularly The herd, which was established in 1939 from a with acaricide to control ticks. They were de-continuous two-breed rotational crossbreeding sys- wormed at about six to eight weeks of age and again tem involving the Sahiwal (S) and Ayrshire (A) immediately before weaning.

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frequency and the reasons of culling in the different For the analysis of the milk production traits, the following fixed effects were fitted: genotype (breed age-classes before the introduction of the F breed

cross) of the cow which consisted of 25 classes with were described by Thorpe et al. (1994).

different sire and dam combinations and hence different breed and heterosis contributions; lactation 2.2. Statistical methods

number (1, 2, 3, 4 or .4) and year-season of calving where each year from 1975 to 1997 has four Live weight (LW; kg) and five milk production

seasons: January to March for the first dry season; and reproductive traits were analysed: lactation milk

April to June for the main wet season; July to yield (MY; kg); lactation length (LL; days); calving

September and October to December as the sec-interval (CI; days); annual milk yield (AMY; kg);

ondary dry and wet seasons, respectively. For the and daily milk yield (DMY; kg). The AMY was

analysis of LW, year-season of calving included each calculated as (MY/ CI)3365, while DMY was

de-year from 1995 to 1997, each with four seasons; fined as MY/ LL. Records where LL was less than 60

physiological status of the cow at time of weighing days or greater than 1000 days were discarded.

consisted of four classes: empty; first trimester of Analysis of a subset of these data including 20

pregnancy; second trimester; and third trimester. The genotypes by Mackinnon et al. (1996) showed that

age in days at weighing date was fitted as a linear inclusion of short lactations had no appreciable

covariable to adjust for the effect of age of the cow influence on the estimates of crossbreeding

parame-at the time of weighing. ters. This was contrary to the results of Madalena

The second step involved regressing the breed (1988) who found that less genetic variation was

cross means on covariables for breed additive and expressed when short lactations were excluded and

non-additive effects in a weighted least-squares that heterosis and recombination loss were

under-(WLS) model using four genetic models to estimate estimated (Madalena et al., 1992; Madalena, 1994).

crossbreeding parameters. The reciprocals of the A two-step method was used to estimate

variances of means were used as weights. Table 1 crossbreeding parameters. In the first step, an

in-shows the crossbreeding effects that were fitted by dividual animal model that accounted for all additive

each genetic model. Additive breed effects represent genetic relationships between animals was used to

groupings according to the proportion of B, F and S estimate the breed cross means using the DFREML

genes in the animals. This implies that additive breed program (Meyer, 1991). Komender and Hoeschele

effects ( g ) were expressed as a deviation from the A (1989) reported a serious underestimation of stan- i

breed. The coefficients of heterosis (or dominance) dard errors of crossbreeding parameters when not

f m m f

and recombination were calculated as p p 1p p

accounting for all genetic relationships via an animal i j i j

f f m m f m

model. The animal model allowed for repeated and p pi j1p p , respectively, where pi j i and pi

records per cow by fitting an additional random denote the gene proportion of breed i in the sire and effect that represented the permanent environmental dam, respectively (Akbas et al., 1993). In this model, effect plus non-additive within breed effects in the the hypothesis X of Kinghorn (1980) which is based cow. This effect was assumed uncorrelated to the on the same nature of interaction as that underlying random additive breed effect for the animal. the Dickerson model, was assumed. The coefficient

Table 1

Crossbreeding effects estimated by different genetic models

a b b

Sources: Dickerson (1969, 1973), Kinghorn (1980). Grosshans et al. (1994) also used a model similar to Model D.

b

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Table 2

Coefficients of crossbreeding effects for different genetic groups

a b

Genetic group Parameters for additive and heterosis effects Parameters for epistasis effects

Dominance Dickerson Kinghorn Model D

gB gS gF hAB hAS hBS rAB rAS rBS eX aaAB aaAS aaBS

A3Ar 0.000 0.167 0.000 0.000 0.333 0.000 0.000 0.222 0.000 0.277 0.000 0.278 0.000

A3Sr 0.000 0.333 0.000 0.000 0.667 0.000 0.000 0.222 0.000 0.445 0.000 0.445 0.000

A3(B3Ar) 0.250 0.083 0.000 0.500 0.167 0.000 0.167 0.056 0.083 0.486 0.333 0.111 0.042 A3(B3Sr) 0.250 0.167 0.000 0.500 0.333 0.000 0.083 0.056 0.167 0.567 0.292 0.194 0.083 (A3Sr)3(B3Sr) 0.250 0.333 0.000 0.333 0.278 0.167 0.083 0.278 0.167 0.653 0.209 0.278 0.167 [Ar3(B3Sr)]3Ar 0.125 0.333 0.000 0.167 0.361 0.083 0.104 0.361 0.083 0.580 0.136 0.361 0.083

B3Ar 0.500 0.167 0.000 0.667 0.000 0.333 0.000 0.222 0.000 0.611 0.333 0.111 0.167

B3Sr 0.500 0.333 0.000 0.333 0.000 0.667 0.000 0.222 0.000 0.611 0.167 0.111 0.333

B3(B3Ar) 0.750 0.083 0.000 0.333 0.000 0.167 0.167 0.056 0.083 0.403 0.250 0.028 0.125 B3(B3Sr) 0.750 0.167 0.000 0.167 0.000 0.333 0.083 0.056 0.167 0.403 0.125 0.028 0.250 [B3(A3Sr)]3Sr 0.250 0.417 0.000 0.167 0.278 0.333 0.167 0.278 0.083 0.653 0.167 0.278 0.209 [B3(B3Sr)]3Ar 0.333 0.250 0.000 0.500 0.139 0.250 0.062 0.236 0.125 0.686 0.281 0.188 0.188 [B3(S3Ar)]3Sr 0.250 0.500 0.000 0.167 0.222 0.333 0.083 0.278 0.167 0.625 0.125 0.250 0.250 B3(Sr3Ar) 0.500 0.250 0.000 0.500 0.000 0.500 0.000 0.250 0.000 0.625 0.250 0.125 0.250

F3Ar 0.000 0.167 0.500 0.000 0.000 0.000 0.000 0.222 0.000 0.611 0.000 0.111 0.000

F3Sr 0.000 0.333 0.500 0.000 0.000 0.000 0.000 0.222 0.000 0.611 0.000 0.111 0.000

F3(B3Ar) 0.250 0.083 0.500 0.000 0.000 0.000 0.167 0.056 0.083 0.653 0.083 0.028 0.042 F3(B3Sr) 0.250 0.167 0.500 0.000 0.000 0.000 0.083 0.056 0.167 0.653 0.042 0.028 0.083

S3Ar 0.000 0.667 0.000 0.000 0.667 0.000 0.000 0.222 0.000 0.445 0.000 0.445 0.000

S3Sr 0.000 0.833 0.000 0.000 0.333 0.000 0.000 0.222 0.000 0.277 0.000 0.278 0.000

S3(B3Ar) 0.250 0.583 0.000 0.000 0.333 0.500 0.167 0.056 0.083 0.569 0.083 0.194 0.292 S3(B3Sr) 0.250 0.667 0.000 0.000 0.167 0.500 0.083 0.056 0.167 0.486 0.042 0.111 0.333 S3[A3(B3Ar)] 0.125 0.563 0.000 0.000 0.625 0.250 0.156 0.078 0.031 0.571 0.078 0.352 0.141 (S3Ar)3Ar 0.000 0.500 0.000 0.000 0.556 0.000 0.000 0.444 0.000 0.500 0.000 0.500 0.000 S3[B3(B3Sr)] 0.313 0.625 0.000 0.000 0.125 0.625 0.078 0.031 0.156 0.508 0.039 0.078 0.391

a

A, Ayrshire; B, Brown Swiss; F, Friesian; S, Sahiwal; Ar567A:33S; Sr567S:33A; r5stabilized two-breed rotation; breed of sire is shown before breed of dam.

b

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2

of epistatic loss was calculated as 12op where pi i the milk production traits and were 14 kg lighter is the proportion of breed i genes in the animal. The (P,0.05) in LW. Generally, there was a decrease in coefficients of additive3additive interaction effects performance with an increasing proportion of S between breeds i and j were calculated as the mean genes.

of the coefficient for heterosis (or dominance) and

recombination effects (Grosshans et al., 1994). Table 3.2. Crossbreeding parameter estimates 2 shows the coefficients of crossbreeding effects for

different genetic models. In the data set used, the The number of records available for the F crosses number of crosses with F genes was insufficient to was not large. However, this was the first attempt to allow estimation of dominance or heterosis, recombi- obtain crossbreeding parameters from data that in-nation and additive3additive interaction effects that cluded F crosses for this long-term programme. are due to A3F, B3F or F3S crossing. The Fitting of the genetic models to data that excluded goodness of fit of each of the four genetic models is the F crosses, to data generated before the F crosses

2

represented by an R value. The test of significant calved for the first time, to data generated onwards differences between the dominance model and the from the year the F crosses calved for the first time other models was done by considering the reduction and to the full data revealed that the changes to in error variance due to the recombination, epistatic within-model estimates were less than one standard or additive3additive interaction effects, using an F error. It was therefore decided to present estimates statistic, as in Robison et al. (1981). generated when utilising the full data. Tables 4 and 5 show the estimates of crossbreeding parameters, with standard errors, for milk production and reproductive

3. Results traits and LW. Table 6 shows estimates for MY and AMY expressed per unit of LW and per unit

meta-0.75

3.1. Fixed effects and genotype performance bolic weight (MW; expressed as LW ) for differ-ent genetic models. The coefficidiffer-ents of determination

2

Table 3 shows the genotype performance for all (R ) for the dominance and Kinghorn models were traits and the overall mean. Apart from the non- essentially identical but less than those for the significant effect of lactation number on CI, all other Dickerson model and Model D which were similar. fixed effects were significant (P,0.01) for all milk For the Dickerson model and Model D, the fit was production traits. For LW, the effect of genotype high for all traits accounting for 81% to 93% of the (P,0.1) and physiological status (P,0.001) were total variation among the breed cross means. For significant. As was expected, age had a significant most traits the Dickerson model and Model D fitted effect (P,0.01) on LW with the mean age being 4.5 significantly better (P,0.05) than the dominance years. The B3Ar cows can be compared with Sr model, and the dominance and Kinghorn models did cows because they are both from Ar dams; corre- not significantly differ, indicating that epistasis was spondingly, the B3Sr cows can be compared with of little or no importance.

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Table 3

Generalised least-squares means (LSM) and standard errors (S.E.s) of milk production and reproductive traits and cow live weight

a b

Genetic group Milk production traits

MY (kg) AMY (kg) CI (days) LL (days) DMY (kg) LW (kg)

n LSM S.E. LSM S.E. LSM S.E. LSM S.E. LSM S.E. n LSM S.E.

A3Ar 169 3274 62 2915 45 412 4 329 5 9.96 0.13 16 444 10

A3Sr 1680 3321 19 3021 14 403 1 325 1 10.32 0.04 24 417 8

A3(B3Ar) 567 3503 34 3079 24 414 2 339 2 10.42 0.07 51 431 5

A3(B3Sr) 347 3299 43 3032 31 398 3 318 3 10.40 0.09 75 429 4

(A3Sr)3(B3Sr) 41 3288 129 2986 91 400 9 324 10 10.38 0.27 14 432 12

[Ar3(B3Sr)]3Ar 270 3408 49 3092 35 398 3 327 3 10.45 0.10 24 419 8

B3Ar 1463 3651 21 3187 15 413 1 339 1 10.75 0.04 68 420 5

B3Sr 1253 3681 23 3286 16 406 1 334 1 11.08 0.04 63 434 5

B3(B3Ar) 285 3505 48 3141 34 408 3 334 3 10.62 0.10 24 416 8

B3(B3Sr) 825 3444 40 3120 29 399 2 329 3 10.56 0.08 162 434 3

[B3(A3Sr)]3Sr 106 3465 79 3075 57 401 5 332 6 10.47 0.16 24 433 8

[B3(B3Sr)]3Ar 405 3687 28 3252 20 411 2 339 2 10.94 0.06 112 432 3

[B3(S3Ar)]3Sr 133 3479 70 3223 50 399 5 323 5 10.87 0.15 35 443 7

B3(Sr3Ar) 328 3515 44 3128 32 406 3 329 3 10.76 0.09 66 425 5

F3Ar 13 3874 229 3399 162 422 16 349 18 11.33 0.48 10 435 13

F3Sr 45 3852 122 3587 87 395 8 326 9 11.86 0.26 56 442 5

F3(B3Ar) 68 4065 98 3567 71 412 7 354 7 11.55 0.20 88 439 4

F3(B3Sr) 20 3863 185 3693 131 376 13 334 15 12.37 0.40 30 428 7

S3Ar 1000 3049 26 2820 18 395 1 311 2 9.90 0.05 22 431 9

S3Sr 76 3037 95 2779 67 395 6 307 7 10.03 0.20 15 411 11

S3(B3Ar) 398 3242 41 2983 29 397 2 317 3 10.27 0.08 51 436 5

S3(B3Sr) 187 3178 60 2919 42 401 4 310 4 10.15 0.12 14 426 11

S3[A3(B3Ar)] 313 3061 46 2910 33 382 3 298 3 10.26 0.09 91 444 4

(S3Ar)3Ar 74 3297 95 3009 68 396 6 321 7 10.26 0.20 20 446 12

S3[B3(B3Sr)] 147 3132 67 2896 48 395 4 301 5 10.23 0.14 23 452 8

Overall 10 213 3446 3124 402 326 10.76 1178 435

SD 1112 833 64 72 2.57 70

a

See footnotes in Table 2 for description of genotypes.

b

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Estimates (Est.) and standard errors (S.E.s) of individual crossbreeding effects for milk production and reproductive traits and cow live weight using the dominance and the Dickerson models

b c

Model Effect Trait

Est. S.E. Est. S.E. Est. S.E. Est. S.E. Est. S.E. Est. S.E.

Dominance m 3544 167 3088 120 425 9 348 11 10.2 0.30 425 16

gB 115 200 130 143 210 11 24 14 0.50 0.35 12 18

R 0.884 0.873 0.689 0.797 0.874 0.368

Dickerson m 3493 172 2961 127 438 9 349 12 10.01 0.33 413 19

Z

R 0.932 0.921 0.814 0.866 0.914 0.477

a

The additive breed effects g are expressed as a deviation from the Ayrshire breed (m).

b

See footnotes in Table 2 for description of breeds.

c

See footnotes in Table 3 for description of traits.

d

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Table 5

a

Estimates (Est.) and standard errors (S.E.s) of individual crossbreeding effects for milk production and reproductive traits and cow live weight using Kinghorn model and Model D

b c

Model Effect Trait

Est. S.E. Est. S.E. Est. S.E. Est. S.E. Est. S.E. Est. S.E.

Kinghorn m 3565 205 3010 143 439 9 353 14 10.17 0.36 420 18

g_B 109 208 154 145 214 9 25 14 0.54 0.36 9 18

d

g_F 1139 556 884* 387 217 24 21 37 2.72** 0.96 20 36

g_S 2792*** 182 2562*** 126 223** 8 245** 12 21.10** 0.32 23 23

d_AB 45 246 2148 171 20 11 6 16 20.15 0.43 1 20

d_AS 37 291 54 203 24 13 29 20 0.37 0.50 11 23

d d

d_BS 459 242 284 168 18 11 10 16 0.93* 0.43 30 21

e_X 284 461 316 320 260** 20 218 31 20.51 0.80 34 33

2

R 0.885 0.880 0.794 0.800 0.877 0.405

Model D m 3493 170 2962 127 438 9 349 12 10.06 0.33 413 18

d

g_B 267 179 239 132 210 10 5 12 0.71 0.34 21 20

d

g_F 1033** 355 1209*** 261 245 19 21 25 3.27*** 0.67 33 23

g_S 2768*** 149 2554*** 109 225** 8 243** 11 21.09*** 0.28 23 24

d_AB 59 396 4 291 14 22 213 28 0.37 0.74 11 35

d

d_AS 2602 324 2311 237 220 17 250* 23 20.40 0.61 7 27

d_BS 393 355 107 260 24 19 23 25 0.37 0.67 23 28

aa_AB 2344 745 2103 547 256 41 21 53 20.78 1.40 30 68

d

aa_AS 1053 539 992* 395 232 29 50 38 1.97 1.01 212 46

d

aa_BS 2193 757 551 554 279 41 261 54 21.37 1.43 68 61

2

R 0.932 0.921 0.815 0.866 0.914 0.478

a

The additive breed effects ( g) are expressed as a deviation from the Ayrshire breed (m).

b

c

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Table 6

a

Estimates (Est.) and standard errors (S.E.s) of individual crossbreeding effects for MY and AMY expressed per unit of metabolic and live weight using different genetic models

b c c

Model Effect Per unit metabolic weight Per unit live weight

MY (kg) AMY (kg) MY (kg) AMY (kg)

Est. S.E. Est. S.E. Est. S.E. Est. S.E.

Dominance m 35.50 1.68 31.00 1.39 7.75 0.41 6.77 0.34

gB 2.64 2.80 3.28 2.31 0.70 0.68 0.82* 0.58

Dickerson m 34.85 1.91 30.19 1.65 7.64 0.48 6.62 0.42

d d

Kinghorn m 35.64 1.99 30.73 1.64 7.81 0.49 6.74 0.41

gB 2.62 2.87 3.30 2.37 0.69 0.71 0.83 0.59

Model D m 34.86 1.92 30.19 1.65 7.64 0.49 6.62 0.42

d d

The additive breed effects ( g) are expressed as a deviation from the Ayrshire breed (m).

b

c

d

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A3S. However the cross B3S showed a signifi- teraction effects (P,0.10) were also estimated by Model D but only in the B3S cross.

cant heterosis effect of 426 kg for MY. This was

For LL, the difference between the estimated 12.4% of the population mean. Heterosis (or

domi-breed effects of A and S were larger than those nance) effects in these crosses were also significant

between A and B or F. This indicates that the S in Dickerson and Kinghorn models but not in Model

breed additive effect resulted in a reduction in the D. The dominance effect in the cross A3S in Model

LL. None of the other effects were significant for D was significant and negative for MY. Negative

LL. The estimates of additive breed, heterosis or recombination and additive3additive interaction

dominance, recombination, additive3additive inter-effects for MY were estimated in the crosses A3B

action and epistasis effects for DMY followed a and B3S in the Dickerson model and Model D.

similar trend to those of MY. For LW, significant Those in the A3S cross were unexpectedly positive

breed difference between the F and A were estimated and significant for both the Dickerson model and

in the Dickerson model (31 kg) and Model D (33 kg) Model D. Fitting of reduced models that excluded

models. The F was between 33 and 38 kg heavier one or other of the covariables for heterosis (or

than the S. While none of the heterosis or dominance dominance) in all the crosses and of the covariables

effects for LW were significant, they were positive for recombination and additive3additive

interac-for all the crosses in all the genetic models. Apart tions effects in the A3B and B3S crosses did not

from the recombination and additive3additive inter-result in changes in the estimates of recombination

action effects in the cross A3S in the Dickerson and additive3additive interaction effects in the A3

model and Model D which were negative, all others S cross compared to the full Dickerson model and

were positive for LW. Model D. This indicated that heterosis (or

domi-For MY and AMY expressed per unit of LW and nance) effects in all crosses and recombination and

MW (Table 6), F showed significantly positive additive3additive interaction effects in the A3B

additive breed effects for both AMY (ranging from and B3S crosses were not confounded with the

11.35 kg in the Kinghorn model to 12.96 kg in recombination and additive3additive interaction

Model D) and MY (ranging from 12.45 kg in the effects in the A3S cross. The estimates of epistasis

Dickerson model to 13.36 in the Kinghorn model) effect from the Kinghorn model was 284 kg for

expressed per unit MW. S had the smallest estimated MY.

additive breed effect for these traits. Significant For AMY, the estimates of additive breed effects

heterosis was only found in the B3S cross for both ranged from 884 kg (for Model D) to 1210 kg (for

these traits in the dominance and Dickerson models. the Dickerson model) for F and 2551 kg (for the

In both the Dickerson model and Model D, recombi-dominance model) to 2562 kg (for Model D) for S.

nation and additive3additive interaction effects in As for MY, the heterosis or dominance effects

the crosses A3B and B3S were negative. How-estimated by the dominance, Dickerson and

Kin-ever, no significant negative epistatic effects were ghorn models were significant in the cross B3S but

estimated in the Kinghorn model. For MY and AMY not in the crosses A3B and A3S. Positive but

expressed per unit of LW, the direction of the non-significant epistatic effects were estimated by

estimates of additive breed effects was similar to that the Kinghorn model. The estimated additive breed

for MY and AMY expressed per unit MW. The effects for CI were, with the exception of the

heterosis or dominance effects in the various crosses dominance model, very similar and the maximum

were all positive and not significant for all genetic value was 245 days for F and 225 days for S.

models. Heterosis effects using the Dickerson model were all

favourable and significant (P,0.10) in all the crosses. These values ranged from 213 days in the

A3B cross to 236 days in the B3S cross. The 4. Discussion

epistatic effect for CI from the Kinghorn model was

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lowland tropics of Kenya were used. These data four had genes from all three B. taurus breeds (Table provided information on the relative lactational, 3).

reproductive and LW performance of various crosses

of A, B, F and S cattle. These breeds have been used 4.1. Additive breed effects widely in crossbred dairy herds in the tropics

(Cun-ningham and Syrstad, 1987). MY and AMY were The estimated breed differences for MY for F over also estimated per unit of LW and per unit of MW. B (765 to 1030) and A (1033 to 1139) are higher Such estimates are scarce in the literature, but than those estimated elsewhere. For example, in an important because they indicate the level of bio- American study, the F contributed 759 and 857 kg logical efficiency of a cow. Consistent with the more first lactation MY than the B and A, respective-literature, this study shows that additive genetic, ly (Robison et al., 1981). As was expected, the breed heterotic or dominance, recombination and difference between the mean of the B. taurus breeds additive3additive interaction effects are important and S breeds for the MY was large. The estimated effects to be considered in the design of efficient difference in MY (1801 to 1914 kg) between the F breeding systems for tropical dairy production sys- and S is more than double the estimate of 773 kg tems based on B. taurus and B. indicus breeds. difference between F and S reported by Sharma and The mean MY of 3446 kg (SD 1112) for the total Pirchner (1991) utilising data obtained from a num-herd (Table 3) was higher than that reported by ber of dairy farms in India. Under a semi-arid and Mackinnon et al. (1996) from a subset of these data. low inputs environment, Thorpe et al. (1993) re-This could be attributed to the introduction of the F ported that MY of S was 746 kg less than that of B. breed in the herd because from the time of the taurus (A and F). This resulted from a 2.2 kg greater

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con-A.K. Kahi et al. / Livestock Production Science 63 (2000) 39 –54 51

firms that the use of F sires for crossbreeding would heterosis and dominance effects were estimated in result in heavier LW in its crossbreds and hence an the cross B3S but not in the other crosses. The increase in food costs. This demonstrates the impor- estimates of these effects were higher than reported tance of including LW as a selection criterion among by Sharma and Pirchner (1991) and Thorpe et al. breeds of B. taurus for crossbreeding in tropical (1993) in the crosses F3S (333 kg) and B. taurus dairy production systems, especially for smallholder (A and F)3S (73 kg), respectively. The lack of a production where feed resources may be scarce and significant heterosis effect in the cross A3B was their availability variable (Walshe et al., 1991). expected and is in line with the theory which predicts Given the high levels of management in this herd that the wider the genetic distance or greater the and the fact that in most of the tropics milk volume phenotypic difference between parental breeds, the has a higher monetary value than milk fat or milk greater the heterosis expressed. The significant effect protein yield, the use of the F breed is justified of heterosis for CI (in the Dickerson model) reported because it was superior to the other B. taurus breeds in the present study is smaller than that reported by for MY and AMY expressed per unit of LW and per Thorpe et al. (1993) for B. taurus (A and F)3S unit of MW (Table 6). However, when feed re- cross. In that study, F cows had CI that were 821

sources are scarce, it would be expected that larger days shorter than the mean of the B. taurus (A and breeds would be less able to meet their feed intake F) and S pure-breds. The heterosis (in the Dickerson capacity than smaller breeds and may then become model) estimated in the present study ranged from less efficient. An important question is whether 213 days in the A3B cross to 236 days in the superior biological efficiency translates to superior B3S cross. Cunningham (1981) suggested that economic efficiency, a question that is difficult to when there is a substantial difference between the F1

answer because of the problems of measuring the and the local strain, production in a poor environ-inputs of a pasture-based production system – in ment is influenced heavily by heterosis and pro-particular feed intake. Feed intake is an important duction in a good environment is largely determined expense trait in explaining variation among breeds in by breed additive effects and small heterotic effects. measures of economic efficiency (Balaine et al., The differences in the magnitude of the heterosis 1981). There is the need therefore to establish the estimated in the present study where nutritional nutrient requirements and the utilisation efficiencies levels were good, and in that reported by Thorpe et of breeds of varying body size so that breeding al. (1993) where there was sub-optimal nutrition, systems can be matched with different production supports this suggestion. Therefore, utilisation of systems in order to optimise production efficiency. heterosis may provide a useful tool to increase This is important especially in tropical dairy pro- reproductive performance in dairy cattle in nutrition-duction systems where the choice of B. taurus and B. ally restricted production systems, which are

wide-indicus breeds to be used in crossbreeding should spread in the smallholder sector in the tropics. While match the levels of inputs (Madalena et al., 1990) estimates of heterosis for CI were significant in all which vary markedly both within and among tropical crosses in the Dickerson model, those estimated in countries. For the F breed, extreme caution must be the Kinghorn model were not. This could be due to taken because of the difference in mature sizes of the difference between the definition of heterosis in various strains. The F strain used in the present study the Dickerson model and dominance in the Kinghorn was the European one which, in the 1980s was model. Heterosis effects estimated by the Dickerson smaller (6%) than the Holstein types from the USA, model includes some epistatic effects whereas the Canada and Israel (Jasiorowski et al., 1987; Stolz- dominance effects estimated by the Kinghorn model man et al., 1988). exclude the epistatic effects.

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al., 1993; Morris et al., 1986, 1987, 1994) and for the heterosis effect estimated by his model is equiva-dairy cattle (Lopez-Villalobos et al., 1998). This lent to half of the additive3additive effect plus the indicates that crossbreeding of these breeds would dominance effect. The lack of a significant difference result in an increase in the LW of the crossbred between the dominance and Kinghorn models indi-population and hence an increase in food costs. This cates that inclusion of epistasis considering specific would have a direct influence on the productivity and breed effects did not improve the accuracy of profitability of the cow. The positive estimate of estimated crossbreeding parameters. However, ac-heterosis or dominance on MY measured per unit of curacy was improved when either the specific recom-MW in all the crosses could be due to good nutrition bination effects (Dickerson model) or specific in the herd which allowed larger breeds to meet their additive3additive interaction effects (Model D) feed intake capacity. In such situations, crossbreed- were included.

ing of large mature size high yielding B. taurus to low yielding B. indicus results in an improvement in

cow productivity per unit MW. This could change in 5. Conclusions

situations where feed is scarce and it’s availability

variable, e.g., in the smallholder dairy sector in the Our study justifies the use of F sires for tropics. Therefore, the choice of B. taurus breeds for crossbreeding to improve biological efficiency in crossbreeding in tropical dairy production systems systems where management levels can support a becomes important. production level of above 3000 kg of milk per The negative estimates of recombination and lactation and where payment is based on volume of additive3additive interaction effects for MY from liquid milk. Additive breed, dominance or heterotic, the Dickerson model and Model D in the crosses recombination or additive3additive interaction ef-A3B were expected. The A and B have been fects are major genetic effects worth, considering in selected for generations with the main aim of a crossbreeding scheme. Although all the genetic increasing MY per cow. Therefore, favourable epi- models showed a similar pattern, the absolute values static interactions between genes on different loci of the parameters varied. The use of the Kinghorn within gametes may have been evolved. By crossing model did not result in an improvement in the A and B, these interactions are lost due to recombi- accuracy of estimated crossbreeding parameters over nation. Similar negative estimates have been reported those estimated by the dominance model. The

simi-2

in the literature from crosses involving B. taurus larity in R values in the Dickerson and D models breeds (McAllister, 1986; Ericson, 1987; Van der means that the proportionate reduction of total Werf, 1990). The epistasis effects from the Kinghorn variation in each trait would be quite similar for the model were negative for MY, CI, DMY and MY two models. It is concluded that, the Dickerson or D expressed per unit of MW and LW. However, with models are most suitable for analysing these this model it is impossible to distinguish between crossbred generations.

different breed combinations when three and more breeds are considered. This is because the epistatic

effects are described by only one parameter (e ).X Acknowledgements

When the recombination and additive3additive

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Ayrshire, Brown Swiss and Sahiwal cattle in the lowland

when the first author was on leave from Egerton

tropics of Kenya. Livest. Prod. Sci. 44, 139–146.

University (Njoro, Kenya).

Kahi, A.K., Nitter, G., Thorpe, W., Gall, C.F., 2000. Crossbreeding for dairy production in the lowland tropics of Kenya. II. Prediction of performance of alternative crossbreeding strate-gies. Livest. Prod. Sci. 63, 55–63.

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