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Genetic correlations between the performance of purebred and crossbred pigs Sansak Nakavisut Dr.Ron Crump Matias Suarez Dr.Hans Graser.

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Presentation on theme: "Genetic correlations between the performance of purebred and crossbred pigs Sansak Nakavisut Dr.Ron Crump Matias Suarez Dr.Hans Graser."— Presentation transcript:

1 Genetic correlations between the performance of purebred and crossbred pigs Sansak Nakavisut Dr.Ron Crump Matias Suarez Dr.Hans Graser

2 Introduction Nucleus herds test & select purebreds But the end products are crossbreds (multipliers and commercial herds) This assumes r g between purebreds and crossbreds of “1” If not “1”, testing and genetic evaluation procedure may need some changes

3 In general Estimation of r g between purebreds and crossbreds NOT possible or NOT reliable Performance test records on crossbreds not available Crossbred records may be available BUT from different environments (nucleus VS multiplier herds)

4 Thai government pig breeding farms Crossbreds were performance tested Purebreds and crossbreds were produced in the same conditions (environments, herds, management, feeding..) Litter records available from both crossbred and purebred sows Allows reliable estimation of r g between pure- and crossbreds

5 Objectives To estimate genetic correlations (r g ) between the performance of purebreds and crossbreds To validate the conventional genetic evaluation procedure (whether r g = 1)

6 Breeding diagram DULRLW LRxLW LWxLR DUx(LRxLW) DUx(LWxLR) GGP GP PS

7 Performance test records by breeds BreedNo. records DU1431 LW27127666 (84%)purebreds LR3523 LRXLW464 962 (11%) 2-way LWXLR498 DUX(LRLW)197 447 ( 5%) 3-way DUX(LWLR)250 Total 9075

8 Litter records by breeds Breed of sows Litter records No. of sows DU1133422 LW4573 10558 (89%)1376 LR48521601 LRXLW534 1265 (11%) 238 LWXLR731271 Total 118233908

9 Traits to be analysed PRODUCTION 1.TDG 2.ADG 3.FCR 4.BF 5.Body Length REPRODUCTION 1.NPB 2.NBA 3.LS3W 4.LWB 5.LW3W 6.GEST

10 Statistical model for test records assumption

11 Statistical model for litter records assumption

12 Fixed effect model for test records BreedSextHYSAgeInFiWt TDG  ADG  FCR  BF  BL 

13 Fixed effect model for litter records Br i breed fHYS j farrowing herd-year-season AgeC k age class of the farrowing sow Par l parity of litter LitBr m (Br i ) nested litter-breed within breed of sow The same fixed effects were fitted for all litter traits

14 Results : r g (pure&cross)

15 Discussion (production traits) r g (pure&cross) high enough => testing and selecting of purebreds in the nucleus can genetically improve the production traits of crossbreds in multiplier and commercial herds To reduce cost of unnecessary test of crossbreds Conventional testing of purebreds is validated

16 Discussion (reproduction traits) r g (pure&cross) NOT “1” (although positive) => selecting on purebred litter records can genetically improve the reproduction of crossbred sows BUT not as efficient as incorporating crossbred records in the genetic evaluation procedure. Crossbred records readily available in most multipliers with no extra cost => combine them with purebred records to produce EBVs for litter traits

17 Conclusion Genetic correlations between pure- and crossbreds for production traits are high Therefore, conventional testing and selecting of purebreds is validated by this study

18 Conclusion Genetic correlations between pure- and crossbreds for reproduction traits are low to moderate Therefore, we must include crossbred information into the genetic evaluation procedure to improve reproduction traits of crossbred sows

19 Thanks Dept. Livestock Development (DLD) Thailand UNERS / IPRS AGBU UNE

20 Genetic links b/w c ross & p urebreds 51 common grandparents (21 grandsires & 30 grandams) 544 Purebred litters (5%) (Total = 10558) 481 Crossbred litters (38%) (Total = 1265) Litter records

21 Methods and Models Treat pure- and crossbred records as different traits eg. ADGp and ADGc Bivariate analysis of the two separate traits using ASReml; animal model Estimate additive genetic covariances and genetic correlations between the two traits

22 Material and methods DU, LW, LR & their crosses 11-year (1993-2003) 9075 performance test records 11823 litter records (from 3908 sows)

23 Number of breeds per contemporary group (HYS) Test recordsLitter records Breeds/CG (tHYS) Breeds/CG (fHYS) Frequency (%)

24 Genetic links b/w c ross & p urebreds 80 common parents (39 sires & 41 dams) 415 Purebred records (5%) (Total = 7666) 429 Crossbred records (30%) (Total = 1409) Performance test records


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