The Use of Field Records in Pig Progeny Testing: 1. Optimum Size of Sire Progeny Groups

The Use of Field Records in Pig Progeny Testing: 1. Optimum Size of Sire Progeny GroupsAuthor(s): Patricia McGloughlinSource: Irish Journal of Agricultural Research, Vol. 16, No. 1 (Apr., 1977), pp. 65-72Published by: TEAGASC-Agriculture and Food Development AuthorityStable URL: http://www.jstor.org/stable/25555853 .

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Ir. J. agric. Res. U: 65-72, 1977

THE USE OF FIELD RECORDS IN PIG PROGENY TESTING

1. Optimum size of sire progeny groups

Patricia McGloughlin An Foras TaUntais, Dunsinea Research Centre, Castleknock, Co. Dublin

ABSTRACT

Three empirical methods were used to determine the number of progeny required for accurately progeny testing a boar under field conditions, based on records from a large commercial pig fatten ing unit.

i) Using 2,800 progeny records of 14 boars the predictive value of average performance based on n progeny {?

= 20,40,.., 180) was assessed by correlation with the average of 200 progeny

(including the n progeny), which was considered to be a close estimate of true breeding value. ii) Using 3,304 progeny records of the same 14 boars, the predictive value of performance

based on 20, 40 and 60 progeny was determined by correlation with the true breeding value based on 176 independent progeny, and the correlations were compared with their expected values,

iii) The added accuracy to be gained by increasing the number of progeny per sire was obtained

by plotting the variance of 58 individual sire effects against the number of progeny per sire. The results of all three methods agreed closely and indicated that at least 40 progeny should be

included in the sire group and that little further accuracy is achieved by increasing the numbers of

progeny per sire beyond 60.

INTRODUCTION

Progeny testing in centralised units has been the basis of pig improvement programmes in many countries since it was first introduced in Denmark at the beginning of this

century* Testing facilities are usually limited by their cost and any alternative source

of widespread and cheap testing facilities is worthy of investigation. Evaluation of

sires on the basis of their field progeny records is an established method in dairy cattle

improvement. The possibility of applying a similar technique to pig testing has re

ceived. little attention, apart from the study of Varo (1), who has used field data to

evaluate A.I. boars in Finland. One reason for this situation is that boars, unlike

dairy sires which are used in A.L and have progeny in many different herds, are gen

erally used exclusively in one herd; it is therefore not possible to make unbiassed

comparisons between boars. On the other hand, field performance testing of both

boars and gilts is quite widespread (2). A recent trend in pig production in Ireland presents an opportunity for progeny

testing boars under field conditions, A number of large co-operatively owned fattening

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66 IRISH IOURNAL OF AGRICULTURAL RESEARCH, VOL. 16, NO. 1, 1977

units have been established throughout the country. Commercial breeders sell their weaner pigs to the unit at 30 to 35 kg. All pigs are then fattened together to slaughter at around 85 kg liveweight. Thus, in theory, these units simulate a progeny testing

station, where the progeny of many boars are reared in the common environment of

the unit. The object of this study was to investigate the feasibility of using these com mercial fattening units for progeny testing boars. This paper investigates the number

of progeny to be included in a sire group, while in a further paper (3) the genetic and

phenotypic parameters of this population are reported.

Under most conventional systems the boar progeny test is based on 12 to 16 pigs (4). These are usually pre-selected to some extent on the basis of weight to give three

or four pigs of uniform weight and desired sex balance, from at least three different litters. In the commercial conditions of the co-operative pig units in this study, whole

litters are submitted to the feeding unit, and the total number of progeny per boar

varies widely. If the test were to be based on the first 12 or 16 available pigs it could be strongly biassed as these pigs might come from only two litters. It was necessary

therefore to determine the minimum number of pigs required to ensure a represen

tative sample of progeny on which to estimate breeding value with reasonable

accuracy.

EXPERIMENTAL

Field records were available from one co-operative pig unit, at Rathduff, Co. Cork.

Information on each pig included parentage, litter details, weights at entry to the unit

and at slaughter, and some carcass data. The 7,953 pigs were the progeny of 58

purebred boars (43 Irish Landrace and 15 Irish Large White) which were born in 178

supplier herds. The average herd size was less than five sows, and all boars sired litters

in at least two herds. The average number of herds per sire was 7.3.

Weaner pigs were delivered to the unit at an average of 35 kg. They were re

grouped according to weight and penned in lots of 20 until slaughtered at an average of 65 kg carcass weight. A balanced barley/soyabean or fishmeal ration was fed in a restricted regime, in conjunction with liquid whey (up to 11 1/pig/day) when available from March to November. When whey was not available water was substituted; meal

was fed dry twice daily, and then the troughs were filled with whey or water. The traits studied were carcass-weight-for-age (carcass weight divided by age at

slaughter, kg/day), station gain (liveweight gain in the fattening station, kg/day), shoulder fat (maximum depth of the subcutaneous fat layer, including skin thickness, in the region of the shoulder, mm) and carcass length (anterior edge of the first rib to the anterior edge of the aitch bone, mm). The relationship between number of

progeny per sire and the accuracy of evaluation was studied using three empirical methods:

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McGLOUGHLIN: PIG PROGENY TESTING, 1 67

Method 1

The data for 14 (9 Landrace, 5 Large White) boars which had at least 200 recorded progeny were sorted in chronological order according to the date of slaughter, and divided into groups of 20 pigs. The predicted value of average performance based on n progeny (n=20, 40,., 180) was assessed by the correlation (r) with the average of 200 progeny, which was considered to be a close estimate of true breeding value.

As each of these subgroups contained a portion of the records included in the 200 progeny used to estimate true breeding value, an automatic part-whole correlation was included in the calculated values of r. Ideally the estimate of the true breeding value should have been based on an independent large sample of records. However, there were not sufficient boars with at least 400 recorded progeny to permit this type of analysis. The expected value of the part-whole correlation (/ ') between the average of 200 records and the subgroup of n of this 200, assuming there was no covariance

present other than the automatic part-whole relationship, was estimated using the formula r' =

kayn/aj. where oJ is the standard deviation of the estimated true breeding value (i.e., mean

of 200 progeny) Gya is the standard deviation of subgroups based on n progeny (w=20, 40,

.> 180) k is the proportion of the total of 200 progeny records which are used in

this subgroup (k=.l, .2,.5 .9) The derivation of this formula is given in Appendix 1.

Method 2

The 14 boars used in this study each had in fact at least 236 recorded progeny. If true breeding value were based on the 61st to 236th progeny, i.e., 176 progeny, this

would allow the formation of independent groups of up to 60 progeny. The predicted value of performance based on 20, 40, 60 progeny was determined by correlation with

the true breeding value based on 176 independent progeny. The expected value of the

correlation, between two subgroups of progeny can be computed using the formula

of Henderson (5):

where oa2 is the sire variance,

ore2 is the error variance

and n and p are the numbers of pigs in the progeny groups. Sire and error variances

for this population were estimated in part 2 of this study (3), where they were based

on 58 sires with a total of 7,953 progeny, which included the data in the present study. The above formula ignores the number of dams per sire. However, the sire variance

used here contained the dam variance component, since it was based on a mixture of

full- and half-sibs (averaging 80 pigs per sire and 5 pigs per litter).

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68 IRISH JOURNAL OF AGRICULTURAL RESEARCH, VOL. 16, NO. 1, 1977

Method 3 The breeding values of individual sires were estimated using the least squares

method for the 58 boars in part 2 of this study (3). The number of progeny per sire

varied from 22 to over 600. A further assessment of the added accuracy to be gained

by increasing the number of progeny per sire was obtained by plotting the variance

of the individual sire effects against the number of progeny per sire. The variance of

the ith sire effect is St = CH.oej23 where o-ej2 is the overall error variance for the jth

trait and Cfl is the inverse of the appropriate element of the least squares coefficient

matrix. Since ae2 is common to all variances, the Cu elements were used to plot their

relative values.

RESULTS

Method 1 The correlation (r) between true breeding value (average of 200 progeny) and the

average of subgroups of n progeny for the four traits is plotted in Fig. L Also included are the estimates of the automatic correlation (/*') due to the part-whole relationship of the two variables. The results indicate that calculations based on between 40 and 50

progeny per boar would give a correlation of more than 0*75 for growth traits, while even fewer progeny would give this degree of accuracy in the case of shoulder fat or carcass length.

Method 2 Table 1 shows the observed and expected correlations between estimates of breed

ing value on the first n progeny and that based on 176 later progeny* The observed and expected correlations agree well with each other and with the earlier results for

progeny groups of 20, 40 and 60 pigs, and confirm the earlier conclusions.

Methods

Fig. 2 shows the relationship between variance of the individual sire effects and number of progeny. Little further increase in accuracy is achieved after 50 to 60 pigs are included in the sire group.

DISCUSSION

The results indicate that at least 40 progeny should be included in'the sire groups. Although this appears to be a large number of pigs when compared'to the conven tional test numbers of 12 to 16, it only amounts to about S litters, as the average number of fully recorded pigs per litter was 5 in these data.

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McGLOUGHLIN: PIG PROGENY TESTING, 1 69

CARCASS-WEIGHT-FQR-AGE STATION GAIN

.6' j ^.o*'* t &

| .*- / / 4 /

1 / _ o-'

2 SHOULDER FAT CARCASS LENGTH s

,- / ,<? ?*

' ^lo

' s6

' i'2o' 160'

' 46

' so

l jl2o' len

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NUMBER OF PROGENY .11)

_Fzg*. 7; Relationship between the number of progeny (n) and the value of the correlation

coefficient between ''true breeding value' and the average of n progeny (r); ?

r; o?o rl (the expected value of the automatic part-whole correlation)

TABLE 1: Observed and expected correlations between estimates of breeding value based on the first n progeny (?=20, 40, 60) and that based on 176 later

progeny * data on 14 boars

Carcass-weight Station Shoulder Carcass -for-age gain fat length

Progeny Obs. Exp. Obs. Exp. Obs. Exp. Obs. Exp.

First 20 0.38 0.58 0.27 0.54 0.74 0.66 0.56 0.58 First40 0.62 0.70 0.51 0.66 0.67 0.76 0.71 0.70 First 60 0.91 0.75 0.80 0.71 0.64 0.81 0.62 0.73

In a study on the field progeny testing of A.I. boars in Finland (1), the number of

progeny per boar averaged 63 pigs, representing 10.2 litters. These pigs were all fattened on the individual farms where they were born, and not in a central unit as in the present situation? which would tend to increase the environmental Variation. Thu?

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70 IRISH JOURNAL OF AGRICULTURAL RESEARCH, VOL. 16, NO. 1, 1977

greater numbers of progeny per sire would be required for accurate testing. Varo (1)

suggested that reliability of the progeny test could be increased by reducing the

number of pigs from the same litter without reducing the total number of offspring in the sire progeny group.

Lush (6) and King (7) have demonstrated that the accuracy of the progeny test is

increased as the number of progeny in the test is increased, either by including more

pigs per litter group or more litter groups. On the other hand, where testing capacity is fixed, the total number of boars that can be tested, and therefore the potential

selection intensity, is inversely related to the number of progeny per boar. As genetic

progress depends on both these factors, normally they must be carefully balanced for

optimum results. However, under field conditions such as in the situation under

consideration here, potential testing facilities are not limited to the same extent so that

the balance between number of boars tested, number of litters per sire and number

of pigs per litter is not important.

Skjervold and Langholz (8) showed that for A.I. cattle breeding, optimum size of

the progeny test group increases with increasing testing capacity, decreasing herita

bility, and increasing selection intensity.

- - -

?|

,14

.12.'

i-A w |

" i

5*-|.

.04- ^

"*^?# *' * *. mi ) "** *?-.?__^__ m f #

i_-r-,-1 -' , V -1-

, *?^?- ?^-1-_-;-J

50 iOQ 150 200 2SQ 300 ?5GO NUMBER OF PROGENY IN TEST GROUP W

Fig. 2: Relationship between variance of the individual sire effects and number of progeny in the test group (?)/ the line representing Ijn wmdd be a function, of sire.

variance had the data been completely balanced':(see texf) ; . . \, '

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McGLOUGHLIN: PIG PROGENY TESTING, 1 71

The observed correlations for shoulder fat and carcass length are initially high and in fact decrease in magnitude with increases in progeny group size up to 40 and 80 respectively for shoulder fat and carcass length (Fig. 1 and Table 1). This situation

might be accounted for by the small sample size of only 14 boars, or by the fact that the records used in this part of the study were not corrected for non-genetic sources

of variation. In the second part of the study (3), sex, breed of dam, year/season and herd were all shown to have significant effects on these traits.

The correlations between true breeding value based on 200 progeny and subgroups

containing a proportion of this same 200 progeny are slightly higher than those

correlations between estimates based on independent samples. However, both are in

reasonably close agreement with the expected correlations, calculated on Hender

son's (5) formula, especially in the case of subgroups of 40 and 60 progeny. The con

clusions to be drawn from each set of results would be similar, that is, that at least 40 progeny should be included in the sire group.

The relationship between sire variance and the number of progeny in the test

group (Fig. 2) shows that little further increase in accuracy is achieved after numbers of 50 to 60 progeny have been reached. This finding therefore verifies the conclusion

drawn from the results of the other methods. If the data used in the variance analysis which produced these estimates of sire effects (3) were completely balanced, that is, if all the cells in the cross-classification, which included sire, sex, breed of dam, year/ season and herd, were filled symmetrically, sire variance would be a function of 1/n

where n is the number of progeny per sire. A line representing l/n for increasing values of n is shown in Fig. 2. Comparison of the variance of the individual sire effects with this line affords a test of the goodness of fit of the statistical model employed. The

results indicate that the model fitted the data very well. The two outliers (sires 34

and 37) were those where the effect of boar and farm were almost statistically con

founded, and therefore estimates of sire effect were subject to considerable bias. In

the case of sire 34, all but two of his 57 progeny were born on a farm where no other

pigs were recorded. In the case of sire 37 all but 8 of his 134 progeny were born on a

farm where no other pigs were recorded.

In conclusion all three empirical methods indicate that at least 40 progeny per sire

group are required for field testing of boars and that little further accuracy is achieved

by increasing the number of progeny beyond 60. The application of field progeny

testing will be discussed in the second part of this study (3).

ACKNOWLEDGMENTS

The author wishes to thank the management of Rathduff Pig Co-Operative Society for providing the data on which this study was based. The helpful comments of the

referee are also gratefully acknowledged

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72 IRISH JOURNAL OF AGRICULTURAL RESEARCH, VOL. 16, NO. 1, 1977

REFERENCES

1. Varo, M., /. Scient. Agric. Soc, Finland 40; 109, 1968. 2. King, J. W. B? Anim. Breed. Abstr. 38: 523, 1970, 3. McGloughlin, Patricia, Ir. J. agric. Res. 16: 73, 1977.

4. Clausen, H. and Gerwig, G, FAO Agricultural Series No. 44, FAO? Rome, 1958. 5. Henderson, C. R., Animal Husbandry 120, Cornell University, 1959. 6. Lush, J. L., Iowa Agric. Exp. Sta. Res. Bull. 204t 1936. 7. King, J. W. B., Anim. Breed. Abstr. 23: 347, 1955. 8. Skjervold, H. and Langholz, H. J? Z. Tierzucht. ZuchtBioL 80: 25, 1964.

Received June 25, 1976

APPENDIX 1

Derivation of formula for the estimation of the automatic part-whole correlation (r1)

Let proof on all (p) pigs | x /p m

Let proof on subgroup (n) pigs n

Let proof on remainder (p-n) pigs p

i*n+1 T

Let n/p = k (the proportion of pigs in the subgroup)

It is assumed that for the automatic correlation Cov (y, i) * 8

P n p ? X, a ? X. + I X,

divided through by p, one gets:

x = ky +

(l-k)i

Cov(x,y) =

Cov{y, ky + (l-k)i)

"_L. ..__.

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