565 Dairy progeny testing in Finland') Ulf Lindström2 ) and Kalle Maijala Agricultural Research Centre, Institute of Animal Breeding, Tikkurila Mikko Varo University of Helsinki, Department of Animal Breeding, Viikki Received March 9, 1973 Abstract. An account is given of the present method of progeny testing of dairy bulls. Correction factors used are presented and an example of their application given. It is noted that progeny tests for milk yield based on less than 30 daughters have a low repeatability. There were no significant changes in the ranking order of AI bulls in different geographical areas. In the Ostrobothnia area, however, the progeny tests seemed to be slightly less accurate than in other regions. Our present method of progeny testing of bulls for dairy characters is based on a method developed by prof. Mikko Varo. Progeny testing of bulls in Finland was done according to this method already in 1950. A description of the principles is given by Varo (1958) and Lindström (1969). In the course of time the method has been modified at the Department of Animal Breeding in collaboration with the AI and breeding organisations. Nowadays the progeny tests are computed at the Central Association of AI Societies. Previously (up to 1963) the Department of Animal Breeding of the Agric. Research Centre did the calculations. Material All figures used in the calculations stem from the reports given by the milk recorders. Previously the material needed for the progeny tests was collected once a year, at the termination of the recording year. Today the monthly reports sent by the recorders to the data processing department are automatically stored on magnetic tapes or discs. This makes it possible to *) Paper presented by dr. Lindström at the 2nd World Ayrshire Conference, Lahti August 3, 1972. 2) At present at the Department of Animal Production, University of Nairobi, Kenya https://www.c-info.fi/en/info/?token=14rmOTjnAZqeyytm.YX_rqDNV4lqWZ5iKNMt6Dg.-Pb2z0WAEgmoE-CQnDongTRCDcJBvU9nB1rH79b-69pjX647rRSsLoJjumZjLCxApIwnNxbxt9AOls03sk1sSAUr4dsSo8wRR1j49hiuTRZgs5CsBAOSpqqUgj9LU40tPba4AbW_vwv3r3IvHe3DjRBSd9MscCue0H7y--pHirClN-cPStuS7YtNhQNRB_uLvPA2hd9YXeHZ_gw 566 calculate the progeny tests more often, even once a month if desired. So far the progeny tests have been based on the results of the recording year. Recently, however, a method has been adopted whereby the production of the daughters is also given as a 12 month rolling average. This enables us to use all records and to speed up the computations. Only the results for daughters milking their first, second or third record- ing year are included. A minimum of 10 daughters per sire is required before a progeny test is calculated. Corrections In order to account for the environmental influences within herds, each daughter’s milk and fat production result is compared with the correspond- ing herd average. The daughter’s own result is included in the herd average. This is a safety measure as our recorded herds, on an average, consist of only 7 cows. The daughter’s result in per cents of the herd average is called her relative production. When more than one breed is represented in a herd, separate averages for the breeds in question are computed. (Mi- nimum 2 cows required.) These are used when calculating the relative production. The fat % is calculated as a deviation from the herd average (including the daughter). To account for differences in ag e and month of calving of the daughters corrections are made. From Table 1 it appears that especially the time of calving affects the milk production results to a high degree. The fat percentage, on the other hand, is but slightly affected by these systematic influences. Calculation of progeny test Each year (or each time the progeny test is calculated) correction factors for the effects of age and calving month are computed by least squares procedures (see Table 1). The correction factors used when calculating the Table 1. Influence of age and calving month on the 3 first production years of Ayrshire cows (recording year 1967/68, least squares analysis 1). Number Percentage of total variation Production year of records Relative milk prod. Fat % deviat. age calv. month age calv. month First 29523 1.669.49 0.440.81 Second 22452 0.473.10 0.070.44 Third 19779 0.18 3.13 0.00 ns s) 0.66 ') Least squares analysis means that the influences of age and calving month have simult- aneously been considered (Harvey 1966). In other words, the age influence is free from the effect of calving month and vice versa. (Statistically speaking we obtain unbiased estimates of these influences.) 2 ) ns = not statistically significant; all other figures highly significant. progeny test in May 1972 are given in Tab 1 e 2. The procedure in calculat- ing the progeny test is perhaps most easily explained by an example. Let us assume that an individual daughter of a certain bull is born in June 1968, that she is milking her first year, that she has calved in July and that her relative production is 91.7. From Table 2 we note that the average relative production for a cow of this age is 90. 5. Further we note that cows milk- ing their first year and calving in July are 5. 8 relative units below the overall average. The result for this daughter is thus as follows: 91.7 (90.5 5.8), i.e. 91.7 90.5-|-5.8 or 7.0. In other words, this cow is 7 % above other Ayrshire cows of the same age calving at the same time. Table 2. Correction for effect of age and calving month in Ayrshire (recording year 1971/72; results for latest 12 months production). a. Least squares estimates of the age effect. Cow born; month, year Rel.milk.prod. Fat % deviat. Ist prod, year 6.69 83.2 0,4 4.69 85.1 0.4 2.69 86.5 0.6 11,68 88.1 0.6 10,68 89.9 0.6 8.68 90.5 0.6 6.68 91.3 0.9 4.68 91.4 1.1 2.68 91.1 0.9 12.67 93.1 aver. 89.0 0.7 aver. 0.67 2nd prod, year 8.68 90.3 0.7 6.68 93.6 0.5 4.68 93.2 0.8 2.68 93.8 0.7 12.67 95.1 0.6 10.67 96.7 0.6 8.67 96.9 0.5 6.67 97.2 0.5 4.67 96.6 0.7 2.67 98.0 aver. 95.1 0.4 aver. 0.59 3rd prod, year 10.67 98.3 -0.6 8.67 97.0 0.4 6.67 97.3 0.6 4.67 98.1 0.5 2.67 98.5 0.4 12.66 99.7 0.2 10.66 100.9 0.3 8,66 101.8 0.2 6,66 101.3 0.2 ■ 4.66 101.2 aver. 99.4 0.2 aver. 0.24 567 568 b. Least squares constants (deviations from overall average) for the calving month effect. Production year Calving Ist 2nd 3rd month rel.milk fat % rel.milk fat % rel.milk fat % yield dev. yield dev. yield dev. 1 2.10.1 -1.6 -0.2 -1.3 -0.1 2 -0.0 0.3 -3.1 -0.1 -1.8 —O.l 3 -1.1 0.3 -1.0 -0.1 1.2 -0.2 4 -2.7 0.3 -0.2 -0.2 1.5 -0.2 5 -6.3 0.3 -1.9 0.1 -0.8 -0.2 6 -7.8 -0.0 -2.1 0.2 -1.8 0.1 7 -5.8 -0.6 -0.1 -0.0 -1.0 0.1 8 1.0 -0.3 1.6 0.00.2 -0.1 9 4.80.0 3.40.2 1.30.4 10 6.3 -0.1 3.3 0.11.8 0.3 11 5.1 -0.0 1.9 0.11.5 0.1 12 4.4 -0.2 -0.1 -0.1 -0.8 -0.1 The calculations and the results for all daughters of the sire are done similarly. The results with regard to fat % deviation, 4 % milk production, fat kg production and live weight deviation can be calculated in the same way. Correction for no. of daughters The milk production figures are corrected for the number of daughters the test is based on. This is done by multiplying the average relative yield by the regression factor n/ (n + 15), where n = no. of daughters. For ex- ample, when the test is based on 20 daughters the correction factor is 0.57, on 100 daughters it is 0.87. Let us assume that a sire has been tested on 45 daughters, the average relative production being + 4.8 units. Thus the cor- rected relative production is 45/ (45 + 15) X 4.8 = 0.75 X 4.8 = 3.6. In other words, we could expect the next progeny test (based on an infinite number of daughters) of this sire to be + 3.6 units above average. The fat % devi- ation is not corrected because it is quite repeatable. Use of progeny test results The most important task of the progeny tests is to provide a basis for the selection of bull sires and »ordinary» sires for production of female replace- ments. Each time the progeny test is calculated the State AI Committee (consisting of representatives from research, AI and breeding sectors, Ministry of Agriculture, Veterinary Medicine) meets and selects the sires on the basis of test results and the amount of pellets stored. The Breed Society classifies the bulls in breeding and elite classes accord- ing to test results. At present the selection criterion used when picking the 569 bulls is the so called combined deviation. This is made up of the corrected relative production plus 10 times the fat percentage deviation. The combined deviation gives approximately correct economic weights to milk production and fat percentage under our present conditions (Lindström and Maijala 1971). In practice this means that the main emphasis is on milk yield, while the fat percentage will be kept approximately at the present level. The Appendix gives a list of the information included in the progeny test. Improving the accuracy Because of our small herds the accuracy ot progeny tests based on small numbers of daughters is low. This is evident from Table 3. (The reason why the repeatability for some of the progeny tests based on more than 50 daughters also is low is probably to be found in the 1968 test which was based on a small number of daughters.) It would seem that at least 40 daughters, and preferably 60—80, would be needed to give a satisfactory degree of accuracy. Table 3. Repeatability of Ayrshire progeny tests for relative milk yield (Progeny tests corrected for age and month of calving; only first year records used.) No. of daughters in 1967 No. of bulls Correlation to 1968 pro- progeny test geny test, % g 20 59 48.2 21 - 30 67 47.9 31 - 40 59 69.1 41 - 50 40 77.6 51 - 70 62 50.9 71 - 100 43 77,1 lOO 43 65.2 The most effective way of improving the overall accuracy would probably be to calculate corrected herd averages. That is, before the herd average is computed the records for each cow in the herd would be cor- rected with regard to age and calving month. Moreover, it would be prefer- able to take into account the progeny test of the sire of each cow (Lind- ström and Maijala 1972). In this way it would be possible to eliminate at least some of the inaccuracies due to the varying composition of our small herds. Differences between areas Do progeny tests in one geographical area satisfactorily indicate a bull’s breeding value in another area? This question has recently been investigated. 570 Table 4. Association between progeny tests for the same Ayrshire Al-bulls in different geo- graphical areas (Recording year 1970/71 results). Aver. no. Genetic correlation, %*) No. of daughters rel.milk fat % rel.fat N 1 N 2 yield dev. kg yield Areas 1 ) SF x CF 68 117 38 101 101 106 SF x Ostr 69 91 33 86 96 92 CF x NF 41 90 16 107 103 114 Ostr. x NF 27 92 21 81 93 110 Average 94 98 105 J) SF = Southern Finland, CF = Central Finland Ostr. = Ostrobothnia, NF = Northern Finland rPI P 92) Genetic correlations (r G ) calculated from: r G = - )/ bx xb2 where rP[ p 2 phenotypic correlation between progeny test results in area 1 and 2 bx and b 2 =repeatability of progeny tests in area 1 and 2 (calculated from the number of daughters, assuming a heritability of 0.2 for one record, Lindström 1969). The main results are given in Table 4. The ranking order of the bulls is not affected to a noticeable degree. (Due to the method of calculation some of the correlations exceed 100 %). It seems, however, that the progeny tests in the Ostrobothnia area are somewhat less accurate indicators of a bulls value than progeny tests in other areas. The progeny tests here were calculat- ed using correction factors (for age and calving month) applicable to the respective areas. It might be useful to include this procedure also in the routine progeny testing as there seem to be differences between the areas in this respect. REFERENCES Harvey, W. R. 1966. Least squares analysis of data with unequal subclass number. ARS 20 —B. Agr.Res. Service. US Dep. of Agr. 157 pp. Lindström, U. B. 1969. Genetic change in milk yield and fat percentage in artificially bred populations of Finnish dairy cattle. Acta Agr. Fenn. 114. —» & Maijala, K. 1971. Studies on AI dairy sire provings. I. Importance of various recordecd characteristics. Z. Tierz. ziicht. biol. 87: 292 298. & Maijala, K. 1972. Improving accuracy of bull dam selection. Acta Agr. Scand. 22: 189-199. Varo, M. 1958. fiber die brauchbarkeit unserer Bullewerte auf den verschiedenen Leistungs- stufen. Acta Agr. Fenn. 93(4); I—3l. 571 Selostus Sonnien jälkeläisarvostelu Suomessa 1) Ulf Lindström ja Kalle Maijala Maatalouden tutkimuskeskus, Kotieläin]alostuslailos, Tikkurila Mikko Varo Helsingin yliopisto, Kotieläinten jalostustieteen laitos, Viikki Karjantarkkailun tuloksiin perustuvan sonnien jälkeläisarvostelun laskenta automaattisella tietojenkäsittelyllä aloitettiin v. 1950. Periaatteessa samanlaisena pysyneeseen laskentamenette- lyyn on tehty eräitä täydennyksiä. Nykyisin arvostelu lasketaan jälkeläisten kolmen ensim- mäisen tuotoksen perusteella käyttämällä suhteellisia tuotoksia tuotantokyvyn mittana. Tuo- tokset korjataan iän, tuotosvuoden ja poikimiskuukauden mukaan sekä lopullinen arvostelu jälkeläisten luvun mukaan. Kaikki sonnit, joilla on vähintään 10 jälkeläistä, arvostellaan. Arvostelun luotettavuuden arvioimiseksi on laskettu eri suurten jälkeläisryhmien ensim- mäisiin tuotoksiin perustuvien jälkeläisarvojen toistumiskertoimia. Tulos viittaa siihen, että vasta vähintään 40, mieluummin 60 —BO jälkeläistä riittää tyydyttävän luotettavaan arvoste- luun. *) Esitelmä, jonka tohtori Lindström piti Maailman 2. Ayrshirekonterenssissa Lahdessa 3.8. 1972. 572 Appendix. Examples of progenytests for Ayrshire bulls. Aver. Aver. Live ~ , , Aver. . n , ... Corrected Com- No milk fat Fat % weight Bull „ ~, Sire’s Dam’s , , , , , fat %,. , . bined Bull s name of prod, of prod, of /u devi- devi- Milk Fat 4 % no no no daught. daught. daught. ation ation devi- devi- milk ev ' , , daught. , , ation kg kg ° kg ation ation dev. 29107 Anttilan Mimro 23111 107745 242 4964 224 4.51 0.01 15 04.7 5.0 04.4 04.8 29111 Marius 23599 127772 243 4350 198 4.55 0.06 -08 -03.1 -1.9 -02.4 -02.5 29115 Ensilän Leif 23204 113499 16 4697 224 4.77 0.14 28 01.9 3.7 -01.6 03.3 29122 Marttilan Malli 23599 108519 68 4393 197 4.48 0.00 05 -04.0 -4.2 -04.3 -04.0 29129 Vihtamaan Mikael 23086 154462 97 4282 201 4.69 0.16 -03 -04.1 -1.1 -01.8 -02.5 29134 Mestari 23506 173318 12 4332 206 4.76 0.19 -01 01.5 3.3 03.3 03.4 29139 Upolan Maisteri 23111 135564 166 4707 200 4.25 -0.19 00 07.8 3.6 04.8 05.9 29141 Metsä-Jonnin Niku 23111 135585 120 4442 209 4.710.23 -10 -03.4 0.6 -00.6 -01.1 29151 Uusi-Mattilan Mainio ....23111 147842 196 4707 202 4.29 -0.10 -02 02.9 0.8 01,9 01.9 29163 Metsä-Paavolan Mauser 19909 160624 100 4581 208 4.54 0.02 -11 00,1 0.800.5 00.3 29166 Kopralan Mukava 23000 140617 168 4251 189 4.450.00 -09 -01.8 —l.B -01.6 -01.8 29177 Kruuvan Lähetti 25075 061074 110 4116 188 4.570.13 -07 -02.0 0.1 -00.6 -00.7 29188 Leppäniemen Mikko 23697 121717 64 4162 183 4.40 -0.05 -12 -00.8 —1.7 -00.8 -01.3 29199 Histan Lento 22501 076833 47 4344 188 4.33 -0.04 00 -01.7 -2.5 -02.0 -02.1 29202 Mäki-Mantilan Mahti 23394 140421 259 4265 188 4.41 -0.05 -01 00.1 -0.6 -00.4 -00.4 29205 Marmori 23674 250718 16 3525 170 4.820.43 -12 -03.7 0.9 -00.2 00.6 29211 Kuusikon Lippo 26064 154320 36 3951 174 4.40 0.01 10 -02.1 -1.9 -01.0 -02.0 29212 Luja 20649 138289 14 4118 207 5.030.11 12 -01.8 —0.6 -01.2 -00.7 29215 Kaartilan Masa 23000 137747 27 4456 208 4.670.13 08 -01.2 0.6 -00.3 00.1