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Extension factors for part-lactation in Churra sheep breed
Small Ruminant Research 63 (2006) 282–287
Extension factors for part-lactation in Churra sheep breed C.A. Cappelletti a , F.M.B. Rozen b,∗ , L.F. De La Fuente Crespo c , F. San Primitivo c a
Biostatistics Area, Facultad de Ciencias Veterinarias, Universidad de Buenos Aires, Av. Chorroar´ın 280, 1427 Buenos Aires, Argentina b Genetics Area, Facultad de Ciencias Veterinarias, Catedra de Bioestadistica, Universidad de Buenos Aires, Av. Chorroar´ın 280, 1427 Buenos Aires, Argentina c Genetics Area, Facultad de Veterinaria, Universidad de Le´ on, Espa˜na Received 18 March 2003; received in revised form 3 March 2005; accepted 3 March 2005 Available online 22 April 2005
Abstract Extension factors of incomplete lactation were developed for Churra sheep breed. These factors were estimated according to the methodology proposed for dairy cows, which is based on the prediction of the unknown portion of the lactation starting from the last available monthly record. Extension factors (FEMi ) were obtained by estimating the regression of milk production on a given control until 120 days with regard to the number of remaining days from this control until 120 days. The flock production level, type of birth, parity and age of dam at lambing were included in the model as fixed effects. The genetic correlations between standardized and extended lactations for two or three monthly controls were high, 0.997 and 0.999 (± 0.001) respectively, whereas heritabilities for standardized and extended lactation considering the daily production in two and three monthly controls were 0.240, 0.211 and 0.237 (± 0.02), respectively. These results could suggest that both, standardized and extended lactation are measures of the same trait. Spearman correlations coefficients between the breeding values of sires, from the standardized and extended lactations were 0.963 and 0.977, respectively. This would indicate that it is convenient to include extended lactations when estimating the breeding value of sires, for it would help to increase its precision as the tendency to reject low producing animals would be avoided. © 2005 Elsevier B.V. All rights reserved. Keywords: Dairy sheep; Churra breed; Incomplete lactations; Extension factors; Monthly control-days
1. Introduction Churra sheep, an indigenous breed farmed in North Western Spain, is one of the most important milk pro∗ Corresponding author. Tel.: +54 11 4 505 0434; fax: +54 11 4 524 8474. E-mail addresses: [email protected], [email protected] (F.M.B. Rozen).
0921-4488/$ – see front matter © 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.smallrumres.2005.03.001
ducers in Spain. The milk production is directed toward cheese manufacturing. A selection scheme for milk production began in 1985 (for description see De La Fuente et al., 1995), allowing a connection among flocks via artificial insemination. Initially, genetic evaluation for Churra dairy sheep was performed for total milk. At present, genetic evaluation is performed, for other Spanish breed sheep, on the basis of models that
C.A. Cappelletti et al. / Small Ruminant Research 63 (2006) 282–287
use the total production for standardized lactation to 120 days as dependent variable (Ugarte et al., 1996; De La Fuente et al., 1995; P´erez-Guzm´an et al., 1996; El-Saied et al., 1998). When one or two of the necessary controls to estimate milk production were missing for Churra breed (De la Fuente et al., 1996) lactation was considered incomplete and was not used to estimate the breeding values of these females’ sires. If the interruption of lactation was caused by low yields from the first controls, these animals were systematically eliminated from the flock. This resulted in a biased breeding value of the sires due to an overestimation of those sires because records of less productive daughters were missing. In dairy cows (Auran, 1976; Danell, 1982; Cordero et al., 1990), as well as in goats (Wiggans et al., 1979), high correlations were estimated between certain portions of lactation and the complete lactation. Some authors used expected lactation curves for animals under milk control (Wilkmink, 1987; Wilkmink and Ouweltjes, 1992). This may be a more efficient mechanism but it may demand a computing support not always feasible for small and even medium-sized animal breeding centers. For dairy cattle, lactation extension, would allow on the one hand, the inclusion of more information to estimate the breeding value and on the other hand, it is possible to shorten the generation interval, since the valuation of certain animals can be performed with some months in advance. As regards to ovine, the lactation period is much shorter than that of dairy cows. As a result, the purpose of the extension would be to retrieve information that would otherwise be lost. If included, this information could contribute to increase the reliability of the genetic prediction of the sires’ parents (Serrano et al., 1996). The present study is therefore aimed at estimating the extension factors of incomplete lactation in the Churra breed in order to adjust them to a 120-day standardized lactation.
2. Materials and methods The breeding value of the Churra sheep’s sires, which are native from the central plateau of the Castilla and Le´on community in Spain, was carried out by Asociaci´on de Criadores de Ganado Selecto de Raza Churra
283
(ANCHE) and performed through two data files, comprising the additive relationship matrix and the sheep milk yield records. A mixed linear model to predict genetic values combining both files (Van Vleck, 1993) was used. Sheep milk production was estimated from four monthly controls. The standardized production at 120 days was calculated following Fleischmann’s method (Barillet, 1985), which incorporated these control values (Carriedo and San Primitivo, 1981, 1989). A database of milking records covering the period from 1990 to 1997 was used. This database comprised 13,278 lactation records from 4617 ewes in production, daughters of 315 rams. Test-day records were obtained monthly according to the official Spanish milk recording scheme for ewes and according to the International Committee for Animal Recording (ICAR, 1992) recommendation. The database was divided at random in two parts, with 6639 lactation records each. The first part (A) was used to calculate the extension coefficients for milk yield at 120 days, and the second one (B), to extend incomplete lactations with the coefficients calculated with sample (A), and also to estimate genetic correlations among standardized and extended values, as well as the corresponding heritabilities. The additive relationship matrix was incorporated in the second file. According to Auran (1976) and Danell (1982), the monthly extension factors (FEMi ) were calculated first from the expression: L120 = PAi + FEMi xPCi (1) where L120 is the standardized production at 120 days; PAi is the cumulative production (standardized) until the control i = 2, 3 or 4; and PCi is the production on control i with i = 3 or 4, since it is assumed that production records of the first 2-monthly controls are available. By solving for FEMi in (1) we have (L120 − PAi ) FEMi = (2) PCi and from (2) the regression coefficient of the FEMi were estimated regarding the days to go from control i up to 120 days and by means of a linear model (3). The model is FEMjklmi = µ + fpj + tbk + prl + adlm + ¯ + εjklmi bijklm (Xijklm − X)
(3)
284
C.A. Cappelletti et al. / Small Ruminant Research 63 (2006) 282–287
where µ is the average mean, FEMjklmi is the dependent variable of the model which corresponds to the already defined monthly extension factors. The fixed effects included in the model were: flock production level (fpj ) with two levels (≤135 l and >135 l, 135 l being the mean yield for complete lactation), type of birth (tbk ) with two levels (single and multiple), parity (prl ) with three levels (one to three) and age of dam at lambing (adlm ) with four levels (one to four). The co-variable (Xijklm ) corresponds to the days between the day of control i and the 120-day in lactation with flock production level j, type of birth k, parity l and ¯ is the average mean age of dam at lambing m and X of the covariable (Xijklm ). The regression coefficients ¯ were incor(bijklm ) of FEM whit respect to (Xijklm − X) porated in the model nested in the levels combinations of the indicated fixed factors, totaling 48 subclasses (2 × 2 × 3 × 4). Finally, εjklmi is the residual error. The general linear model (GLM) of the statistical package SAS (SAS, 1989) was used for estimating regression coefficients. According to Van Vleck and Henderson (1961), the effect of the average flock can be substituted by flock production level, for practical reason and not much error is introduced. Although this criteria efficiency is 10% lower than the estimate within the flock, this is compensated for by the simplification of the calculations, for cooperative dairy record processing center. Through the estimates of the regression coefficients, 120-day-extended lactations (LE120 ) were calculated starting from the last available control and considering the successive ones as unknown. For any control (p) is LE120 = PAp + bijklm (120 − Dp )PCp
(4)
where LE120 is the production of a 120-day-extended lactation; PAp is the cumulative production of 120 days until last known control p; bijklm is the regression coefficient of FEMi on (120-Dp) in each combination of fixed factors that affect lactation; Dp are the days between parity and the last known control p; and PCp is the control p production. To check the accuracy of the results of the extended lactations, sample B was used with 6639 lactations with the 4 monthly records, and two record bases were simulated, one with the first two controls, and the other with the three first ones, and were extended to 120 days. With these data, genetic correlations and heritabilities
were calculated between the standardized productions and the extended ones, by means of the REML-VCE 4.2 program (Groeneveld, 1998) for a multi-trait animal model with repeated measures. The model included the fixed effects flock-year-parity month, parity, age of dam and type at lambing and the random effects of animal genotype, permanent environment and the residual error. The estimated breeding values of the sires, from a data base with 100% standardized lactations was correlated with those estimated from a data base with 50% standardized lactations and 50% extended lactations, with 2 and 3 monthly controls available. The Spearman coefficient was used to determine discrepancies within the genetic values of animals.
3. Results and discussion The R2 of model (3) was 90% and the effects of type of birth, parity, age of dam at lambing, and of the co-variable were significant (** p < 0.01), thus indicating it is suitable to estimate the regression coefficients of the monthly extension factors on production from the last control until 120 days. The regression coefficients, nested in the levels of the fixed effects, were all significant (** p < 0.01), and are shown on Table 1. These are the coefficients applied in the (4) expression to calculate the 120-day extended lactation (LE120 ). The estimated values keep close relation with those obtained by Serrano et al. (1996) in Manchega ovine breed. Table 2 shows heritabilities and genetic correlations between standardized and extended lactation considering that daily production in two or three controls is possible. As it can be observed in Table 2, genetic correlations are very high. Heritability values of 0.211 and 0.237 are quite similar to 0.240, this fact corresponds to the standardized milk production character to 120 days, especially when lactation extension is done from three available controls on. This shows that standardized production to 120-day lactation is almost the same as the extended production from two or three known productive controls. Table 3 shows the Spearman correlations between the breeding values of the sires, from a data base with 100% standardized lactations with those estimated
C.A. Cappelletti et al. / Small Ruminant Research 63 (2006) 282–287 Table 1 Regression coefficients (b) to extend part-lactation to 120 days for flock production (liters), calculated from the whole data FP
TB
PR
ADL
REG (b)
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2
1 1 1 1 2 2 2 2 3 3 3 3 1 1 1 1 2 2 2 2 3 3 3 3 1 1 1 1 2 2 2 2 3 3 3 3 1 1 1 1 2 2 2 2 3 3 3 3
1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4
0.888 0.887 0.817 0.827 0.786 0.852 0.848 0.846 0.820 0.843 0.848 0.839 0.912 0.897 0.860 0.887 0.763 0.824 0.788 0.889 0.769 0.847 0.837 0.860 0.849 0.839 0.839 0.814 0.984 0.817 0.812 0.811 0.710 0.812 0.810 0.831 0.789 0.825 0.790 0.820 0.793 0.810 0.802 0.783 0.730 0.779 0.803 0.812
FP: flock production level; TB: type of birth; PR: parity; ADL: age of dam at lambing; REG: regression coefficient.
285
Table 2 Heritabilities (on the diagonal) and genetic correlations between standardized and extended lactations (Exten.) considering two and three controls Production
Standardized
Exten.(two controls)
Exten.(three controls)
Standardized Extended with two controls Extended with three controls
0.240
0.997 0.211
0.999 – 0.237
from a data base with 50% standardized lactations and 50% extended lactations, both for 2 and 3 monthly controls. The production records are also subdivided into several categories according to the different numbers of daughters per sire, in order to check if correlations indicate important modifications. Estimated correlations between the breeding value of sires, from complete lactations (100%) and from complete lactations (50%) plus incomplete extended lactations (50%) roughly show a good concord among values, even though when the first two controls are used to extend the lactations, a correlation of about 95% is obtained, with at least 30 daughters per sire. This threshold decreases to 20 daughters for extended lactations when the first three controls are available. Anyway, Sperman correlation values here obtained are lower than the ones estimated by Serrano et al. (1996) in the Manchega sheep breed in about 3 to 4 points in percentage terms. In accordance with this fact, it is necessary to incorporate these incomplete lactations (in which at least the first and second controls are available, since using Table 3 Spearman correlations between estimated breeding values with 100% standardized lactations (LES100) and 50% standardized and 50% extended, with two (LEX12) and three (LEX13) controls by the number of daughters per sire No. daughters
No. sires
LES100LEX12
LES100LEX13
40+ 30+ 20+ 10+ All S.D. (average) ± 0.009
85 107 143 192 315
0.963 0.942 0.930 0.911 0.891
0.977 0.961 0.958 0.930 0.925
S.D.: standard deviation.
286
C.A. Cappelletti et al. / Small Ruminant Research 63 (2006) 282–287
lactations with only one control might be considered as rather imprecise), to predict the breeding value of reproductors by means of lactational models. The consequence of this practice is that the obtained Spearman correlations are in the order of 0.96 and 0.98 among the values that are carried out with 100% of the complete lactations with the ones obtained from data with a 50% of complete lactations and 50% of extended lactations, if the extension corresponds to production registers with two or three controls, respectively (Table 3). If extended lactations were not incorporated, the correlations that result from using data base with 100% of complete lactations with respect to bases with only 50% of the same lactations, is about 0.81 for parents with more than 40 daughters and only 0.56 for parents with 10 daughters or more (Cappelletti, 1998). The given results might let us consider that the incomplete lactations extension, in which at least the two first controls are available, would be the most suitable practice for estimating breeding value, for it would allow to avoid the biases that might be done when only the most productive daughters are included. 4. Conclusions The criterion of extending incomplete lactations described here is suitable when at least two monthly controls are available, as shown by the high genetic correlations obtained. The model used to estimate the extension factors for incomplete lactations should include the milk production level of the flock, age of dam at lambing, type of birth and parity as fixed effects. The inclusion of incomplete lactations in the breeding value of sires, prior extension to 120 days, contributes to its accurate prediction because it avoids the biases done when culling animals with low production. The results obtained in this paper might be the base of a new approach of the diary control, as regards to a possible decrease in the number of controls to assess the productive capacity of the animals with the consequent economic benefit of these strategies. Acknowledgements The authors thank ANCHE, Spain, for their cooperation in supplying data; the CICYT through the
National Project AGF96-0819-CP, Le´on, Spain; and UBACyT for the partial support through the AV22 Project. References Auran, T., 1976. Studies on monthly and cumulative monthly milk yield records. IV. Estimating total lactation from part-lactation. Act. Agric. Scand. 26, 10–17. Barillet, F., 1985. Am´elioration g´en´etique de la composition du lait des brebis: l’exemple de la breed Lacaune (Genetic improvement for ewe milk composition. The case of Lacaune breed). In: Th´ese de Docteur Ing´enieur. INA, Paris-Grignon, France, 238 pp. Cappelletti, C.A., 1998. Modelos Estad´ısticos para la Valoraci´on Gen´etica en Ganado Ovino de Aptitud L´actea. Disertaci´on doctoral. Universidad de Le´on, Espa˜na (Statistical models for the genetic assessment of ovine sheep milk). Doctoral dissertation, Le´on University, Spain), 161 pp. Carriedo, J.A., San Primitivo, F., 1981. Estudio gen´etico de los factores que influyen en la producci´on l´actea del ganado ovino. I. Tratamiento inform´atico y estudios previos (Genetic studies on factors affecting sheep milk production. I. Computer treatment and previous studies). Ann. Fac. Vet. Le´on 27, 87–97. Carriedo, J.A., San Primitivo, F., 1989. Mejora gen´etica de la producci´on l´actea. OVIS. Tratado de patolog´ıa y producci´on ovina (Genetic improvement of milk production). OVIS. Pathology and ovine production treaty, vol. 3. Luz´ans, Madrid, Espa˜na, pp. 53–77. Cordero, J.L., Alenda, R., Vargas, P., 1990. Factores de extensi´on de la lactaci´on a 305 d´ıas en Cantabria, Pa´ıs Vasco y Orense (Extension factors of lactation to 305 days in Cantabria, Basque Republic and Orense). Frisona, Espa˜nola, pp. 144–147. Danell, B., 1982. Studies on lactation yield and individual test-day yield of Swedish dairy cows. II. Estimates of genetic and phenotypic parameters. Acta Agric. Scand 32, 103–113. De La Fuente, L.F., Baro, J.A., San Primitivo, F., 1995. Breeding programme for Spanish Churra sheep breed. Cahiers Options Mediterran´ennes 11, 165–172. De La Fuente, L.F., Merino, E., L´opez, T., San Primitivo, F., 1996. Problem´atica del programa de selecci´on de la Raza Churra (Selection program of the Churra breed problems). ITEA 92A (3), 31–43. El-Saied, U.M., Carriedo, J.A., Baro, J.A., De La Fuente, L.F., San Primitivo, F., 1998. Genetics correlations and heretabilities for milk yield and lactation length of dairy sheep. Small Rumin. Res. 27, 217–221. Groeneveld, E., 1998. PEST User’s Manual. Ver. 4.2. Inst. Anim. Husb. Anim. Behav., Germany. ICAR, 1992. International Committee for Animal Recording. Regulations for milk recording in dairy sheep. Group of experts for milk recording in dairy sheep. Roma, Italia, p. 32. P´erez-Guzm´an, M.D., Serrano, M., Montoro, V., Jurado, J.J., 1996. Estima de la tendencia gen´etica en el esquema de selecci´on de la raza ovina Manchega, incluyendo grupos gen´eticos (Estimate of the genetic tendency in the Manchega ovine breed selection, including genetic group). ITEA 1 (1), 394.
C.A. Cappelletti et al. / Small Ruminant Research 63 (2006) 282–287 SAS Institute Inc., 1989. SAS/STAT user’s guide, version 6, vol. 2, fourth ed. SAS Institute Inc., Cary, NC. Serrano, M., Jurado, J.J., Perez-Guzman, M.D., Montoro, V., 1996. C´alculo de los factores de extensi´on de la lactaci´on a 120 d´ıas en ganado ovino Manchego (Projection factors to extend partlactations in Manchega sheep breed). Inv. Agric. Prod. San. An. 11 (1), 69–83. Ugarte, E., Urarte, E., Arranz, J., Arrese, F., 1996. Programa de mejora gen´etica y selecci´on de las ovejas de raza Laxta y Carranzana en la Comunidad Aut´onoma Vasca y Navarra: problemas que presenta su aplicaci´on pr´actica (Genetic improvement program and sheep selection of Laxta and Carranzana breed in the Basque Independent Community and Navarra: problems of its practical application). ITEA 92A (3), 11–21.
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Van Vleck, L.D., Henderson, C.R., 1961. Extending part lactation milk records by regression ignoring herd effects. J. Dairy Sci. 44, 1519–1528. Van Vleck, L.D., 1993. Selection Index and Introduction to Mixed Model Methods. CRC-Press, London, 491 pp. Wiggans, G.R., Van Vleck, L.D., Dickinson, F.N., 1979. Projection factors for goat lactation records. J. Dairy Sci. 62, 797– 801. Wilkmink, J.B.M., 1987. Comparison of different methods of predicting 305-day milk yield using means calculated from within herd lactation curves. Livest. Prod. Sci. 17, 1–17. Wilkmink, J.B.M., Ouweltjes, W., 1992. Calculation of lactation production in the Netherlands. In: Proceedings of the ICAR Mtg., Nesstift, Austria, pp. 121–126.
Extension factors for part-lactation in Churra sheep breed C.A. Cappelletti a , F.M.B. Rozen b,∗ , L.F. De La Fuente Crespo c , F. San Primitivo c a
Biostatistics Area, Facultad de Ciencias Veterinarias, Universidad de Buenos Aires, Av. Chorroar´ın 280, 1427 Buenos Aires, Argentina b Genetics Area, Facultad de Ciencias Veterinarias, Catedra de Bioestadistica, Universidad de Buenos Aires, Av. Chorroar´ın 280, 1427 Buenos Aires, Argentina c Genetics Area, Facultad de Veterinaria, Universidad de Le´ on, Espa˜na Received 18 March 2003; received in revised form 3 March 2005; accepted 3 March 2005 Available online 22 April 2005
Abstract Extension factors of incomplete lactation were developed for Churra sheep breed. These factors were estimated according to the methodology proposed for dairy cows, which is based on the prediction of the unknown portion of the lactation starting from the last available monthly record. Extension factors (FEMi ) were obtained by estimating the regression of milk production on a given control until 120 days with regard to the number of remaining days from this control until 120 days. The flock production level, type of birth, parity and age of dam at lambing were included in the model as fixed effects. The genetic correlations between standardized and extended lactations for two or three monthly controls were high, 0.997 and 0.999 (± 0.001) respectively, whereas heritabilities for standardized and extended lactation considering the daily production in two and three monthly controls were 0.240, 0.211 and 0.237 (± 0.02), respectively. These results could suggest that both, standardized and extended lactation are measures of the same trait. Spearman correlations coefficients between the breeding values of sires, from the standardized and extended lactations were 0.963 and 0.977, respectively. This would indicate that it is convenient to include extended lactations when estimating the breeding value of sires, for it would help to increase its precision as the tendency to reject low producing animals would be avoided. © 2005 Elsevier B.V. All rights reserved. Keywords: Dairy sheep; Churra breed; Incomplete lactations; Extension factors; Monthly control-days
1. Introduction Churra sheep, an indigenous breed farmed in North Western Spain, is one of the most important milk pro∗ Corresponding author. Tel.: +54 11 4 505 0434; fax: +54 11 4 524 8474. E-mail addresses: [email protected], [email protected] (F.M.B. Rozen).
0921-4488/$ – see front matter © 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.smallrumres.2005.03.001
ducers in Spain. The milk production is directed toward cheese manufacturing. A selection scheme for milk production began in 1985 (for description see De La Fuente et al., 1995), allowing a connection among flocks via artificial insemination. Initially, genetic evaluation for Churra dairy sheep was performed for total milk. At present, genetic evaluation is performed, for other Spanish breed sheep, on the basis of models that
C.A. Cappelletti et al. / Small Ruminant Research 63 (2006) 282–287
use the total production for standardized lactation to 120 days as dependent variable (Ugarte et al., 1996; De La Fuente et al., 1995; P´erez-Guzm´an et al., 1996; El-Saied et al., 1998). When one or two of the necessary controls to estimate milk production were missing for Churra breed (De la Fuente et al., 1996) lactation was considered incomplete and was not used to estimate the breeding values of these females’ sires. If the interruption of lactation was caused by low yields from the first controls, these animals were systematically eliminated from the flock. This resulted in a biased breeding value of the sires due to an overestimation of those sires because records of less productive daughters were missing. In dairy cows (Auran, 1976; Danell, 1982; Cordero et al., 1990), as well as in goats (Wiggans et al., 1979), high correlations were estimated between certain portions of lactation and the complete lactation. Some authors used expected lactation curves for animals under milk control (Wilkmink, 1987; Wilkmink and Ouweltjes, 1992). This may be a more efficient mechanism but it may demand a computing support not always feasible for small and even medium-sized animal breeding centers. For dairy cattle, lactation extension, would allow on the one hand, the inclusion of more information to estimate the breeding value and on the other hand, it is possible to shorten the generation interval, since the valuation of certain animals can be performed with some months in advance. As regards to ovine, the lactation period is much shorter than that of dairy cows. As a result, the purpose of the extension would be to retrieve information that would otherwise be lost. If included, this information could contribute to increase the reliability of the genetic prediction of the sires’ parents (Serrano et al., 1996). The present study is therefore aimed at estimating the extension factors of incomplete lactation in the Churra breed in order to adjust them to a 120-day standardized lactation.
2. Materials and methods The breeding value of the Churra sheep’s sires, which are native from the central plateau of the Castilla and Le´on community in Spain, was carried out by Asociaci´on de Criadores de Ganado Selecto de Raza Churra
283
(ANCHE) and performed through two data files, comprising the additive relationship matrix and the sheep milk yield records. A mixed linear model to predict genetic values combining both files (Van Vleck, 1993) was used. Sheep milk production was estimated from four monthly controls. The standardized production at 120 days was calculated following Fleischmann’s method (Barillet, 1985), which incorporated these control values (Carriedo and San Primitivo, 1981, 1989). A database of milking records covering the period from 1990 to 1997 was used. This database comprised 13,278 lactation records from 4617 ewes in production, daughters of 315 rams. Test-day records were obtained monthly according to the official Spanish milk recording scheme for ewes and according to the International Committee for Animal Recording (ICAR, 1992) recommendation. The database was divided at random in two parts, with 6639 lactation records each. The first part (A) was used to calculate the extension coefficients for milk yield at 120 days, and the second one (B), to extend incomplete lactations with the coefficients calculated with sample (A), and also to estimate genetic correlations among standardized and extended values, as well as the corresponding heritabilities. The additive relationship matrix was incorporated in the second file. According to Auran (1976) and Danell (1982), the monthly extension factors (FEMi ) were calculated first from the expression: L120 = PAi + FEMi xPCi (1) where L120 is the standardized production at 120 days; PAi is the cumulative production (standardized) until the control i = 2, 3 or 4; and PCi is the production on control i with i = 3 or 4, since it is assumed that production records of the first 2-monthly controls are available. By solving for FEMi in (1) we have (L120 − PAi ) FEMi = (2) PCi and from (2) the regression coefficient of the FEMi were estimated regarding the days to go from control i up to 120 days and by means of a linear model (3). The model is FEMjklmi = µ + fpj + tbk + prl + adlm + ¯ + εjklmi bijklm (Xijklm − X)
(3)
284
C.A. Cappelletti et al. / Small Ruminant Research 63 (2006) 282–287
where µ is the average mean, FEMjklmi is the dependent variable of the model which corresponds to the already defined monthly extension factors. The fixed effects included in the model were: flock production level (fpj ) with two levels (≤135 l and >135 l, 135 l being the mean yield for complete lactation), type of birth (tbk ) with two levels (single and multiple), parity (prl ) with three levels (one to three) and age of dam at lambing (adlm ) with four levels (one to four). The co-variable (Xijklm ) corresponds to the days between the day of control i and the 120-day in lactation with flock production level j, type of birth k, parity l and ¯ is the average mean age of dam at lambing m and X of the covariable (Xijklm ). The regression coefficients ¯ were incor(bijklm ) of FEM whit respect to (Xijklm − X) porated in the model nested in the levels combinations of the indicated fixed factors, totaling 48 subclasses (2 × 2 × 3 × 4). Finally, εjklmi is the residual error. The general linear model (GLM) of the statistical package SAS (SAS, 1989) was used for estimating regression coefficients. According to Van Vleck and Henderson (1961), the effect of the average flock can be substituted by flock production level, for practical reason and not much error is introduced. Although this criteria efficiency is 10% lower than the estimate within the flock, this is compensated for by the simplification of the calculations, for cooperative dairy record processing center. Through the estimates of the regression coefficients, 120-day-extended lactations (LE120 ) were calculated starting from the last available control and considering the successive ones as unknown. For any control (p) is LE120 = PAp + bijklm (120 − Dp )PCp
(4)
where LE120 is the production of a 120-day-extended lactation; PAp is the cumulative production of 120 days until last known control p; bijklm is the regression coefficient of FEMi on (120-Dp) in each combination of fixed factors that affect lactation; Dp are the days between parity and the last known control p; and PCp is the control p production. To check the accuracy of the results of the extended lactations, sample B was used with 6639 lactations with the 4 monthly records, and two record bases were simulated, one with the first two controls, and the other with the three first ones, and were extended to 120 days. With these data, genetic correlations and heritabilities
were calculated between the standardized productions and the extended ones, by means of the REML-VCE 4.2 program (Groeneveld, 1998) for a multi-trait animal model with repeated measures. The model included the fixed effects flock-year-parity month, parity, age of dam and type at lambing and the random effects of animal genotype, permanent environment and the residual error. The estimated breeding values of the sires, from a data base with 100% standardized lactations was correlated with those estimated from a data base with 50% standardized lactations and 50% extended lactations, with 2 and 3 monthly controls available. The Spearman coefficient was used to determine discrepancies within the genetic values of animals.
3. Results and discussion The R2 of model (3) was 90% and the effects of type of birth, parity, age of dam at lambing, and of the co-variable were significant (** p < 0.01), thus indicating it is suitable to estimate the regression coefficients of the monthly extension factors on production from the last control until 120 days. The regression coefficients, nested in the levels of the fixed effects, were all significant (** p < 0.01), and are shown on Table 1. These are the coefficients applied in the (4) expression to calculate the 120-day extended lactation (LE120 ). The estimated values keep close relation with those obtained by Serrano et al. (1996) in Manchega ovine breed. Table 2 shows heritabilities and genetic correlations between standardized and extended lactation considering that daily production in two or three controls is possible. As it can be observed in Table 2, genetic correlations are very high. Heritability values of 0.211 and 0.237 are quite similar to 0.240, this fact corresponds to the standardized milk production character to 120 days, especially when lactation extension is done from three available controls on. This shows that standardized production to 120-day lactation is almost the same as the extended production from two or three known productive controls. Table 3 shows the Spearman correlations between the breeding values of the sires, from a data base with 100% standardized lactations with those estimated
C.A. Cappelletti et al. / Small Ruminant Research 63 (2006) 282–287 Table 1 Regression coefficients (b) to extend part-lactation to 120 days for flock production (liters), calculated from the whole data FP
TB
PR
ADL
REG (b)
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2
1 1 1 1 2 2 2 2 3 3 3 3 1 1 1 1 2 2 2 2 3 3 3 3 1 1 1 1 2 2 2 2 3 3 3 3 1 1 1 1 2 2 2 2 3 3 3 3
1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4
0.888 0.887 0.817 0.827 0.786 0.852 0.848 0.846 0.820 0.843 0.848 0.839 0.912 0.897 0.860 0.887 0.763 0.824 0.788 0.889 0.769 0.847 0.837 0.860 0.849 0.839 0.839 0.814 0.984 0.817 0.812 0.811 0.710 0.812 0.810 0.831 0.789 0.825 0.790 0.820 0.793 0.810 0.802 0.783 0.730 0.779 0.803 0.812
FP: flock production level; TB: type of birth; PR: parity; ADL: age of dam at lambing; REG: regression coefficient.
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Table 2 Heritabilities (on the diagonal) and genetic correlations between standardized and extended lactations (Exten.) considering two and three controls Production
Standardized
Exten.(two controls)
Exten.(three controls)
Standardized Extended with two controls Extended with three controls
0.240
0.997 0.211
0.999 – 0.237
from a data base with 50% standardized lactations and 50% extended lactations, both for 2 and 3 monthly controls. The production records are also subdivided into several categories according to the different numbers of daughters per sire, in order to check if correlations indicate important modifications. Estimated correlations between the breeding value of sires, from complete lactations (100%) and from complete lactations (50%) plus incomplete extended lactations (50%) roughly show a good concord among values, even though when the first two controls are used to extend the lactations, a correlation of about 95% is obtained, with at least 30 daughters per sire. This threshold decreases to 20 daughters for extended lactations when the first three controls are available. Anyway, Sperman correlation values here obtained are lower than the ones estimated by Serrano et al. (1996) in the Manchega sheep breed in about 3 to 4 points in percentage terms. In accordance with this fact, it is necessary to incorporate these incomplete lactations (in which at least the first and second controls are available, since using Table 3 Spearman correlations between estimated breeding values with 100% standardized lactations (LES100) and 50% standardized and 50% extended, with two (LEX12) and three (LEX13) controls by the number of daughters per sire No. daughters
No. sires
LES100LEX12
LES100LEX13
40+ 30+ 20+ 10+ All S.D. (average) ± 0.009
85 107 143 192 315
0.963 0.942 0.930 0.911 0.891
0.977 0.961 0.958 0.930 0.925
S.D.: standard deviation.
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lactations with only one control might be considered as rather imprecise), to predict the breeding value of reproductors by means of lactational models. The consequence of this practice is that the obtained Spearman correlations are in the order of 0.96 and 0.98 among the values that are carried out with 100% of the complete lactations with the ones obtained from data with a 50% of complete lactations and 50% of extended lactations, if the extension corresponds to production registers with two or three controls, respectively (Table 3). If extended lactations were not incorporated, the correlations that result from using data base with 100% of complete lactations with respect to bases with only 50% of the same lactations, is about 0.81 for parents with more than 40 daughters and only 0.56 for parents with 10 daughters or more (Cappelletti, 1998). The given results might let us consider that the incomplete lactations extension, in which at least the two first controls are available, would be the most suitable practice for estimating breeding value, for it would allow to avoid the biases that might be done when only the most productive daughters are included. 4. Conclusions The criterion of extending incomplete lactations described here is suitable when at least two monthly controls are available, as shown by the high genetic correlations obtained. The model used to estimate the extension factors for incomplete lactations should include the milk production level of the flock, age of dam at lambing, type of birth and parity as fixed effects. The inclusion of incomplete lactations in the breeding value of sires, prior extension to 120 days, contributes to its accurate prediction because it avoids the biases done when culling animals with low production. The results obtained in this paper might be the base of a new approach of the diary control, as regards to a possible decrease in the number of controls to assess the productive capacity of the animals with the consequent economic benefit of these strategies. Acknowledgements The authors thank ANCHE, Spain, for their cooperation in supplying data; the CICYT through the
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