Reprodukcinių savybių ir jas įtakojančių veiksnių analizė Lietuvoje veisiamų juodmargių galvijų populiacijoje ; Analysis of reproductive features and factors influencing these features in the black & white cattle population in Lithuania
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LITHUANIAN VETERINARY ACADEMY The work was carried out at the Lithuanian Veterinary Academy in 2001–2005. The research supervisor Assoc. prof. dr. Ilona Miceikien ė (Lithuanian Veterinary Academy, biomedical sciences, zootechny – 13 B). Chairman of Zootechny science council Prof. habil. dr. Česlovas Jukna (Lithuanian Veterinary Academy, biomedical Rasa Petraškien ė sciences, zootechny – 13 B). Members: Prof. at Incumbent, dr. Antanas Sederevi čius (Lithuanian Veterinary Academy, biomedical sciences, veterinary medicine – 12 B); Prof. at Incumbent dr. Bronius Bakutis (Lithuanian Veterinary Academy, ANALYSIS OF REPRODUCTIVE FEATURES AND biomedical sciences, veterinary medicine – 12 B); Prof. habil. dr. Romas Gružauskas (Lithuanian Veterinary Academy, biomedical FACTORS INFLUENCING THESE FEATURES IN THE sciences, zootechny – 13 B); Prof. habil. dr. Vytautas Tarvydas (LVA Institute of Animal Science, biomedical BLACK & WHITE CATTLE POPULATION IN LITHUANIA sciences, zootechny – 13 B). Opponents: Assoc. prof. dr. Eugenijus Aniulis (Lithuanian Veterinary Academy, biomedical Summary of dissertation sciences, veterinary medicine – 12 B); Assoc. prof. dr. Asta Klimien ė (Šiauliai University, biomedical sciences, Biomedical sciences, zootechny (13 B) zootechny – 13 B).
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| Publié par | lithuanian_veterinary_academy |
| Publié le | 01 janvier 2005 |
| Nombre de lectures | 47 |
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Rasa Petrakien
LITHUANIAN VETERINARY ACADEMY ANALYSIS OF REPRODUCTIVE FEATURES AND FACTORS INFLUENCING THESE FEATURES IN THE BLACK & WHITE CATTLE POPULATION IN LITHUANIA
Summary of dissertation Biomedical sciences, zootechny (13 B)
Kaunas, 2005
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The work was carried out at the Lithuanian Veterinary Academy in 20012005. The research supervisor Assoc. prof. dr. Ilona Miceikien (Lithuanian Veterinary Academy, biomedical sciences, zootechny 13 B). Chairman of Zootechny science council Prof. habil. dr. Č eslovas Jukna (Lithuanian Veterinary Academy, biomedical sciences, zootechny 13 B). Members: Prof. at Incumbent, dr. Antanas Sederevi č ius (Lithuanian Veterinary Academy, biomedical sciences, veterinary medicine 12 B); Prof. at Incumbent dr. Bronius Bakutis (Lithuanian Veterinary Academy, biomedical sciences, veterinary medicine 12 B); Prof. habil. dr. Romas Gruauskas (Lithuanian Veterinary Academy, biomedical sciences, zootechny 13 B); Prof. habil. dr. Vytautas Tarvydas (LVA Institute of Animal Science, biomedical sciences, zootechny 13 B). Opponents: Assoc. prof. dr. Eugenijus Aniulis (Lithuanian Veterinary Academy, biomedical sciences, veterinary medicine 12 B); Assoc. prof. dr. Asta Klimien (iauliai University, biomedical sciences, zootechny 13 B). Public defence of doctoral dissertation in Zootechny science council will take place at the Lithuanian Veterinary Academy I auditorium 1 pm LT on 28 nd October of 2005. Address: Til s 18, LT- 47118 Kaunas, Lithuania. The abstract of doctoral dissertation has been sent on 26 th of September 2005 according to confirmed address list. The doctoral thesis is available at the library of the Lithuanian Veterinary Academy.
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LIETUVOS VETERINARIJOS AKADEMIJA Rasa Petrakien
REPRODUKCINI SAVYBI IR JAS TAKOJAN Č I VEIKSNI ANALIZ LIETUVOJE VEISIAM JUODMARGI GALVIJ POPULIACIJOJE
Daktaro disertacijos santrauka Biomedicinos mokslai, zootechnika (13 B)
Kaunas, 2005
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Disertacija rengta 20012005 metais Lietuvos veterinarijos akademijoje. Mokslinis vadovas doc. dr. Ilona Miceikien (Lietuvos veterinarijos akademija, biomedicinos mokslai, zootechnika 13 B) Disertacija ginama Lietuvos veterinarijos akademijos Zootechnikos mokslo krypties disertacijos gynimo taryboje: Pirmininkas prof. habil. dr. Č eslovas Jukna (Lietuvos veterinarijos akademija, biomedicinos mokslai, zootechnika 13 B). Nariai: e. prof. p. dr. Antanas Sederevi č ius (Lietuvos veterinarijos akademija, biomedicinos mokslai, veterinarin medicina 12 B); e. prof. p. dr. Bronius Bakutis (Lietuvos veterinarijos akademija, biomedicinos mokslai, veterinarin medicina 12 B); prof. habil. dr. Romas Gruauskas (Lietuvos veterinarijos akademija, biomedicinos mokslai, zootechnika 13 B); prof. habil. dr. Vytautas Tarvydas (Lietuvos veterinarijos akademijos Gyvulininkyst s institutas, biomedicinos mokslai, zootechnika 13 B). Oponentai: doc. dr. Asta Klimien (iauli universitetas, biomedicinos mokslai, zootechnika 13 B); doc. dr. Eugenijus Aniulis (Lietuvos veterinarijos akademija, biomedicinos mokslai, veterinarin medicina 12 B). Disertacija bus ginama vieame Zootechnikos mokslo krypties tarybos pos dyje 2005 m. spalio m n. 28 d. 13 val. Lietuvos veterinarijos akademijos I auditorijoje. Adresas: Til s g. 18, LT- 47118 Kaunas, Lietuva. Disertacijos santrauka isiuntin ta 2005 m. rugs jo 26 d. pagal patvirtint ą adres s ą ra ą . Disertacij ą galima peri r ti Lietuvos veterinarijos akademijos bibliotekoje.
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Introduction General condition of economical efficiency of animal breeding is the rising requirements of milk productivity. The prerequisite to receive that purpose is the healthy animal capable repeatedly to receive high level of productivity and good quality of production and thus to get high results of reproduction. That tendency promotes to search for ways that precipitate progress of selection and of betterment of utility features of cattle. The gain of herd grows when grows milk productivity of cows, longevity of cows, and increases number of calves. High productivity, good rate of reproduction is essential for desirable longevity of cows. 5% of culled cows in Lithuania − cows, which culled owing to low productivity, 11.8% − cows, which culled owing to barrenness and illnesses of generative organs. Reproductive activity of the herd defines age of the cow at the first calving (AFC), days from calving to first semination (DFS), the number of days from calving to insemination (or days open, DO), number of seminations from calving to insemination (NS), calving interval (CI) et al. They are influenced by all series of genetic and non-genetic factors (Anderson et al., 1979; Brotherstone, 1987; Cady et al. 1978; Demesinov, 1989; Echternkamp ir Gregory, 1999; Gutbier, 2003; Jongeling, 2001; Knight, 2001; Miglior et al., 1989; Münnich, 2000; Oishi et al., 1985; Powell, 1985; Quintela et al., 2004; Streit, 1990; Voll, 1989; Зайцева , 2001; Исаева , 1998; Карамаев , 2001; Кертиев ir Лось , 1999; Лось , 2002; Прокофьев et al., 2002; Рыбалко , 1996; Яковлева , 1999; et al.). The aim of the present study. To make analysis of reproductive features and factors influencing these features in the black & white cattle population in Lithuania. Goals of the present study: 1. To make analysis of the reproductive features (DO, NS, CI, length of pregnancy (LP), results of calving) in the black & white cattle population in Lithuania. 2. To investigate influence of genetic and non-genetic factors on reproductive features. 3. To investigate influence of productivity of milk on reproductive features. 4. To investigate influence of reproductive features on productivity of milk. 5. To make correlation analysis and dispersion analysis of productivity and reproductive features. Novelty of the study. 1. First is made the exhausting analysis of reproductive features in the black & white cattle population in Lithuania. 2. First are investigated factors influencing reproductive features in the black & white cattle population in Lithuania. 3. Estimated relations of correlation between reproductive features and productivity . 5
Practical significance of the study. Influence of genetic and non-genetic factors on reproductive features in the black & white cattle population in Lithuania, correlation of reproductive features, and relations of reproductive features and productivity are investigated. In concordance with these results, in development breeding programs of the dairy cattle, it is necessary to add selection of reproductive features. Are corrected ranges of reproductive features which can be used when will be prepares data for an estimation of breeding values of the reproductive features of the black & white cattle population. Materials and methods The data about pedigree of black & white cows, calvings, inseminations, production records and the data about the percentage of genes Holsteins in the genotype of bulls were used. Data obtained from the Dairy Records Processing Center. The data of calvings, inseminations and productivity in 19962004 years are analyzed. Data base for research was prepared using Access. Were prepared data arrays of pedigree, reproductive performance and production of cows which were born at 1995 − 2002 years. Various grouping methods were used in biometrics analysis for an evaluation of influence of different factors. Biometrics data analysis was accomplished using R statistical package. The averages ( x ), standard errors of the means (m x ), standard deviation (SD) and coefficient of variation (Cv) of features were computed. Pearsons correlation coefficient were used for the estimate of phenotypic correlatations between features. Students criterion were used for the estimate of reliability of relations. Evaluation of reproductive features was carried out by using univariate and multivariate methods. Model 1 Y i = μ + L i + P + Rkg + Rpr + Bkg + Bpr + e i ; where: Y i − estimated influence on DO, CI, NS; μ − overall mean; L i − effect of i th lactation, P − effect of milk yield; Rkg − effect of yield of fat; Rpr − effect of fat content; Bkg − effect of yield of protein; Bpr − effect of protein content; e i − residual error. Model 2 Y i = μ + SPTa + SPTe + e i ; where: Y i − estimated influence on milk yield, yield of fat, fat content, yield of protein, protein content; μ − overall mean; SPTa − effect of previous lactations DO; SPTe − effect of current lactations DO; e i − residual error. Results and discussion Were used data of reproductive and productive features of 39588 cows. Cows were 7 breeds (Lithuanian black & white − 90.7 % ), 33 lines (Wis Ideal 933122 − 46.9%).
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Table 1. The statistical analysis of features 1 lentel . Poymi statistin analiz Feature n x ± m x Change, % Age at first calving (AFC) 29637 27.72 ± 0.02 -1.42 Number of services (NS) 30803 1.63 ± 0.01 -2.5 Days open (DO) 46094 109.65 ± 0.30 -12.14 Length of pregnancy (LP) 65263 281.62 ± 0.03 +0.21 Calving interval (CI) 56677 393.37 ± 0.28 -3.69 Influence of genetic and non-genetic factors on the age at first calving (AFC) Influence of breed. The most AFC were cows of British Friesian breed, the least AFC were cows of Danish black & white breed. Difference of AFC between these groups is 2.62 ± 0.01 month (P<0.001). Influence of line. The most AFC were offspring of Dutch black & white bulls, the least AFC were of cows of A. R. Sovereign 198998 line. Difference of AFC between these groups is 1.23 ± 0.00 month (P<0.001). Influence of percentage Holstein genes in the genotype (H % ). Cows, the fathers which have not been improved by Holstein genes, had greater AFC. Cows which fathers are Holstein bulls had the least AFC. Difference of AFC between these groups is 1.62 ± 0.00 month (P<0.001). Influence of year of calving. During period of research AFC has decreased. Cows who first time calving till 1999 had the greater AFC. Cows who first time calving at 2003 had the least AFC. Difference of AFC between these groups is 0.95 ± 0.00 month (P<0.001). Influence of season of calving. Cows who first time calving in autumn had the greater AFC. Cows who first time calving in spring had the least AFC. Difference of AFC between these groups is 1.32 ± 0.00 month (P<0.001). Influence of genetic and non-genetic factors on the days open (DO) Influence of breed. Danish black & white cows had the longest DO. Lithuanian black & white cows had the shortest DO. Difference of DO between these groups is 33.25 ± 4.44 days (P<0.001). Influence of line. Progenies of line of O. Ivanhoe had the longest DO. Progenies of line of V. Ernst 8294 had the shortest DO. Difference of DO between these groups is 15.61 ± 3.74 days (P<0.001). Influence of percentage Holstein genes in the genotype (H % ). Cows which fathers have not been improved by Holstein genes had the shortest DO. Cows which fathers have 37.550 % of genes Holstein had the longest DO. Difference of DO between these groups is 19.19 ± 2.06 days (P<0.001). Influence of AFC. Cows which AFC is 2932 months had the longest DO after 1 st calving. Cows which AFC is 2528 months had the shortest DO after 1 st calving. Difference of DO between these groups is 10.9 ± 0.02 days (P<0.001). If AFC is increase till 30 months, DO during successive lactations is decrease. 7
More (41.6 % ) often AFC − 2528 months. Cows which AFC is 2932 months had the longest mean DO. Cows which AFC is 2024 months had the shortest mean DO. Difference of DO between these groups is 11.36 ± 0.01 days (P<0.001). Influence of season of calving. More often cows are calving in spring (35.7%). If cows are calving in spring or in summer, DO is shortest than these calving in autumn or in winter. Difference of DO between these groups is 12.15 ± 0.86 days (P<0.001). Influence of lactation. The longest DO is after 1 st calving. The shortest DO is after 5 th calving and later. Difference of DO between these groups is 12.15 ± 0.86 days (P<0.001). Influence of result of calving. DO is longer after a stillbirth than after calving when is born alive calf. Difference of DO between these groups is 6.47 ± 1.49 days (P<0.001). DO is longer after calving when are born twins than when is born one calf. Difference of DO between these groups is 1.72 ± 2.28 days (P>0.05). DO is the longest after a stillbirth (115.85 ± 1.46 days). Influence of herds. The longest DO is in herds where hold 201-400 cows. The shortest DO is in herds where hold 21-50 cows. Difference of DO between these groups is 19.08 ± 1.4 days (P<0.001). Influence of genetic and non-genetic factors on the number of services (NS) Influence of breed. British Friesian cows had the most NS, Lithuanian black & white cows had the least NS. Difference of NS of these groups is 0.78 ± 0.16 time (P<0.001). Influence of line. Posterity of line Criscross 1378594 had the most NS; posterity of line V. Ernest 8294 had least NS. Difference of NS of these groups is 0.23 ± 0.07 time (P<0.001). Influence of H % . Cows which fathers had 50.062.5% of genes Holstein had the most NS, cows which fathers had 75.0100% of genes Holstein had the least NS. Difference of NS of these groups is 0.18 ± 0.04 time (P<0.001). Influence of AFC. Cows which AFC is 2936 months had the most NS after 1 st calving. Cows which AFC is 2024 months had the least NS after 1 st calving. Difference of NS between these groups is 0.13 ± 0.00 time (P<0.001). Cows which AFC is 2024 months had the least mean NS. Cows which AFC is 2932 months had the most average NS. Difference of NS between these groups is 0.19 ± 0.00 time (P<0.001). Influence of season of calving. Cows after calving in autumn had the most NS. Cows after calving in spring had the least NS. Difference of NS between these groups is 0.15 ± 0.01 time (P<0.001). Influence of lactation. Cows after second calving had the most NS. Cows after 5 th calving and later had the least NS. Difference of NS between these groups is 0.12 ± 0.01 time (P<0.001). Influence of result of calving. After calving when born lively calf NS is more than after a stillbirth is. Difference of NS between these groups is 0.04 ± 0.03 time (P<0.001). After calving when is born one calf NS is more than when are born 8
twins. Difference of NS between these groups is 0.02 ± 0.01 time (P>0.05). NS is the most after a stillbirth (1.67 ± 0.03 time). Influence of herds. The most NS is in herds where hold 11-20 cows. The least NS is in herds where hold more than 400 cows. Difference of NS between these groups is 0.62 ± 0.01 time (P<0.001). Influence of genetic and non-genetic factors on the calving interval (CI) Influence of breed. Danish black & white cows had the longest CI. Lithuanian black & white cows had the shortest CI. Difference of CI between these groups is 33.61 ± 4.34 days (P<0.001). Influence of line. Progenies of line of O. Ivanhoe 1189870 had the longest CI. Progenies of line of V. Ernst 8294 had the shortest CI. Difference of CI between these groups is 14.96 ± 3.51 days (P<0.001). Influence of percentage Holstein genes in the genotype (H % ). Cows which fathers have not been improved by Holstein genes had the shortest CI. Cows which fathers had 37.550% of genes Holstein had the longest CI. Difference of CI between these groups is 9.57 ± 1.95 days (P<0.001). Influence of AFC. Cows which AFC is 2932 months had the longest CI after 1 st calving. Cows which AFC is 2528 months had the shortest CI after 1 st calving. Difference of CI between these groups is 11.12 ± 0.02 days (P<0.001). Cows which AFC is 2932 months had the longest mean CI. Cows which AFC is 2024 months had the shortest mean CI. Difference of CI between these groups is 10.56 ± 0.01 days (P<0.001). Influence of season of calving. CI is the shortest than cows calving in spring. CI is the longest than cows calving in autumn. Difference of CI between these groups is 12.76 ± 0.83 days (P<0.001). Influence of lactation. The longest CI is after 1 st calving. The shortest CI is after 5 th calving and later. Difference of CI between these groups is 13.94 ± 1.05 days (P<0.001). Influence of result of calving. CI is shorter after calving when is born alive calf than after a stillbirth. Difference of CI between these groups is 5.11 ± 1.42 days (P<0.001). CI is longer after calving when are born twins than when is born one calf. Difference of CI between these groups is 2.87 ± 2.16 days (P>0.05). Influence of herds. The longest CI is in herds where hold 201-400 cows. The shortest CI is in herds where hold 1120 cows. Difference of CI between these groups is 15.23 ± 1.55 days (P<0.001). Influence of genetic and non-genetic factors on the length of pregnancy (LP) Influence of breed. Dutch black & white cows had the shortest LP. British Friesian cows had the longest LP. Difference of LP between these groups is 1.56 ± 0.75 days (P<0.001). Influence of line. Progenies of line of V. Ernst 8294 had the longest LP. Progenies of line of G. Criscross 1378594 had the shortest LP. Difference of LP between these groups is 1.68 ± 0.42 days (P<0.001). 9
Influence of percentage Holstein genes in the genotype (H % ). Cows which fathers had 50.062.5% of genes Holstein had the shortest LP. Cows which fathers had 75100% of genes Holstein had the longest LP. Difference of LP between these groups is 1.13 ± 0.12 days (P<0.001). Influence of AFC. Heifers which AFC is 3242 months had the longest LP. Heifers which AFC is 2024 months had the shortest LP. Difference of LP between these groups is 1.69 ± 0.15 days (P<0.001). Cows which AFC is 37-42 months had the longest mean LP. Cows which AFC is 2024 months had the shortest mean LP. Difference of LP between these groups is 0.49 ± 0.00 days (P<0.001). Influence of season of calving. LP is the shortest than cows calving in spring. LP is the longest than cows calving in autumn. Difference of LP between these groups is 0.18 ± 0.00 days (P<0.001). Influence of lactation. The shortest LP had heifers. The longest LP is at 5 th lactation and later. Difference of LP between these groups is 1.85 ± 0.09 days (P<0.001). Influence of result of calving. LP is shorter when born lively calf than a stillbirth is. Difference of LP between these groups is 0.61 ± 0.15 days (P<0.001). LP is longer when is born one calf than when are born twins. Difference of LP between these groups is 1.15 ± 0.19 days (P<0.001). Influence of herds. The longest LP is in herds where hold 201400 cows. The shortest LP is in herds where hold 610 cows. Difference of LP between these groups is 1.72 ± 0.19 days (P<0.001). Influence of genetic and non-genetic factors on the result of calving Influence of year. Annually the stillbirths and the twins are born more often. Till 1999 the stillbirths have made 3.38 % of all calvings, the twins − 0.78%. Yearly this part was growing and in 2004 of the stillbirths are 6.24%, of the twins − 3.49%. During period of research of the stillbirths was 5.44%, of the twins − 2%. Influence of breed. British Friesian cows bear a stillbirth and twins most frequently (9.05% and 3.14% accordingly). Swedish black & white cows bear twins most seldom (1.07%) but stillbirths most seldom bear Danish black & white cows (4.88%). Influence of line. Progenies of line of W. A. Burke Lad 697789 bear stillbirths most frequently (6.58%) but twins bear most frequently progenies of line of V. Ernst 8294 (3.24%). Progenies of line of G. Criscross 1378594 (3.47) bear stillbirths most seldom but twins bear most seldom progenies of line of Wis Ideal 933122 (1.77%). Influence of percentage Holstein genes in the genotype (H % ). Cows, the fathers which had 100% of genes Holstein bear stillbirths most frequently, most seldom − cows, the fathers which had 37.550.0% of genes Holstein. Cows, the fathers which had 75100% of genes Holstein bear twins most frequently, most seldom − cows, the fathers which had 50.062.5% of genes Holstein. Influence of AFC. Cows which AFC is 2024 months bear stillbirths most 10
frequently, most seldom − cows, which AFC is 2528 months. Cows which AFC is 3742 months bear twins most frequently, most seldom − cows which AFC is 3336 months. Influence of LP. Stillbirths are most frequently (7.47%) after longer LP (301310 days). Twins are most frequently (2.42%) after the shortest LP (270280 days). Influence of season of calving. Stillbirths are born most frequently in autumn (6.41%), most seldom − in summer (4.92%). Influence of lactation. Heifers bear stillbirths twice more often than cows. Heifers bear twins only 0.92% of all calving. Influence of productivity on features of reproduction The data of lactations was grouped conformity milk yield. When productivity is increase, DO, NS and CI are increase too. Average of DO of cows, milk yield which is 25004000 kg, is 102.72 days, and DO of cows, milk yield which is more than 10000 kg, is 149.72 days, CI is 385.34 days and 429.67 days respectively, NS is 1.56 and 2.48 respectively. Relative analysis of influence of different factors on features of reproduction Data of DO, CI and NS was grouped accordingly AFC, calving season, lactation, heard, milk yield. Deviations of those features from the average population have estimated (averages DO, CI and NS of population were equated to zero). Influences of age at first calving (AFC) on average features of reproduction (days open [DO], number of services [NS] and calving interval [CI]) and on features of reproduction after 1 st calving are different (figures 1 and 2). 8 6 4 Average of opulation 2 0 -2 -4 20-24 25-28 29-32 33-36 37-42 AFC DO NS CI Figure 1. Influences of AFC on features of reproduction after 1 st calving 1 paveikslas. Amiaus pirmojo veriavimosi metu taka karvi pirmos laktacijos reprodukciniams rodikliams The deviations of DO, CI and NS after 1 st calving cows, which AFC was 2932 months was the most (figure 1). Deviations were 6.4%, 1.9% and 4.2% (DO, CI 11
and NS respectively). 8 6 4 Average of 2 opulation 0 -2 -4 -6 20-24 25-28 29-32 33-36 37-42 AFC DO NS CI Figure 2. Influences of AFC on average features of reproduction 2 paveikslas. Amiaus pirmojo veriavimosi metu taka karvi vidutiniams reprodukciniams rodikliams The deviations of DO, CI and NS cows, which AFC was 2932 months was the most (figure 2). Deviations were 6.2%, 1.7% and 6% (DO, CI and NS respectively). J. F. Ettema and J. E. P. Santos (2004) showed that small AFC had negative influence on features of reproduction. They noted that the best AFC is 24 months. Influences of AFC on features of reproduction also showed scientists L. V. Isajeva (1998) and R. Kertijev and N. F. Los (1999). 10 8 6 Average of p op ulation 4 2 0 -2 -4 -6 Sp ring Summer Autumn Winter Season DO NS CI Figure 3. Influences of season of calving on features of reproduction 3 paveikslas. Veriavimosi sezono taka reprodukciniams rodikliams 12
After calving in autumn DO and CI was the longest (deviation from average population respectively 6.1% and 1.8%), NS was 9.8% more than the average population) (figure 3). That ours results similar with results of Shapiro J. O. and Pavlovskij V. V. (1999) what showed that after calving in autumn DO is 3.49% longest than average. Similar results had Rybalko V. A. (1996). Los N. F. (2002), Oberauskas D. et al. (2004) rated that DO and NS is the most in 1 st lactation. Influence of lactation on days open (DO), number of services (NS) and calving interval (CI) of black & white cattle population in Lithuania is shown in figure 4. 8 6 4 2 0 -2 -4 Average of population -6 -8 -10 1 2 3 4 5 et al. Lactation DO NS CI Figure 4. Influences of lactation on features of reproduction 4 paveikslas. Karv s amiaus (laktacijos) taka reprodukciniams rodikliams st DO, CI and NS are worst after 1 st calving. Later those features improve. After 1 calving NS, DO and CI was respectively 5.56%, 5.2% and 1.4% more than the average of population (figure 4). When the yield of milk is increase then the features of reproduction are worsening (Faust, 1989; Loeffler et al, 1999; Shapiro and Pavlovskij, 1999; Vanek, 2004). Influence of milk yield on days open (DO), number of services (NS) and calving interval (CI) shown in figure 5. Deteriorative reproduction features are conditioned by increscent milk yield (figure 5). Reproduction features of cows with low production (25004500 kg) are better than average of population. But reproduction features of cows which milk yield is 10000 kg and more, CI, DO and NS was respectively 9.2%, 36.5% and 52.1% more than the average of population.
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50 40 30 Average of population 20 10 0 -10
2500-4000 4001-5500 5501-7000 7001-8500 8501-10000 >10000 Yield of milk, kg DO NS CI Figure 5. Influences of milk yield on features of reproduction 5 paveikslas. Pieno kiekio per laktacija taka karvi reprodukciniams rodikliams Influence of the size (by number of cows) herd on days open (DO), number of services (NS) and calving interval (CI) shown in a figure 6. 20 15 10 Average of population 5 0 -5 -10 -15 -20 1-5 6-10 11-20 21-50 51-100 101-200 201-400 >400 Number of cows DO NS CI Figure 6. Influence of the size herd on features of reproduction 6 paveikslas. kio stambumo taka reprodukciniams rodikliams Deteriorative features of reproduction are conditioned by the increasing size of herd (figure 6). At herds where 200 and more cows, CI, DO and NS was respectively 2.6%, 10.5% and 4.9% more than the average of population.
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35 2,3 30 2,2 25 20 2,1 15 2,0 10 5 1,9 0 1,8 Spring Summer Aut umn Wint er Season of insemination All inseminations Successful inseminations Proportion All/Successfull Figure 7. Distribution of inseminations on a season 7 paveikslas. S klinim pasiskirstymas pagal s klinimo sezonus Even 34.0% of all inseminations are made in the summer, but if there are inseminations in the autumn or in the winter, the percent from successful inseminations is conditionally the biggest (figure 7). Annually the stillbirths and the twins are born more often (Hondele J., 1986; Streit P., 1990; Baars S., 2001). Results of our researches of influence of year of calving on results of calving are shown on a figure 8. 7 6 5 4 3 2 1 0 <1999 1999 2000 2001 >2001 Twins Stillbirth Year of calving Figure 8. Influence of year of calving on results of calving 8 paveikslas. Veriavimosi met taka atsivedam dvyni ir negyv vereli skai č iui 15
Till 1999 the stillbirths have made 3.38% of all calving, the twins − 0.78%. Yearly this part was growing and in 2004 of the stillbirths are 6.24%, of the twins − 3.49%. During period of research of the stillbirths was 5.44%, of the twins − 2% (figure 8). On studies of influence of season on results of calving the results of researches of different authors are discrepant (Nielen et al, 1989; Eddy et al, 1991; Kinsel et al, 1998). Distribution of results of calving on season of calving is shown on a figure 9. 40 7 35 6,415,81 6 30 4,954,92 5 25 4 20 15 2,04 2,31 04 3 2, 10 1,56 2 5 1 0 0 Spring Summer Autumn Winter Season of calving All calvings Twins Stillbirths Twins rate Stillbirths rate Figure 9. Distribution of results of calving on season of calving 9 paveikslas. Veriavim si danio pasiskirstymas pagal veriavimosi sezon ą Cows are calving more often in the spring (34.7%). More seldom cows are calving in autumn 19.8% (of the twins in autumn only 15.2%, of the stillbirths are 23.4%). Least of the stillbirths are in summer (21.9%). In autimn twins rate is least (1.6%), stillbirths rate is the most (6.41%). The calvings of the heifers are frequently difficult therefore the heifers reproduce stillbirths more often (Streit P., 1990; Jahnke B., 2004). The heifers drop stillbirths twice often (7.8%) than adult cows (figure 10). The heifers of twins reproduce less than 1%. Nielen M. et al (1989), Eddy R. G. et al (1991), Peeler E. J. et al (1994), Kinsel M. L. (1998) presented the identical results.
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8 7 6 5 4 3 2 1 0 1 2 3 4 5 et al. Lactation Twins Stillbirths Figure 10. Influence of lactation on results of calvings 10 paveikslas. Laktacijos taka atsivedam dvyni ir negyv vereli skai č iui Influence of features of reproduction on productivity of milk Influence of DO on productivity of milk. The data of lactations we grouped by DO. More often DO is 57112 days (43.6%), but the best for productivity of milk − 169224 days. Difference of productivity of milk between these groups is 215.4 ± 23.01 kg of milk, 8.13 ± 1.08 kg of fat and 5.54 ± 0.80 kg of protein (P<0.001). Influence of CI on productivity. More often CI is 351400 days (35.2%). The best CI for milk yield is 450500 days. Difference of milk yield between these groups is 153.15 ± 21.43 kg. The best CI for yield of fat and for yield of protein is 401 450 days. Differences of yield of fat and yield of protein between these groups are 5.79 ± 0.78 kg and 3.74 ± 0.57 kg (of fat and of protein respectively, P<0.001). Influence of LP on productivity. More often LP is 270280 days (48.2%). The prolonged LP (more than 300 days) happens seldom (only 2.1%). The best productivity of milk is when LP is 281290 days. Influence of results of calving on productivity. Productivity is better when born live calf than after a stillbirth. Difference of productivity between these groups is 151.24 ± 23.82 kg of milk, 6.73±1.1 kg of fat and 3.7±0.82 kg of protein (P<0.001). Productivity is better after twins than when is born one calf. Difference of productivity between these groups is 453.56 ± 40.18 kg of milk, 15.97±1.8 kg of fat and 17.5±1.39 kg of protein (P<0.001). If cows though once have given the twins, their productivity is better than of cows which have never given the twins. Difference of productivity between these groups is 174.14 ± 19.5 kg of milk, 7.13±0.9 kg of fat and 17.5±0.68 kg of protein (P<0.001). 17
The dispersive and correlation analysis of features of reproduction and productivity Coefficients of phenotypic correlation: between milk yield and DO, and between milk yield and CI is 0.12 (P<0.001); between yield of fat and CI and between yield of protein and CI is 0.10 (P<0.001). Correlation between DO at last lactation and DO at current lactation is small (r=0.16, P<0.001). Correlation between LP at last lactation and LP at current lactation is small too (r=0.14, P<0.001). Relation of correlation between CI and DO is very tough (r=0.995). It shown, that various factors influence both features equally. Moreover, coefficients of correlation between NS and DO and between NS and CI are 0.56. These propositions confirm one another. Correlation between DFS and DO and between DFS and CI is tough (r=0.71, P<0.001); correlation between DFS and NS is negative and small (r=-0.09, P<0.001). Table 2. Influences of various factors on features of reproduction 2 lentel . vairi veiksni taka reprodukcin ms savyb ms Feature DO NS CI Factor One-factor analysis 1.1 *** 0.28 *** 0.53 *** Breed Line 0.2 *** 0.31 *** 0.21 *** Father 2.5 *** 4.22 *** 2.44 *** H% of father 0.1 *** 0.34 *** 0.09 ** AFC 0.8 *** 0.61 *** 0.79 *** Season of calving 0.35 *** 0.27 *** 0.35 *** Herd 4.8 *** 9.64 *** 4.63 *** Multi-factorial analysis Lactation 0.84 *** 0.22 *** 0.73 *** Milk kg 2.15 *** 1.2 *** 2.21 *** Fat kg 0 ¬ 0.1 *** 0 ¬ * Fat% 0.02 0.04 ** 0.02 * Protein kg 0.36 *** 0.04 ** 0.39 *** Protein% 0.03 * 0 ¬ 0.03 * Total influence 3.4 *** 1.6 *** 3.39 *** *** − P<0.001; ** − P<0.005; * − P<0.05; ¬ − P>0.05 Results of analysis show that the biggest influences on features of reproduction had herd (4.8%, 9.64% and 4.63% on DO, NS and CI respectively, P<0.001) and father (2.5%, 4.22% and 2.44% on DO, NS and CI respectively, P<0.001). Influences of all factors were significant. The total regression of productivity on DO and CI was the biggest (3.4% and 3.39%, P<0.001). The total regression of productivity on NS was something less (1.6%). The biggest regression on features of reproduction was of milk yield (2.15%, 2.21% and 1.2% on DO, CI and NS respectively). 18
The results of the dispersive analysis of influence of features of reproduction on productivity are shown in table 3. Table 3. Influences of features of reproduction on productivity 3 lentel . Reprodukcini poymi taka produktyvumo rodikliams Feature Milk, Fat, Fat, Protein, Protein, kg kg % kg % Factor Regression of: DO at least lactation 1.0 *** 1.0 *** 0.04 *** 0.5 *** 0.9 *** DO at current 1.5 *** 1.0 *** 0.04 *** 0.9 *** 0.5 *** lactation total 2.8 *** 2.1 *** 0.08 *** 1.9 *** 1.0 *** * *** CI 1.5 *** 1.0 *** 0.05 ** 0.9 *** 0.6 Influence of: vitality of calf 0.1 *** 0.06 *** 0.01 *** 0.04 *** 0.18 *** multi-foetus 0.21 *** 0.12 *** 0 ¬ 0.26 *** 0.08 *** *** − P<0.001; ¬ − P>0.05 Influence of DO on productivity was significant (P<0.001) and ranged from 0.08% (on fat content) to 2.8% (on milk yield). Influence of CI on productivity was significant too (P<0.001) and ranged from 0.05% (on fat content) to 1.5% (on milk yield). Influence of vitality of calf on productivity ranged from 0.01% (on fat contents) to 0.18% (on protein contents, P<0.001). Influence of multi-foetus on the productivity ranged from 0% (on fat contents, P>0.05) to 0.26% (on protein contents, P<0.001). Conclusions 1. During the period of research the age of cows at the first birth of a cub of the black-and-white population in Lithuania has decreased 1.42 %, the open days have decreased 12.14 %, the number of services in the concept has decreased 2.5 %, the calving interval has decreased 3.69 %, the length of pregnancy has increased for 0.21 % (P<0.001). Average of rate of stillbirths is 5.44%; average of rate of twins is 2.0%. 2. Breed influence on the age of cows at first calving most of all, year of calving − the least of all. Breed influence on the days open and on the calving interval most of all, percentage Holstein genes in the genotype − the least of all. Breed influence on the number of services per conception most of all, the lactation − the least of all. Herd influence on the length of pregnancy of cows most of all, age of first calving − the least of all. Breed influence the vitality of calf most of all, age of first calving − the least of all. Lactation influences the multi-foetus most of all with, age of first calving − the least of all. 3. When productivity of cows increases, days open, calving interval and number of services per conception increases also (P<0.001). 4. Coefficients of phenotypic correlation between features of reproduction ranged from 0.16 (between days open at last lactation and days open at 19
current lactation, P<0.001) to 0.995 (between calving interval and days open, P<0.001). Coefficients of phenotypic correlation between features of reproduction and productivity ranged from 0.10 (between calving interval and yield of protein, P<0.001) to 0.12 (between milk yield and days open and between milk yield and calving interval, P<0.001). 5. The influence of the herd on reproductive features is the biggest (from 4.63% on calving interval to 9.64% on number of services per conception, P<0.001). The influence of the percentage Holstein genes in the genotype on reproductive features is the least (from 0.09% on calving interval to 0.34% on number of services per conception, P<0.001). The regression of milk yield on reproductive features is the biggest (from 1.2% on number of services per conception to 2.21% on caving interval, P<0.001). The regression of fat contents on reproductive features is the least (from 0.02% on days open and caving interval to 0.04% on number of services per conception, P<0.005). Proposals 1. To reduce the losses of herd for impairment of reproductive function of cows, recommended: • To implement selection on reproductive features of black & white cattle. • To select the time of insemination subject to productivity; if milk yield is 7500 kg and more, to inseminate 110150 days after calving and later. • If born twins or stillbirth, inseminate 100120 days after calving and later. 2. To introduce the estimate of reproductive features of cattles, necessary to collect data of all inseminations and data of easy of calving. 3. For estimate, to escape distortion of data of population, recommended range of days open 21 − 250 days, range of calving interval 291 − 550 days. List of publications Paskelbt straipsni s ą raas 1. Petrakien R., Miceikien I. Holteinizacijos taka juodmargi buli veislinei vertei. Veterinarija ir zootechnika. Kaunas, 2004. T.25(47). P. 76-79. 2. I. Miceikien , N. Pe č iulaitien , R. Petrakien . Milk protein genotypes and their association with milk composition traits in the Lithuanian dairy cattle. Medycyna Weterynaryjna Lublin, Poland. 2005, 61(4). P. 394-397. 3. Petrakien R., Miceikien I. Lietuvoje veisiam juodmargi galvij servis periodo trukm s ir j ą veikian č i faktori analiz . Veterinarija ir zootechnika. Kaunas, 2005. T.31(53) Veterinarija ir zootechnika. Kaunas, 2005. T.31(53). . P.8386 Other publications Kitos publikacijos 1. Miceikiene I., Krasnopiorova N., Petraskiene R. Ex-situ and in-situ conservation of Lithuanian domestic animal genetic resources − lessons from past and future perspectives. // Proceedings of Farm animal reproduction: Conserving local genetic resources. Uppsala, 2003. P. 8-11. 20
2. Pe č iulaitien N., Petrakien R., Miceikien I. Associations between milk protein genotypes and milk composition traits in the Lithuanian dairy cattle. // Proceedings of X Baltic Animal Breeding Conference, Estonia, Tartu, 2004, 13-14 th May. P. 86-90. 3. Petraskiene R., Miceikiene I., Paleckaitis M. Influence of bulls age on its breeding value and daughters productivity. // Proceedings of the 11 th Baltic Animal Breeding and Genetics Conference, Palanga, Lihuania, 13-14 th May 2005. P. 31-34. Other editions Kiti leidiniai 1. Juozaitien V., Kardiauskas A., Tarasevi č ius S., Petrakien R. ir kt. Lietuvos juodmargi galvij selekcijos programa 20022005 metams. Marijampol , 2002. 32 p. 2. Juozaitien V., Vyniauskien O., Japertien R., Petrakien R. ir kt. Lietuvos juodmargi galvij genealogija. Marijampol , 2002. 66 p. Rezium io darbo tikslas − atlikti Lietuvoje veisiam juodmargi galvij populiacijos reprodukcini savybi ir jas takojan č i veiksni analiz ę . iam tikslui pasiekti buvo ikelti sekantys udaviniai: 1. Atlikti Lietuvoje veisiam juodmargi galvij populiacijos reprodukcini savybi analiz ę . 2. Itirti genetini ir negenetini veiksni tak ą reprodukcin ms savyb ms. 3. Itirti produktyvumo rodikli tak ą reprodukcin ms savyb ms. 4. Itirti reprodukcini savybi tak ą produktyvumo rodikliams. 5. Atlikti koreliacin ę ir dispersin ę reprodukcini ir produktyvumo poymi analiz ę . Tyrimui naudoti juodmargi galvij , veisiam Lietuvoje, kilm s, veriavimosi, s klinimo, produktyvumo duomenys bei duomenys apie gerinan č i veisli gen dal buli genotipe. Duomenys apie karvi kilm ę , s klinimus, veriavim ą si ir produktyvum ą gauti i V IKVC. Duomenims buvo taikomos login s ribos: karv s, gimusios 1995.01.01 − 2002.12.31; aius pirmojo veriavimosi metu 20 − 42 m n.; vringumo trukm 270 − 310 dien ; servis periodo trukm 18340 dien ; laikotarpis tarp veriavim si 288650 dien ; produktyvumas laktacij , kuri trukm 240305 dienos, pieno kiekis per laktacij ą − ne maiau 2500 kg. Analizuoti 1996 − 2004 met veriavimosi, s klinimo, produktyvumo duomenys. Duomen baz paruota naudojant Access duomen bazi valdymo sistem ą . Suformuoti kilm s, s klinimo, veriavimosi ir produktyvumo duomen masyvai. vairavimo statistikai ireikti skai č iavome reprodukcijos ir produktyvumo rodikli , sukaupt tyrim baz je, vidutines reikmes ( x ), aritmetini vidurki paklaidas (m x ), vidutinius kvadratinius nuokrypius (SD) ir vairavimo koeficientus (Cv) visai populiacijai ir grupuojant duomenis pagal genetinius ir negenetinius veiksnius. Dviej grupi aritmetinio vidurkio skirtumo patikimumui nustatyti buvo naudojamas Stjudento (t) kriterijus. 21
Koreliacin s analiz s metodu ityr me reprodukcini poymi fenotipinius tarpusavio ryius ir ryius su produktyvumo poymiais. Ryiui tarp poymi nustatyti buvo taikomas Pearson`o koreliacijos koeficientas (Snedecor, 1989). Genetini ir negenetini veiksni taka buvo apskai č iuojama dispersin s analiz s metodu (ANOVA), naudojant statistin paket ą R (Lorenz, 1996; Gentlemen and Ihaka, 1997), vertinant kiekvieno veiksnio takos poymi kintamumui dal procentais ir statistin patikimum ą (P). Dispersin analiz buvo atliekama keliais etapais. Pirmajame etape buvo atlikti genetini veiksni tyrimai ir nustatyta j taka reprodukciniams poymiams. Antrajame etape buvo atlikti negenetini veiksni tyrimai ir nustatyta j taka reprodukciniams poymiams. Tre č iame etape nustatyta produktyvumo rodikli taka reprodukcin ms savyb ms. Ketvirtajame etape ityr me reprodukcini poymi tak ą produktyvumo rodikliams. Penktajame etape nustat me koreliacinius ryius tarp poymi ir veiksni takos reprodukcin ms savyb ms ir produktyvumo rodikliams dal bendroje dispersijoje. Tyrimams atrinkta 39588 karvi kilm s, s klinimo, veriavimosi ir produktyvumo duomenys. Karv s priklaus 7 veisl ms (90,7 % sudar Lietuvos juodmargi veisl s karv s), 33 linijoms (46,9 % priklaus Wis Ideal 933122 linijai). 71,9 % karvi t vai buvo buliai, kuri genotipe Holtein veisl s gen dalis − 75100 %. 59,1 % tyrimams atrinkt karvi laikoma stambiuose (100 ir daugiau karvi ) kiuose. Didinant karvi ami pirmojo veriavimosi metu iki 32 m n., vidutin t karvi servis periodo trukm , laikotarpis tarp veriavim si ir s klinimo indeksas po pirmojo veriavimosi did ja. Toliau didinant ami pirmojo veriavimosi metu, vidutin t karvi servis periodo trukm , laikotarpis tarp veriavim si ir s klinimo indeksas turi tendencij ą ma ti. Karvi , kurios pirm ą kart ą veriavosi b damos 2932 m n. amiaus, vidutin s servis periodo, laikotarpio tarp veriavim si ir vidutinio s klinimo indekso nuokrypis nuo populiacijos vidurkio sudaro atitinkamai 6,2 %, 1,7 % ir 6,0 %. Didiausias pirmos laktacijos servis periodo, laikotarpio tarp veriavim si ir s klinimo indekso po pirmojo veriavimosi nuokrypis nuo populiacijos vidurkio yra t karvi , kurios pirm ą kart ą veriavosi b damos 2932 m n. Nuokrypis nuo populiacijos vidurkio sudaro 6,4 % , 1,9 % ir 4,2 % (servis periodo trukm s, laikotarpis tarp veriavim si ir s klinimo indekso atitinkamai). Ilgiausia servis periodo trukm ir laikotarpis iki sekan č io veriavimosi bei didiausias s klinimo indeksas yra po rudenini veriavim si, geriausi reprodukciniai rodikliai − po pavasarini veriavim si. Po rudenini veriavim si servis periodo trukm bei laikotarpis iki sekan č io veriavimosi buvo atitinkamai 6,1 % ir 1,79 % ilgesni nei populiacijos vidurkis, s klinimo indeksas po rudenini veriavim si buvo 9,82 % didesnis nei populiacijos vidurkis. S klinimo indeksas po pirmojo veriavimosi 5,5 % didesnis nei populiacijos vidurkis, servis periodo trukm ir laikotarpis tarp veriavim si po pirmojo veriavimosi atitinkamai 5,2 % ir 1,39 % ilgesni nei populiacijos vidurkis. Did jant laktacijai, servis periodo trukm ir laikotarpis iki sekan č io veriavimosi tendencingai trump ja, s klinimo indeksas did ja. 22
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