2. Materials and Methods
2.1. Study Design and Data Collection
This review was conducted to evaluate the reproductive performance of crossbred dairy cattle, specifically focusing on Jersey cross, 50% HF cross, and 75% HF cross genotypes in Ethiopia. Data were collected from both published and unpublished sources, including research articles, technical reports, and institutional records. A total of 156 reproductive performance records of crossbred dairy cattle were compiled, covering key reproductive trait such Age at first services (AFS), Age at first calving (AFC), calving interval (CI), Days open (DO) and Number of service per conception (NSPC). The data spanned various agro-ecological zones and management systems to ensure representativeness.
2.2. Data Analysis
The collected data were analyzed using statistical software SAS (version 9.0). Descriptive statistics, including means and standard deviations, were calculated for each reproductive trait. The effect of genetic group (Jersey cross, 50% HF cross, and 75% HF cross) on reproductive performance was assessed using one-way analysis of variance (ANOVA). Phenotypic correlations among reproductive traits (AFS, AFC, CI, DO and NSPC) were also computed to understand the relationships between these traits and their potential implications for selection and breeding programs.
2.3. Variables and Measurements
The reproductive traits evaluated in this study were defined as follows:
Age at first service (AFS): The age at which a heifer first receives artificial insemination or mates.
Age at first calving (AFC): The age at which a cow gives birth for the first time.
Calving Interval (CI): The time between two successive calving’s.
Days open (DO): The number of days between calving and successful conception.
And Number of services per conception (NSC): The average number of inseminations or mating required for a cow to conceive.
2.4. Statistical Models
Statistical Model for Analysis of reproductive traits
Where:
Yin = AFS, AFC, CI, DO and NSC trait of ith Animal group
μ = overall mean
Yi = the effect of ith Animal group (I = Jersey cross, 50% HF cross and 75% HF cross)
Ein = random error associated with each observation
3. Results and Discussion
3.1. Age at First Service (AFS)
The variability in the age at first service (AFS) among different genetic groups of crossbred cows, including Jersey cross, 50% HF, and 75% HF. The overall mean AFS of 30.68 ± 4.76 months with a coefficient of variation (CV) of 15.51% indicates moderate variability across the studied populations. This finding aligns with previous studies by
[8] | Wassie, T., Taye, M., & Dessie, T. (2015). Reproductive performance of indigenous and crossbred dairy cows in selected districts of Eastern Amhara Region, Ethiopia. Journal of Reproduction and Infertility, 6(2), 35-40. |
[9] | Wubshet, K. W. (2018). Estimation of Genetic and Non-Genetic Parameters for Reproductive and Productive Traits of Holstein Friesian Dairy Cows at Holeta Bull Dam Station. [Master's thesis, Haramaya University]. |
[8, 9]
, who reported similar AFS values for HF x Boran and 93.75% HF crossbred cows, respectively. However, the AFS in this review is longer than the 18.96 months reported by
[10] | Sena, L., Ayalew, W., & Hegde, B. P. (2014). Reproductive performance of HF x Fogera crossbred dairy cows under farmer’s management in North Western Ethiopia. Journal of Animal and Veterinary Advances, 13(6), 419-423. |
[10]
for HF x Fogera crossbred cows on farms, but shorter than the 40.9 ± 0.33 months reported by
[11] | Berhanu, B., Aynalem, H., & Mesfin, R. (2011). Productive and reproductive performance of Holstein-Friesian cows un-der farmer’s management in Hossana Town, Ethiopia. Ethiopian Journal of Animal Production, 11(1), 67-82. |
[11]
for HF x Boran crossbred cows on-station. These discrepancies may be attributed to differences in management practices, genetic composition, and environmental conditions.
The lack of a significant effect (p > 0.05) of genetic group on AFS suggests that factors other than genetics, such as management, nutrition, and production systems, play a more critical role in determining the age at which heifers are first serviced. This is consistent with findings by
[12] | Dessalegn, T., Mekasha, Y., & Tegegne, A. (2016). Effect of management practices on pre-pubertal growth and attain-ment of puberty in crossbred dairy heifers in urban dairy production systems, Ethiopia. Tropical Animal Health and Pro-duction, 48(3), 545-550. |
[12]
, who emphasized that poor feeding and low management levels during early stages of life can delay growth and puberty, leading to an extended AFS. Similarly,
[13] | Kefale, A. (2018). Reproductive performance of 50% F3 Friesian crossbred dairy cows at Holetta Agricultural Research Center, Ethiopia. Livestock Research for Rural Development, 30(9), 138. |
[13]
highlighted the importance of optimizing breeding seasons to coincide with periods of high forage quality and quantity, which can promote early service and improve reproductive efficiency.
Recent studies further support the idea that management and nutritional interventions are key to reducing AFS. For instance,
[14] | Tadesse, M., Thiengtham, J., Pinyopummin, A., & Prasanpanich, S. (2020). Impact of improved feeding management on milk yield and reproductive performance of smallholder dairy cows in Ethiopia. Tropical Animal Health and Production, 52(2), 789-795. |
[14]
found that improved feeding strategies and health management significantly reduced AFS in smallholder dairy systems. Additionally
[1] | Mekonnen, G., Moges, N., & Melaku, A. (2021). Effects of intensive management on growth performance and age at first service of crossbred dairy heifers in central Ethiopia. Heliyon, 7(3), e06489. |
[1]
reported that crossbred heifers reared under intensive management systems achieved earlier AFS compared to those under traditional systems, underscoring the importance of targeted interventions.
In conclusion, while genetic factors may contribute to some variation in AFS, the primary drivers appear to be management practices, nutritional status, and production systems. Addressing these factors through improved feeding, health management, and strategic breeding practices can help achieve earlier AFS, thereby enhancing reproductive performance and overall productivity in crossbred dairy cows.
3.2. Age at First Calving (AFC)
The results reveal significant variability in the age at first calving (AFC) among crossbred cows, including Jersey cross, 50% HF, and 75% HF genetic groups. The overall mean AFC of 40.99 ± 4.95 months, with a coefficient of variation (CV) of 12.08%, indicates moderate variability across the studied populations. This finding is consistent with earlier studies by
[15] | Million, T., Tadelle, D., & Alemu, Y. (2006). Reproductive performance of 75% Holstein Friesian crossbred cows at Holetta Agricultural Research Center. Ethiopian Journal of Animal Production, 6(1), 33-48. |
[15]
and
[16] | Haile, A., Joshi, B. K., Ayalew, W., Tegegne, A., & Singh, A. (2009). Genetic evaluation of Ethiopian Boran cattle and their crosses with Holstein Friesian in central Ethiopia: Age at first calving and calving interval. Journal of Agricultural Science, 147(6), 689-699. |
[16]
, who reported similar AFC values for 75% HF x local (F2) and 75% HF crossbred cows, respectively. However, the AFC in this review is lower than values reported by
[17] | Wondossen, A., Banerjee, S., & Lakew, M. (2018). Reproductive performance of Jersey × Gumez and Holstein Friesian × Gumez crossbred dairy cows under smallholder farmers’ management in North Western Ethiopia. International Journal of Livestock Production, 9(5), 113-119. |
[18] | Kefena, E., Tegegne, A., & Peters, K. J. (2006). Reproductive performance of F1 and F2 crossbred dairy cows in Eastern Ethiopia. Ethiopian Journal of Animal Production, 6(1), 37-52. |
[19] | Tadesse, M. (2014). Reproductive and productive performance of 75% Holstein Friesian crossbred dairy cows at Alage Agricultural Technical Vocational Education and Training College, Ethiopia. International Journal of Livestock Produc-tion, 5(9), 154-160. |
[17-19]
, and
[13] | Kefale, A. (2018). Reproductive performance of 50% F3 Friesian crossbred dairy cows at Holetta Agricultural Research Center, Ethiopia. Livestock Research for Rural Development, 30(9), 138. |
[13]
, who observed longer AFCs for Jersey x GH, F2 Friesian, and 75% HF x Borena crossbred cows. Conversely, the AFC in this review is longer than findings by
[20] | Enyew, N., Brannang, E., Rottmann, O. J., & Aster, A. (1998). Reproductive performance of dairy cattle at Asella Live-stock Farm, Arsi, Ethiopia. Ethiopian Journal of Agricultural Sciences, 16(1-2), 53-66. |
[10] | Sena, L., Ayalew, W., & Hegde, B. P. (2014). Reproductive performance of HF x Fogera crossbred dairy cows under farmer’s management in North Western Ethiopia. Journal of Animal and Veterinary Advances, 13(6), 419-423. |
[20, 10]
, and
[21] | Melku, M. (2016). Reproductive performance of 75% Holstein Friesian crossbred dairy cows under smallholder farmers’ management in Gondar, Ethiopia. Journal of Biology, Agriculture and Healthcare, 6(9), 82-87. |
[21]
, who reported shorter AFCs for 50% Jersey x Arsi, HF x Fogera, and 75% HF x local crossbred cows.
The lack of a significant effect (p > 0.05) of genetic group on AFC suggests that non-genetic factors, such as feeding management, heat detection, timely insemination, health control, and climate, play a more critical role in determining AFC. This aligns with
[22] | Kelay, B. (2002). Analysis of dairy cattle breeding practices in selected areas of Ethiopia. [Master's thesis, Alemaya Uni-versity]. |
[22]
, who emphasized that AFC is influenced by nutrition, year and month of birth, and rearing intensity. Similarly,
[12] | Dessalegn, T., Mekasha, Y., & Tegegne, A. (2016). Effect of management practices on pre-pubertal growth and attain-ment of puberty in crossbred dairy heifers in urban dairy production systems, Ethiopia. Tropical Animal Health and Pro-duction, 48(3), 545-550. |
[12]
highlighted that poor feeding and management during early life stages can delay growth and puberty, leading to extended AFC.
Recent studies further support the importance of management and nutritional interventions in reducing AFC. For instance
[1] | Mekonnen, G., Moges, N., & Melaku, A. (2021). Effects of intensive management on growth performance and age at first service of crossbred dairy heifers in central Ethiopia. Heliyon, 7(3), e06489. |
[1]
found that crossbred heifers under intensive management systems achieved earlier AFC compared to those under traditional systems.
[14] | Tadesse, M., Thiengtham, J., Pinyopummin, A., & Prasanpanich, S. (2020). Impact of improved feeding management on milk yield and reproductive performance of smallholder dairy cows in Ethiopia. Tropical Animal Health and Production, 52(2), 789-795. |
[14]
also reported that improved feeding strategies and health management significantly reduced AFC in smallholder dairy systems. These findings underscore the need for targeted interventions to optimize heifer rearing practices and improve reproductive efficiency.
In conclusion, while genetic factors may contribute to some variation in AFC, the primary drivers appear to be management practices, nutritional status, and environmental conditions. Addressing these factors through improved feeding, health management, and strategic breeding practices can help achieve earlier AFC, thereby enhancing reproductive performance and overall productivity in crossbred dairy cows.
3.3. Calving Interval (CI)
The results highlight the variability in calving intervals (CI) among crossbred cows, including Jersey cross, 50% HF, and 75% HF genetic groups. The overall mean CI of 456.93 ± 49.16 days is significantly longer than the ideal CI of 365 days, which is considered optimal for dairy cattle to maximize milk production and reproductive efficiency
[23] | Bourchier, C. P. (1981). The inter-relationships between yield, fertility and calving interval in high yielding dairy cattle. Animal Production, 32(2), 394-398. |
[23]
. This result aligns with findings by
[19] | Tadesse, M. (2014). Reproductive and productive performance of 75% Holstein Friesian crossbred dairy cows at Alage Agricultural Technical Vocational Education and Training College, Ethiopia. International Journal of Livestock Produc-tion, 5(9), 154-160. |
[15] | Million, T., Tadelle, D., & Alemu, Y. (2006). Reproductive performance of 75% Holstein Friesian crossbred cows at Holetta Agricultural Research Center. Ethiopian Journal of Animal Production, 6(1), 33-48. |
[19, 15]
, who reported similar CIs for 50% HF x local (F3) and 50% F2 Friesian crossbred cows, respectively. However, the CI in this review is shorter than values reported
[17] | Wondossen, A., Banerjee, S., & Lakew, M. (2018). Reproductive performance of Jersey × Gumez and Holstein Friesian × Gumez crossbred dairy cows under smallholder farmers’ management in North Western Ethiopia. International Journal of Livestock Production, 9(5), 113-119. |
[18] | Kefena, E., Tegegne, A., & Peters, K. J. (2006). Reproductive performance of F1 and F2 crossbred dairy cows in Eastern Ethiopia. Ethiopian Journal of Animal Production, 6(1), 37-52. |
[17, 18]
, and
[13] | Kefale, A. (2018). Reproductive performance of 50% F3 Friesian crossbred dairy cows at Holetta Agricultural Research Center, Ethiopia. Livestock Research for Rural Development, 30(9), 138. |
[13]
for Jersey x GH, F2 Friesian, and 50% F2 Friesian crossbred cows, but longer than the 351.2 ± 10.9 days reported by
[20] | Enyew, N., Brannang, E., Rottmann, O. J., & Aster, A. (1998). Reproductive performance of dairy cattle at Asella Live-stock Farm, Arsi, Ethiopia. Ethiopian Journal of Agricultural Sciences, 16(1-2), 53-66. |
[20]
for 50% Jersey x Arsi (F1) crossbred cows.
The lack of a significant effect (p > 0.05) of genetic group on CI suggests that non-genetic factors, such as management practices, environmental conditions, and geographical location, play a more critical role in determining CI. This is consistent with
[12] | Dessalegn, T., Mekasha, Y., & Tegegne, A. (2016). Effect of management practices on pre-pubertal growth and attain-ment of puberty in crossbred dairy heifers in urban dairy production systems, Ethiopia. Tropical Animal Health and Pro-duction, 48(3), 545-550. |
[12]
and
[13] | Kefale, A. (2018). Reproductive performance of 50% F3 Friesian crossbred dairy cows at Holetta Agricultural Research Center, Ethiopia. Livestock Research for Rural Development, 30(9), 138. |
[13]
, who emphasized that poor management practices, heat detection, and environmental stressors can delay the return to estrus and conception, leading to extended CIs. Additionally,
[24] | Arbel, R., Bigun, Y., Ezra, E., Sturman, H., & Hojman, D. (2001). The effect of extended calving intervals in high lactat-ing cows on milk production and profitability. Journal of Dairy Science, 84(3), 600-608. |
[24]
highlighted that CI is a crucial index of reproductive performance, as it directly impacts total milk production and the number of calves born.
Recent studies further support the importance of management and environmental factors in optimizing CI. For instance,
[1] | Mekonnen, G., Moges, N., & Melaku, A. (2021). Effects of intensive management on growth performance and age at first service of crossbred dairy heifers in central Ethiopia. Heliyon, 7(3), e06489. |
[1]
found that improved feeding strategies, health management, and timely heat detection significantly reduced CI in smallholder dairy systems. Similarly,
[14] | Tadesse, M., Thiengtham, J., Pinyopummin, A., & Prasanpanich, S. (2020). Impact of improved feeding management on milk yield and reproductive performance of smallholder dairy cows in Ethiopia. Tropical Animal Health and Production, 52(2), 789-795. |
[14]
reported that crossbred cows under intensive management systems achieved shorter CIs compared to those under traditional systems, underscoring the need for targeted interventions to improve reproductive efficiency.
In conclusion, while genetic factors may contribute to some variation in CI, the primary drivers appear to be management practices, environmental conditions, and geographical location. Addressing these factors through improved feeding, health management, and strategic breeding practices can help achieve shorter CIs, thereby enhancing reproductive performance and overall productivity in crossbred dairy cows.
3.4. Days Open (DO)
The results reveal significant variability in days open (DO) among crossbred cows, including Jersey cross, 50% HF, and 75% HF genetic groups. The overall mean DO of 147.40 ± 43.74 days indicates considerable variability across the studied populations. This result is slightly lower than the findings of
[13] | Kefale, A. (2018). Reproductive performance of 50% F3 Friesian crossbred dairy cows at Holetta Agricultural Research Center, Ethiopia. Livestock Research for Rural Development, 30(9), 138. |
[13]
, who reported longer DOs for 75% F1 Friesian and 50% F2 Friesian crossbred cows at Holetta Research Center. However, the DO in this review is higher than values reported by
[20] | Enyew, N., Brannang, E., Rottmann, O. J., & Aster, A. (1998). Reproductive performance of dairy cattle at Asella Live-stock Farm, Arsi, Ethiopia. Ethiopian Journal of Agricultural Sciences, 16(1-2), 53-66. |
[20]
and
[25] | Butler, W. R. (2003). Energy balance relationships with follicular development, ovulation and fertility in postpartum dairy cows. Livestock Production Science, 83(2-3), 211-218. |
[25]
for 50% Jersey x Arsi (F1), 50% Friesian x Arsi (F1), and Jersey x Horro crossbred cows, respectively. The minimum and maximum DO values in this review were 76.30 and 243.03 days, respectively, highlighting the wide range of reproductive performance across different management systems and genetic groups.
The lack of a significant effect (p > 0.05) of genetic group on DO suggests that non-genetic factors, such as management practices, nutritional status, and environmental conditions, play a more critical role in determining DO. This aligns with
[13] | Kefale, A. (2018). Reproductive performance of 50% F3 Friesian crossbred dairy cows at Holetta Agricultural Research Center, Ethiopia. Livestock Research for Rural Development, 30(9), 138. |
[8] | Wassie, T., Taye, M., & Dessie, T. (2015). Reproductive performance of indigenous and crossbred dairy cows in selected districts of Eastern Amhara Region, Ethiopia. Journal of Reproduction and Infertility, 6(2), 35-40. |
[19] | Tadesse, M. (2014). Reproductive and productive performance of 75% Holstein Friesian crossbred dairy cows at Alage Agricultural Technical Vocational Education and Training College, Ethiopia. International Journal of Livestock Produc-tion, 5(9), 154-160. |
[13, 8, 19]
, who emphasized that feed shortages, both in quality and quantity, and high milk production can delay the return to estrus and extend DO. High-producing cows often experience negative energy balance during early lactation, which can suppress reproductive function and prolong the interval to conception
[25] | Butler, W. R. (2003). Energy balance relationships with follicular development, ovulation and fertility in postpartum dairy cows. Livestock Production Science, 83(2-3), 211-218. |
[25]
. Additionally,
[12] | Dessalegn, T., Mekasha, Y., & Tegegne, A. (2016). Effect of management practices on pre-pubertal growth and attain-ment of puberty in crossbred dairy heifers in urban dairy production systems, Ethiopia. Tropical Animal Health and Pro-duction, 48(3), 545-550. |
[12]
highlighted that poor heat detection and suboptimal insemination practices can further exacerbate DO.
Recent studies further support the importance of management and nutritional interventions in reducing DO. For instance,
[1] | Mekonnen, G., Moges, N., & Melaku, A. (2021). Effects of intensive management on growth performance and age at first service of crossbred dairy heifers in central Ethiopia. Heliyon, 7(3), e06489. |
[1]
found that improved feeding strategies, health management, and timely heat detection significantly reduced DO in smallholder dairy systems. Similarly,
[14] | Tadesse, M., Thiengtham, J., Pinyopummin, A., & Prasanpanich, S. (2020). Impact of improved feeding management on milk yield and reproductive performance of smallholder dairy cows in Ethiopia. Tropical Animal Health and Production, 52(2), 789-795. |
[14]
reported that crossbred cows under intensive management systems achieved shorter DOs compared to those under traditional systems, underscoring the need for targeted interventions to improve reproductive efficiency.
In conclusion, while genetic factors may contribute to some variation in DO, the primary drivers appear to be management practices, nutritional status, and environmental conditions. Addressing these factors through improved feeding, health management, and strategic breeding practices can help achieve shorter DOs, thereby enhancing reproductive performance and overall productivity in crossbred dairy cows.
3.5. Number of Service Per Conception (NSPC)
The results highlight the variability in the number of services per conception (NSPC) among crossbred cows, including Jersey cross, 50% HF, and 75% HF genetic groups. The overall mean NSPC of 1.69 ± 0.28 is within an acceptable range, as values higher than 2 are considered poor
[26] | Mukassa-Mugrewa, E. (1989). A review of reproductive performance of female Bos indicus (Zebu) cattle. ILCA Mono-graph, No. 6. International Livestock Centre for Africa. |
[26]
. This result aligns with the findings of
[21] | Melku, M. (2016). Reproductive performance of 75% Holstein Friesian crossbred dairy cows under smallholder farmers’ management in Gondar, Ethiopia. Journal of Biology, Agriculture and Healthcare, 6(9), 82-87. |
[21]
, who reported a similar NSPC for 25% HF x Local crossbred cows. However, the NSPC in this review is slightly higher than values reported by
[18] | Kefena, E., Tegegne, A., & Peters, K. J. (2006). Reproductive performance of F1 and F2 crossbred dairy cows in Eastern Ethiopia. Ethiopian Journal of Animal Production, 6(1), 37-52. |
[18]
and
[13] | Kefale, A. (2018). Reproductive performance of 50% F3 Friesian crossbred dairy cows at Holetta Agricultural Research Center, Ethiopia. Livestock Research for Rural Development, 30(9), 138. |
[13]
for 75% Jersey and 75% F2 Friesian crossbred cows, respectively, but lower than the findings of
[16] | Haile, A., Joshi, B. K., Ayalew, W., Tegegne, A., & Singh, A. (2009). Genetic evaluation of Ethiopian Boran cattle and their crosses with Holstein Friesian in central Ethiopia: Age at first calving and calving interval. Journal of Agricultural Science, 147(6), 689-699. |
[16]
for 50% HF and 75% HF crossbred cows. The minimum and maximum NSPC values in this review were 1.23 and 2.20, respectively, indicating variability in reproductive efficiency across different management systems and genetic groups.
The lack of a significant effect (p > 0.05) of genetic group on NSPC suggests that non-genetic factors, such as management practices, insemination techniques, and environmental conditions, play a more critical role in determining NSPC. This is consistent with
[13] | Kefale, A. (2018). Reproductive performance of 50% F3 Friesian crossbred dairy cows at Holetta Agricultural Research Center, Ethiopia. Livestock Research for Rural Development, 30(9), 138. |
[27] | Mengistu, A., Moges, N., & Taye, M. (2016). Reproductive performance of crossbred dairy cows under smallholder con-ditions in and around Gondar, Northern Ethiopia. Journal of Dairy and Veterinary Sciences, 1(1), 1-6. |
[28] | Hunduma, D. (2012). Reproductive performance of crossbred dairy cows under smallholder conditions in Ethiopia. Inter-national Journal of Livestock Production, 3(3), 25-28. |
[13, 27, 28]
, who emphasized that inconsistent feeding management, poor heat detection, inseminator skill, semen quality, and environmental variability can negatively impact conception rates. High milk yield and lactation length can also contribute to extended NSPC, as high-producing cows often experience negative energy balance, which can suppress reproductive function
[25] | Butler, W. R. (2003). Energy balance relationships with follicular development, ovulation and fertility in postpartum dairy cows. Livestock Production Science, 83(2-3), 211-218. |
[25]
. Additionally, silent ovulation and suboptimal insemination timing can further reduce conception rates
[12] | Dessalegn, T., Mekasha, Y., & Tegegne, A. (2016). Effect of management practices on pre-pubertal growth and attain-ment of puberty in crossbred dairy heifers in urban dairy production systems, Ethiopia. Tropical Animal Health and Pro-duction, 48(3), 545-550. |
[12]
.
Recent studies further support the importance of management and nutritional interventions in reducing NSPC. For instance,
[1] | Mekonnen, G., Moges, N., & Melaku, A. (2021). Effects of intensive management on growth performance and age at first service of crossbred dairy heifers in central Ethiopia. Heliyon, 7(3), e06489. |
[1]
found that improved feeding strategies, health management, and timely heat detection significantly reduced NSPC in smallholder dairy systems. Similarly,
[14] | Tadesse, M., Thiengtham, J., Pinyopummin, A., & Prasanpanich, S. (2020). Impact of improved feeding management on milk yield and reproductive performance of smallholder dairy cows in Ethiopia. Tropical Animal Health and Production, 52(2), 789-795. |
[14]
reported that crossbred cows under intensive management systems achieved lower NSPC compared to those under traditional systems, underscoring the need for targeted interventions to improve reproductive efficiency.
In conclusion, while genetic factors may contribute to some variation in NSPC, the primary drivers appear to be management practices, nutritional status, and environmental conditions. Addressing these factors through improved feeding, health management, and strategic breeding practices can help achieve lower NSPC, thereby enhancing reproductive performance and overall productivity in crossbred dairy cows.
3.6. Phenotypic Correlation
Correlations are measures of the strength of the relationship between two variables, and they play a crucial role in predicting the response to selection in one trait due to selection in another
[29] | Bourdon, R. M. (2000). Understanding Animal Breeding (2nd ed.). Prentice Hall. |
[29]
. In this review, phenotypic correlations were estimated between reproductive traits. Age at first service (AFS) and age at first calving (AFC) showed a positive correlation with calving interval (CI), number of services per conception (NSPC), and days open (DO). This finding aligns with
[13] | Kefale, A. (2018). Reproductive performance of 50% F3 Friesian crossbred dairy cows at Holetta Agricultural Research Center, Ethiopia. Livestock Research for Rural Development, 30(9), 138. |
[13]
, who reported that AFS was negatively correlated with CI, DO, and NSPC, while AFC was negatively correlated with CI and DO but positively correlated with NSPC.