AAVS_13_8_1708-1715

INTRODUCTION

Indonesian Friesian Holstein (FH) cattle are the backbone of national milk production in Indonesia. However, their reproductive performance is frequently hampered by delayed age at first calving (AFC), prolonged days open (DO), and extended calving intervals (CI), leading to reduced productivity and profitability for dairy farms (Armengol et al., 2023; Tadesse et al., 2022). These challenges are exacerbated by suboptimal management practices, inadequate feed quality, and the physiological limitations of FH cattle to Indonesia’s tropical climate, resulting in lower conception rates and inefficiencies in herd replacement (Aryogi et al., 2024; Mandal et al., 2021).

The ideal reproductive benchmarks include an AFC ranges between 24–26 months to support optimal milk productivity (Pasaribu et al., 2023; Christi, 2023), S/C value is 1–2 artificial inseminations (AI) per pregnancy, DO should be less than 120 days (Adyatama et al., 2024), and CI is 365 days. However, prolonged CI and suboptimal CR (<60%) persist due to management gaps like poor estrus detection and nutritional deficits (Sudrajat et al., 2022; Nuryamin et al., 2024; Tadesse et al., 2022). Lactation periods also play an important role in the reproductive performance of FH cattle. During early lactation, energy deficits frequently occur due to high demands for milk production, resulting in delayed estrous cycles and reduced conception rates (Knegsel et al., 2022). Additionally, technology-based approaches such as AI using sexed semen offer potential to improve reproductive efficiency while increasing the female birth ratio. However, the effectiveness of this technology still requires further evaluation to ensure results align with expectations.

The Technical Implementation Unit for Livestock Breeding and Forage (TIU-LBF) Batu plays a strategic role in addressing these challenges by ensuring livestock breeding quality meets Indonesian National Standards (SNI). However, an in-depth evaluation of FH cattle reproductive performance at this unit remains limited. Therefore, this study aims to evaluate the reproductive performance of Indonesian FH cattle based on lactation periods TIU-LBF Batu and to assess the effectiveness of the implemented livestock breeding policies.

MATERIALS AND METHODS

Time and Location of Research

This research was conducted from December 2024 to February 2025 at the Technical Implementation Unit for Livestock Breeding and Forage (TIU-LBF) Batu located at Jalan Raya Tlekung, Beji Village, Junrejo District, Batu City, East Java Province, Indonesia.

Research Materials and Sampling Method

The study involved 62 female Friesian Holstein (FH) dairy cows kept at TIU-LBF Batu. All cows meeting the inclusion criteria were selected as samples (census), with reproductive data collected retrospectively from herd records for the period 2021–2024. Inclusion criteria consisted of FH dairy cows with complete records of birth date, calving, insemination, and pregnancy confirmation, and being in lactation periods I, II, or III during the study period. Cows with a history of abortion, those not originating from TIU-LBF Batu, or inseminations using semen from sources other than BBIB Lembang/Singosari or with incomplete calf sex data were excluded from the analysis.

Research Design

This study employed a case study design with a quantitative approach. Primary data were obtained through interviews with inseminators and barn staff, while secondary data were sourced from herd reproductive records.

Observed Variables

The study population comprised 62 Indonesian Friesian Holstein (FH) dairy cattle at UPT PT dan HMT Batu. Reproductive data were collected retrospectively from herd records (2020–2025), with parameters selected based on availability and alignment with international dairy cattle reproduction KPIs (Armengol et al., 2023). Data collection included:

Age at first calving (AFC): Defined as the cow’s age (in days) at initial parturition. This parameter reflects heifer rearing efficiency and was analyzed against the optimal range of 22–25 months (Atashi et al., 2021).

Service per conception (S/C): The number of artificial inseminations (AI) required to achieve pregnancy. Values >2.0 indicate suboptimal fertility, as per benchmarks for tropical dairy systems (Mungube et al., 2019).

Days open (DO): Postpartum interval from calving to subsequent conception. Ideal targets ≤120 days were applied (Temesgen et al., 2022).

Conception rate (CR): Percentage of cows conceiving on first AI. Values <60% suggest issues in estrus detection or semen quality (Nuryamin et al., 2024).

Calving interval (CI): Duration between consecutive calvings, with 365–420 days considered optimal for annual calving (Setyorini et al., 2022).

AI outcomes: Calf sex ratios from sexed (Singosari) and non-sexed (Lembang/Singosari) semen were compared to evaluate sexing technology efficacy (Wiranto et al., 2020).

The reproductive traits examined in this study included:

Age at first calving (AFC): The age at which a female cow first calves.

Service per conception (S/C): The number of inseminations required to achieve pregnancy.

Days open (DO): The interval between calving and the next pregnancy.

Conception rate (CR): The percentage of cows that conceive on their first insemination.

Calving interval (CI): The time span between consecutive calvings.

Results of AI using sexed and non-sexed semen: The percentage of calves produced from sexed versus non-sexed semen.

Ethical Approval

All research procedures involving animals were approved by the Faculty of Animal Science, Universitas Brawijaya (Approval No.: 00045/UN10.F0501/B/PP/2025), in accordance with national animal welfare regulations (Peraturan Menteri Pertanian Republik Indonesia No. 14 Tahun 2020) and with permission from TIU-LBF Batu.

Data Analysis

Data were analyzed descriptively to obtain the mean and standard deviation of each reproductive parameter (Lušņičenko et al., 2024). One-way ANOVA was used to compare S/C among lactation periods, followed by Tukey’s test if significant differences were found (Setyorini et al., 2022). The chi-square test was used to compare AI success rates between the use of sexed and non-sexed semen (Adyatama et al., 2024; Wiranto et al., 2020; Jaglan et al., 2023). All analyses were performed using Microsoft Excel and R Studio (Herdian et al., 2024).

Research Ethics Statement

This research received permission from TIU-LBF Batu and followed animal welfare guidelines in accordance with the Regulation of the Minister of Agriculture of the Republic of Indonesia Number 14 of 2020 concerning Animal Welfare in Livestock. All research procedures were conducted with minimal stress to animals and ensured optimal health conditions during data collection.

RESULTS AND DISCUSSION

Key Findings

To provide a clear overview of the study outcomes, we summarize the key findings of reproductive performance in Indonesian Friesian Holstein dairy cattle across lactation periods as follows:

Age at first calving (AFC): 34.16 months, exceeding the ideal range of 24–26 months.

Service per conception (S/C): Highest in lactation I (2.65; P<0.05 vs. II), indicating reduced fertility in early lactation.

Days open (DO): Exceeded 120 days in all periods.

Calving interval (CI): Exceeded 420 days in all periods.

Conception rate (CR): Lowest in lactation I (22.92%), improving in later lactations but remaining below the 60% benchmark.

Sexed semen outcome: Sexed semen produced 63.16% male calves, contrary to the expected 50% female bias.

Age at First Calving (AFC)

We observed that the AFC value was 1,024.71 ± 182.42 days (≈34.16 months), exceeding the ideal standard of 24–26 months. This value is relatively higher compared to the ideal standard according to Atashi et al. (2023) of 24 to 26 months (720-780 days), indicating a delay of approximately 8 to 10 months from the ideal standard. The relatively large standard deviation (182.42 days) indicates high variability in the population, reflecting inconsistency in heifer management. Cattle reached the fastest AFC at 1.88 years of age, while delayed first-calving cattle reached AFC at 3.96 years, almost 4 years. Delayed AFC (>3 years) results from breeding management factors such as suboptimal estrus detection, high S/C (more than once), malnutrition during the pre-weaning phase, and reproductive health disorders.

Service Per Conception (S/C)

The Service per Conception (S/C) values for lactation periods I, II, and III were 2.65 ± 1.52, 1.98 ± 0.92, and 2.13 ± 1.52, respectively. A significant difference (P<0.05) was observed between periods I and II, indicating improved reproductive efficiency during lactation period II. This improvement may be attributed to enhanced reproductive management, including more accurate estrus detection, better semen straw quality, and improvements in livestock maintenance and nutrition. The lower S/C value in period II reflects the positive impact of these management adjustments.

The increase in S/C during lactation period III (2.13) suggests fluctuations in reproductive efficiency. This resulted from cattle health issues following the 2022 Foot-and-Mouth Disease (FMD) outbreak, which can cause reduced fertility and productivity (Torres-Aburto et al., 2020; Temesgen et al., 2022). This aligns with findings by Sudrajat et al. (2022), who reported that S/C values >2.0 are associated with chronic energy deficits and suboptimal nutritional status in late-lactation cows. Nutritional imbalances, particularly energy deficiencies, can reduce reproductive efficiency by lowering Body Condition Score (BCS), disrupting reproductive hormones, prolonging anestrus periods, and decreasing pregnancy rates.

Generally, high S/C values can be addressed through improved reproductive management (e.g., estrus detection, semen quality, insemination timing), enhanced livestock maintenance, and optimized nutrition-specifically ensuring adequate energy and protein intake. Integrated efforts across management and nutritional aspects are critical to achieving ideal S/C values (1–2 inseminations per conception).

The standard deviation (SD) of S/C was quite high, particularly in periods I (1.52) and III (1.52), showing significant variation between individuals in the number of AIs required to achieve pregnancy. Factors such as reproductive health conditions, semen quality, and AI timing can influence this variation (Tariq et al., 2024). Period III had the widest S/C value range, from minimum 1 to maximum 9, indicating extreme variation in reproductive efficiency. Period II had the narrowest S/C value range (1-4), indicating more consistent reproductive management. Overall, despite fluctuations, there are indications of improved reproductive efficiency from period I to subsequent periods. However, consistent efforts are still needed to achieve and maintain ideal S/C values across all periods.

Days Open (DO)

DO in lactations I, II, and III were 254.62 ± 163.58, 195.48 ± 110.37, and 210.81 ± 104.54 days, respectively. These values exceed the optimal standard (<120 days) (Adyatama et al., 2024). Short DO indicates cows return to estrus and achieve subsequent pregnancy more rapidly after calving, contributing to improved reproductive efficiency (Temesgen et al., 2022). Conversely, long DO reflects delays in rebreeding, which may result from suboptimal estrus detection, health disorders, or nutritional deficits. This results from factors such as improved nutrition, optimal health management, and more efficient breeding programs. However, the increase in Period III indicates variations in reproductive performance caused by external factors such as environmental stress, health disturbances, changes in feed management, and delayed AI during FMD recovery. The DO period in this study is longer than the ideal value, ranging from 85-115 days, related to lactation energy deficit (NE-l) of -8.42 Mcal/head/day. This deficit indicates that cows do not receive sufficient energy to support optimal milk production and post-lactation recovery. This can cause reproductive disorders such as increased Days Open (DO) and decreased Body Condition Score (BCS), as reported by Wicaksono and Susilorini (2022) at the same location, TIU-LBF Batu, where most cows had BCS values in the “rather thin” (1.75–2.50) to “medium” (BCS 2.75–3.00) categories.

Conception Rate (CR)

CR in lactations I, II, and III were 22.92%, 40.00%, and 37.50%. CR values show a similar pattern, with the lowest value in lactation period I (22.92±6.07) and highest in lactation period II (40.00±6.93). The ideal CR is 60% (Nuryamin et al., 2024); low CR is caused by improper AI timing and as well as poor body condition of livestock. Body condition score below 3 will result in a high S/C value. Research by Lee et al. (2021) showed that insemination at optimal timing after estrus detection can significantly increase CR. Additionally, using protocols such as Ovsynch to manage reproductive cycles has also been proven to increase CR to 67.7% (Borş, 2021). Environmental conditions, particularly heat stress, also significantly impact CR. This is supported by Wicaksono and Susilorini’s (2022) research that temperatures at TIU-LBF Kota Batu around 15-34ºC with unpredictable weather can cause decreased production performance due to heat stress. This aligns with Aryogi et al. (2024) who reported that heat stress also impairs reproductive quality, including oocyte maturation and early embryonic development, leading to lower conception rates and higher pregnancy failure. Furthermore, Khan et al. (2023) stated that heat stress can reduce CR by 20-27% during summer, and Simmental cattle were found to exhibit higher heat tolerance than Holstein cattle, as indicated by a lower increase in somatic cell count in milk during heat stress conditions.

Calving Interval (CI)

The decrease in calving interval (CI) from 553.45 days in the first lactation to 468.22 days in the third lactation indicates improved reproductive efficiency. However, despite this reduction, CI values remained over 120 days longer than the ideal target of 365 days. This persistent gap highlights ongoing management deficiencies that need to be addressed to achieve the recommended goal of one calving per year in dairy cows (Setyorini et al., 2022; Prabowo, 2021; Alwinda et al., 2023). The extended CI at UPT is caused by high DO and low CR.

The standard deviation also decreased from period I to period III, from 173.81 days to 91.66 days. This indicates that variation in CI decreases with increasing lactation experience, which can contribute to increased stability and predictability in reproductive management (Handcock et al., 2020). The ideal CI value should not exceed 14 months (420 days), and longer CI can result in decreased profitability for farmers (Setyorini et al., 2022; Ózsvári et al., 2020). Factors affecting CI value in this study are closely related to DO value; period I CI: 553.45 days, DO: 254.62 days; period II CI: 474.70 days (decreased 14.2%), DO: 195.48 days; period III CI: 468.22 days, DO: 210.81 days.

Research in tropical regions shows that intensive management systems can produce shorter CI compared to semi-intensive systems, with average CI of 17.53 months and 20.03 months, respectively (Alwinda et al., 2023). Overall, several factors affecting reproductive performance include livestock health conditions, including FMD cases in 2022 that impacted reproductive efficiency, suboptimal feed management, environmental stress, particularly heat stress with environmental temperatures around 15-34°C. Aryogi et al. (2024) also emphasize that local cattle demonstrate better adaptation and more stable performance across various altitudes, whereas crossbred dairy cattle are more susceptible to extreme tropical environmental changes, making the development of crossbred dairy cattle more advisable in highland regions. This highlights the importance of management practices in reproductive efficiency.

AI Success Using Sexed and Non-sexed Semen

A critical finding was sexed semen produced 63.16% male calves vs. expected 50% female bias (Figure 1). This outcome is highlighted here due to its significant implications for breeding strategies and herd replacement planning. This finding is consistent with Harshini et al. (2022), who reported reduced X-sperm viability after the sexing process.

The histogram in Figure 1 shows the sex distribution of offspring resulting from artificial insemination (AI) using non-sexed semen from BBIB Lembang. The histogram shows the proportion of female calf births is 42.50% (17 head), while male calves reach 57.50% (23 head) from a total of 40 samples. The red horizontal line marks the expected value of balanced sex distribution (50%). Test results show that sex distribution does not significantly differ from the expected 50%. This indicates that the non-sexed semen used produces a sex distribution approaching random. In contrast, Singosari sexed semen resulted in a male-biased ratio (63.16% male vs. 36.84% female), contradicting the intended purpose of sexing technology to increase female births. This discrepancy suggests technical limitations in the sperm-sorting process, such as suboptimal X/Y chromosome separation or reduced sperm viability post-sorting (Harshini et al., 2022; Guo et al., 2020).

Overall, non-sexed semen from both BBIB Lembang and Singosari produces sex distributions approaching random without significant difference from the 50% expectation. This aligns with the characteristics of non-sexed semen that does not undergo X and Y chromosome separation. Research shows that non-sexed semen, which does not undergo chromosome separation, produces balanced sex proportions (50:50), similar to those found in natural populations (Harshini et al., 2022). In this context, non-sexed semen serves as an important control to compare the effectiveness of sex-sorted semen that often shows different results in terms of reproductive success rates and birth ratios (Guo et al., 2020; Reese et al., 2021). The chromosome separation process in sexed semen can reduce sexed sperm viability by 15–20% (Hamid et al., 2021; Koca et al., 2023), potentially affecting insemination success rates (Ayoub and Mohamed, 2022). The results of using sexed semen in this study demonstrate ineffectiveness in increasing the likelihood of female calf births. Factors include: potentially suboptimal sexing process in separating X and Y spermatozoa, semen quality after the sexing process, AI timing precision relative to ovulation which is critical for successful AI with sexed semen, or the physiological condition of the cow that can affect sexing technique success. Thus, AI results from BBIB Lembang and Singosari semen support the understanding that non-sexed semen produces balanced sex distribution, which is a natural characteristic of semen that does not undergo chromosome separation process. This affirms the importance of considering separation methods and their impact on semen quality and reproductive outcomes in artificial insemination practices (Meles et al., 2022; Wiranto et al., 2020) although sexed semen can be used for sex selection purposes, we still need to consider overall reproductive success (Sawant et al., 2022).

Managerial Factors and Recommendations

The herd experienced a NE-l deficit (−8.42 Mcal/head/day) exceeds critical thresholds. Deficits greater than −5 Mcal/head/day have been shown to significantly increase the risk of decreased Body Condition Score (BCS), prolonged postpartum anestrus, reduced conception rates, and extended days open and calving intervals (Nigussie, 2018; National Academies of Sciences, 2021). Estrus detection in the herd relied primarily on visual observation, a method susceptible to inaccuracies; thus, integrating activity monitoring systems or infrared thermography is recommended to enhance detection accuracy (Shokrollahi et al., 2024). The use of a modified Ovsynch protocol (GnRH–PGF2α–GnRH–timed AI) is recommended, as it has been shown to increase conception rates in multiparous cows. The Ovsynch protocol is a reproductive management technique that uses a timed sequence of hormone injections (GnRH and PGF2α) to synchronize ovulation, allowing for fixed-time artificial insemination without the need for estrus detection (Lee et al., 2021; Borş, 2021). Nutritional management should be improved by adjusting the forage-to-concentrate ratio to 60:40 during early and mid-lactation and providing targeted mineral supplementation (Zn, Cu, Se) to correct energy and micronutrient deficits (National Academies of Sciences, 2021). Furthermore, it is essential to routinely evaluate the effectiveness of sexed semen before large-scale implementation to avoid skewed calf sex ratios and ensure optimal herd replacement.

CONCLUSIONS AND RECOMMENDATIONS

This study reveals that the reproductive performance of Indonesian Friesian Holstein dairy cattle at TIU-LBF Batu remains below optimal standards, as indicated by delayed age at first calving, high service per conception, prolonged days open, low conception rates, and extended calving intervals. These inefficiencies are primarily driven by inadequate energy intake, suboptimal estrus detection, and the limited effectiveness of sexed semen technology. Strategic interventions are required, including adjusting the forage-to-concentrate ratio to 60:40 during early and mid-lactation, providing targeted mineral supplementation (Zn, Cu, Se), adopting reproductive management protocols such as Ovsynch to synchronize ovulation and optimize insemination timing, and routinely evaluating the effectiveness of sexed semen before large-scale use. Addressing these issues is critical, as persistent reproductive inefficiencies increase production costs, reduce farm profitability, and hinder progress toward national breeding standards and sustainable dairy development in Indonesia.

ACKNOLEDGMENTS

We express our gratitude to the Technical Implementation Unit for Livestock Breeding and Forage (TIU-LBF) Batu for granting access to data and facilities during this study. We also thank the inseminators, farm staff, and management team for their cooperation and support throughout the research process.

NOVELTY STATEMENTS

This study provides the first integrated analysis of key reproductive parameters (AFC, S/C, DO, CR, and CI) of Indonesian Friesian Holstein cattle across lactation periods at a government breeding unit (TIU-LBF Batu), highlighting persistent inefficiencies despite institutional interventions.
The field-based assessment of sexed semen technology, which unexpectedly resulted in a male-biased calf ratio (63.16% males), highlighting the current limitations of sexing technology in achieving targeted female calf production for herd replacement.
The identification of a negative net energy balance (−8.42 Mcal/head/day) as a major contributing factor to poor reproductive outcomes underscores the critical role of nutritional management in optimizing reproductive efficiency in institutional dairy herds.

AUTHOR’S CONTRIBUTIONS

The authors confirm contribution to the paper as follows: St. Theresia Sri Wulandari Setiawanti: Collected the data, Conceptualization, methodology, and manuscript drafting,Tri Eko Susilorini: Performed the statistical analysis and the preparation of tables, Sri Wahjuningsih: corrected the manuscript attending the reviewer’s suggestions and language of the manuscript, Kuswati: Review of results and critical manuscript revision and Suyadi: Supervision, project administration, and corresponding author responsibilities.

Conflict of Interest

The authors declare no conflicts of interest regarding the publication of this article.

REFERENCES

Adyatama A, Muktiani A, Samsudewa D (2024). Correlation between body condition score with estrus and reproductive performance in dairy cow post ovary hypofunction. Livestock Anim. Res., 22(1): 34. https://doi.org/10.20961/lar.v22i1.72066

Alwinda TA, Tafsin M, Trisna A, Mulatsi S (2023). Comparative study of livestock appearance and beef cattle breeder income in Aek Kuo District of North Labuhanbatu Regency. J. Peternakan Integratif, 11(1): 16–23. https://doi.org/10.32734/jpi.v11i1.11564

Armengol R, Fraile L, Bach À (2023). Key performance indicators used by dairy consultants during the evaluation of reproductive performance during routine visits. Front. Vet. Sci., 10:1165184: 10. https://doi.org/10.3389/fvets.2023.1165184

Aryogi A, Affandhy L, Pamungkas D, Setiasih S, Anggraeny Y, Prihandini P, Matitaputty P, Suyasa I, Rusdiana S, Ramsiati D, Wulansari W, Chanafi M, Robba D, Luthfi M (2024). Genetic environmental interaction to achieve optimum physiological states of crossbred cattle in tropical climate. Global J. Environ. Sci. Manage., 10(4): 2083-2098. https://doi.org/10.22034/ggjesm.2024.04.35

Atashi H, Asaadi A, Hostens, M (2021). Association between age at first calving and lactation performance, lactation curve, calving interval, calf birth weight, and dystocia in Holstein dairy cows. Plos One, 16(1): e0244825. https://doi.org/10.1371/journal.pone.0244825

Ayoub EOFEE, Mohamed, MA (2022). Effect of rabbit semen filtration methods on conception rates and altering sex ratio in artificially inseminated rabbits. J. Anim. Poult. Fish Prod., 11(1): 55–63. https://doi.org/10.21608/japfp.2022.284098

Borş SI (2021). Adapting the treatment of ovarian cysts according to their type in dairy cattle. J. Appl. Life Sci. Environ., 54(1): 77–84. https://doi.org/10.46909/journalalse-2021-008

Christi R (2023). Evaluasi performa produksi susu dan reproduksi sapi perah Friesian Holstein di BPT HMT Cikole Lembang. Jurnal Sumber Daya Hewan, 4(1): 1–10. https://doi.org/10.24198/jsdh.v4i1.48548

Guo W, Liu J, Li W, Ma H, Gong Q, Kan X, Cao Y, Wang J, Fu S (2020). Niacin Alleviates Dairy Cow Mastitis by Regulating the GPR109A/AMPK/NRF2 Signaling Pathway. Int. J. Mol. Sci., 21(9): 3321. https://doi.org/10.3390/ijms21093321

Hamid M, Abduraman S, Tadesse B (2021). Risk factors for the efficiency of artificial insemination in dairy cows and economic impact of failure of first service insemination in and around Haramaya Town, Oromia Region, Eastern Ethiopia. Vet. Med. Int., 2021: 1–6. https://doi.org/10.1155/2021/6622487

Handcock RC, López-Villalobos N, McNaughton L, Back PJ, Edwards G, Hickson RE (2020). Body weight of dairy heifers is positively associated with reproduction and stayability. J. Dairy Sci., 103(5): 4466–4474. https://doi.org/10.3168/jds.2019-17545

Harshini V, Karthickeyan S, Kumarasamy K, Jeevan C (2022). Determination of sex ratio in bovine semen using SYBR Green real-time PCR. Res. Square. 1-12. https://doi.org/10.21203/rs.3.rs-1154594/v1

Herdian H, Sofyan A, Sakti AA, Harahap MA, Wulandari, Widodo S, Kusnadi H, Anggraeni AS, Darma ING (2024). The Use of R Programming Language for ModellingIn vitroRumen Fermentation Gas Production. BIO Web Conf., 88:, 00002. https://doi.org/10.1051/bioconf/20248800002

Jaglan K, Sukhija N, KK K, Verma A, Surati U, Amandeep, Ritu (2023). Chi square analysis of parity, period of calving, season of calving, and lactation yield influencing mastitis incidence in Bubalus bubalis. Pharma. Innov. J., 12(11S): 561–563.

Khan I, Mesalam A, Heo YS, Lee S, Nabi G, Kong I (2023). Heat stress as a barrier to successful reproduction and potential alleviation strategies in cattle. Animals, 13(14): 2359. https://doi.org/10.3390/ani13142359

Knegsel A, Burgers E, Ma J, Goselink R, Kok A (2022). Extending lactation length: Consequences for cow, calf, and farmer. J. Anim. Sci., 100(10): skac220. https://doi.org/10.1093/jas/skac220

Koca D, Aktar A, Turgut A, Sağırkaya H, Alçay S (2023). The effect of conventional semen, sexed-semen, and embryo transfer on pregnancy rate in Holstein dairy cows. J. Res. Vet. Med., 42(2): 99–103. https://doi.org/10.30782/jrvm.1361215

Lee J, Lee S, Park Y, Lee S, Ha S, Han M, Chung H (2021). The detection of bovine estrus by lactoferrin monoclonal antibody. Animals, 11(6): 1582. https://doi.org/10.3390/ani11061582

Lušņičenko M, Zolova A, Perevozčikova J, Gavrilova A, Semjonov A, Zolovs M (2024). Beyond the p-value: How descriptive statistics unlock insights in veterinary research. Ger. J. Vet. Res., 4 (3): 140-150. https://doi.org/10.51585/gjvr.2024.3.0105

Mandal DK, Bhakat C, Dutta TK (2021). Impact of environmental factors on physiological adaptability, thermo-tolerance indices, and productivity in Jersey crossbred cows. Int. J. Biometeorol., 65: 1999–2009. https://doi.org/10.1007/s00484-021-02157-2

Meles D, Mustofa I, Hariadi M, Wurlina W, Susilowati S, Amaliya A, Rimayanti R (2022). The enriched Y-bearing sperm combined with delayed fixed-time artificial insemination for obtaining male Simmental crossbred offspring. Vet. World, 15(1): 102–109. https://doi.org/10.14202/vetworld.2022.102-109

Mungube EO, Njarui DMG, Maichomo MW, Olum MO, Ndirangu PN, Kabirizi J, Ndikumana J, Mwangi G (2019). Reproductive performance indicators of dairy cattle in selected small-scale dairy farms in semi-arid Eastern Kenya. Livestock Res. Rural Dev., 31(6): http://lrrd.cipav.org.co/lrrd31/6/erick31088.html

National Academies of Sciences, Engineering, and Medicine (2021). Nutrient Requirements of Dairy Cattle (8th rev. ed.). Washington, DC: The National Academies Press. https://doi.org/10.17226/25806

Nigussie T (2018). A Review on the Role of Energy Balance on Reproduction of Dairy Cow. J. Dairy Res. Technol., 1(1): 1–9. https://doi.org/10.24966/drt-9315/100003

Nuryamin H, Widyani R, Sumardjo D (2024). Evaluasi tingkat keberhasilan inseminasi buatan (IB) pada sapi peranakan Onggole (PO) (Studi kasus di Kelompok Tani Harapan Mulya Kabupaten Kuningan) Tahun 2011 s/d 2013. Kandang: Jurnal Peternakan, 6(1): 24–29. https://doi.org/10.32534/jkd.v6i1.206

Ózsvári L, Harnos A, Láng Z, Monostori A, Strain S, Fodor I (2020). The impact of paratuberculosis on milk production, fertility, and culling in large commercial Hungarian dairy herds. Front. Vet. Sci., 7: 565324. https://doi.org/10.3389/fvets.2020.565324

Pasaribu A, Firmansyah F, Idris N (2023). Analisis faktor-faktor yang memengaruhi produksi susu sapi perah di Kabupaten Karo Provinsi Sumatera Utara. J. Ilmiah Ilmu-Ilmu Peternakan, 18(1): 28–35. https://doi.org/10.22437/jiiip.v18i1.2656

Prabowo T (2021). Performen reproduksi dan produksi susu sapi perah di Kecamatan Tegalombo Kabupaten Pacitan Provinsi Jawa Timur. J. Peternakan Sriwijaya, 10(1): 29–36. https://doi.org/10.33230/jps.10.1.2021.13762

Reese S, Pirez M, Steele H, Kölle S (2021). The reproductive success of bovine sperm after sex-sorting: A meta-analysis. Sci. Rep., 11(1): 1–12. https://doi.org/10.1038/s41598-021-96834-2

Sawant S, Patil M, Ingawale M, Hase P (2022). Effect of sexed and conventional semen on pregnancy rate in Murrah buffaloes under field condition. Indian J. Vet. Sci. Biotechnol., 18(4): 143–144. https://doi.org/10.48165/ijvsbt.18.4.30

Setyorini YW, Kurnianto E, Sutopo S, Sutiyono, S (2022). Effect of age at first calving on milk production and reproductive performance of Indonesian Holstein dairy cattle. Buletin Peternakan, 46(4): 243–250. https://doi.org/10.21059/buletinpeternak.v46i4.77097

Shokrollahi B, Morammazi S, Dananiani K, Tarjoman H (2024). Infrared thermometry for detecting estrus and pregnancy in Holstein cows. J. Therm. Biol., 125: 103972. https://doi.org/10.1016/j.jtherbio.2024.103972

Sudrajat A, Khaerudin A, Christi R (2022). Dairy cow reproduction display (Friesian Holstein) at KPBS Pangalengan Bandung Regency. Majalah Ilmiah Peternakan, 25(3): 166–175. https://doi.org/10.24843/mip.2022.v25.i03.p08

Tadesse B, Reda A, Kassaw N, Tadeg W (2022). Success rate of Artificial Insemination, Reproductive Performance and Economic Impact of failure of first service insemination: A Retrospective Study, 18(1): 226. https://doi.org/10.21203/rs.3.rs-1672235/v1

Tariq M, Khan M, Manzoor H, Asghar M, Nazeer H, Sadiq A, Shah, S, Rauf U, Zeb, K, Rehman M (2024). Effect of heat stress on ovaries evolution of repeat breeders in dairy cattle, specifically holstein friesian. Biol. Clin. Sci. Res. J., 2024(1): 737. https://doi.org/10.54112/bcsrj.v2024i1.737

Temesgen M, Assen A, Gizaw T, Minalu B, Mersha A (2022). Factors affecting calving to conception interval (days open) in dairy cows located at Dessie and Kombolcha Towns, Ethiopia. PLOS ONE, 17(2): e0264029. https://doi.org/10.1371/journal.pone.0264029

Torres-Aburto VF, Barrientos-Morales M, Hernández-Flores H, Rodríguez-Andrade A, Cervantes-Acosta P, Landi V, Beltran AH, Domínguez-Mancera B (2020). Breeding soundness examination and herd proficiency of local genetic groups of bulls in tropical environment conditions in Veracruz, Mexico. Ital. J. Anim. Sci., 19(1): 840–855. https://doi.org/10.1080/1828051x.2020.1803773

Wicaksono A, Susilorini TE (2022). Hubungan periode laktasi dengan body condition score (BCS) dan produksi susu pada sapi perah peranakan Friesian Holstein (PFH) di UPT PT-HMT Kota Batu [Skripsi]. Universitas Brawijaya.

Wiranto W, Kuswati K, Prafitri R, Huda A, Yekti A, Susilawati T (2020). Tingkat keberhasilan inseminasi buatan menggunakan semen beku sexing pada bangsa sapi yang berbeda. Jurnal Agripet, 20(1): 17–21. https://doi.org/10.17969/agripet.v20i1.15811