Associations between dairy cow inter-service interval and probability of conception

Estrus Detection and Dairy Cow Identification with Cascade Deep Learning for Augmented Reality-Ready Livestock Farming

Accurate prediction of the estrus period is crucial for optimizing insemination efficiency and reducing costs in animal husbandry, a vital sector for global food production. Precise estrus period determination is essential to avoid economic losses, such as milk production reductions, delayed calf births, and disqualification from government support. The proposed method integrates estrus period detection with cow identification using augmented reality (AR). It initiates deep learning-based mounting detection, followed by identifying the mounting region of interest (ROI) using YOLOv5. The ROI is then cropped with padding, and cow ID detection is executed using YOLOv5 on the cropped ROI. The system subsequently records the identified cow IDs. The proposed system accurately detects mounting behavior with 99% accuracy, identifies the ROI where mounting occurs with 98% accuracy, and detects the mounting couple with 94% accuracy. The high success of all operations with the proposed system demonstrates its potential contribution to AR and artificial intelligence applications in livestock farming.

Evaluation of breeding objectives, breeding practices and reproductive performance of indigenous dairy cows in selected districts of Kaffa Zone, South West Ethiopia

BACKGROUND

Breeding objectives are designed to achieve targeted dairy cow production goals, which can be affected by production type, farmer preferences, environmental factors and genetic factors individually or in combination. Breeding practices, such as both controlled and uncontrolled, and artificial insemination (AI) are the tools used to obtain the desired breeding objectives. The lower reproductive performance of indigenous dairy cows affects the total milk production and calf crops that are produced during their lifetime. Designing appropriate breeding objectives and breeding practices can improve the reproductive performance of dairy cows and their overall production performance.

MATERIALS AND METHODS

The current study was conducted with the objective of evaluating the breeding, practices and performance of indigenous dairy cattle in the south western part of Ethiopia. The districts of Gesha and Chena were purposefully chosen. The study design for the 384 household surveys was a cross-sectional survey with a simple random sample approach. Data analysis was carried out by MS-Excel (2010) and the general linear model procedure of SAS of 2008.

RESULTS

The current study revealed that methods of breeding were predominantly natural-controlled mating, followed by natural-uncontrolled mating and AI in descending order. Breeding objectives were input function, output function, sociocultural and economic functions and assets and security functions in decreasing order of rank. Reproduction performance indexes of indigenous dairy cows age at first service (3.72 ± 0.05 years), age at first calving (AFC) (4.71 ± 0.07 years), calving interval (CI) (1.58 ± 0.03 years), days open (DO) (4.26 ± 0.11 months), services per conception in natural mating (1.4 ± 0.08) and AI (2.73 ± 0.14), age of bull at maturity (4.17 ± 0.74 years), interoestrus interval (23.18 ± 0.61 days), calves crop (7.53 ± 0.22) and the life span of indigenous dairy cow (11.94 ± 0.26 years) were significant (p < 0.01) between two districts, whereas the values of age of bull at maturity and number of services per conception in natural mating were significant (p < 0.05) between districts.

CONCLUSIONS

Using AI and major reproduction performances, such as AFC, CI and DO of indigenous dairy cows in the study area, were very low. Therefore, concerned bodies should intervene to improve reproduction performance through the utilization of AI techniques, with the integration of forage development activities and improvements in livestock health care.

Estimates of dairy herd health indicators of mastitis, ketosis, inter-calving interval, and fresh cow replacement in the Piedmont region, Italy

Test-day milk analysis has largely been used to study health and performance parameters in dairy cows. In this study, we estimated four health indicators of dairy cows using test-day data. Our purpose was to estimate (1) mastitis incidence rate, prevalence, and the probability of recovery; (2) the incidence proportion of ketosis; (3) the duration of inter-calving interval; and (4) the risk of a fresh cow being replaced, in a large cohort of dairy herds in the Piedmont region (Italy). We retrospectively analysed test day records of 261,121 lactating cows and 1315 herds during five years (2015-2020). Mastitis was defined by somatic cell count and ketosis by fat-to-protein ratio. Calving dates were used to calculate ICI and to estimate the removal of a fresh cow from the herd. Mixed-effect generalized linear models were used to adjust for unmeasured herd-level risk factors. The risk of mastitis increased by 120% with parity (Odds ratio [OR] = 2.20, confidence interval [CI]: 2.17 - 2.23), by 7% by months in milking (OR = 1.07, CI: 1.07 - 1.07), and even more if the cow was already affected during the same lactation (OR = 8.74, CI: 8.67 - 8.82). Lactose concentration on the previous test day was the best positive prognostic factor for mastitis recovery (OR = 1.12, CI: 1.08 - 1.17). Ketosis risk was the highest between 3rd and 4th lactations and itself increased the risk of having ICI longer than 440 days (OR = 1.12, CI: 1.02 - 1.22), and fresh-cow removal (OR = 1.75, CI: 1.58 - 1.93). Also, the removal of fresh cows was more likely when mastitis (OR = 1.31, CI: 1.19 - 1.45) or long ICI (OR = 1.34, CI: 1.22 - 1.48) occurred. For each health indicator, herd-level risk factors had an important role (18-56% of within-herd covariance). Our results indicate that milk analysis could be also useful for predicting mastitis, its cure rate, and ketosis. Cow-level risk factors are not enough to explain the risk of these issues. By studying a large population over a long period, this study provides an updated estimate of dairy cow health indicators in Piedmont (north-western Italy), useful for benchmarking dairy herds.

Success rate of artificial insemination, reproductive performance and economic impact of failure of first service insemination: a retrospective study

Background

A retrospective cohort study using a 10 year artificial insemination (AI) and cow reproductive performance data was conducted to study the success rate of AI; associations between effectiveness of AI and breed, AI season and, number of service per conception, and economic impact of failure of FSC in Dessie town, Dessie zuria and Kutaber districts. A total of 3480 dairy cows’ AI and reproductive performance records which were performed between 2003 and 2013 in the three selected districts of South Wollo were used. The economic losses and costs for cows that failed to conceive at their first AI associated with the larger number of days open were estimated.

Result

The prevalence of conception has a statistically significant difference between breeds of cows (P = 0.019). The non-return rate for first service was 58.54%. The median days to first service (DFS), inter-service interval (ISI) and gestation length (GL) were 126, 30 and 278 days respectively. Whereas, the mean + SD days open, calving interval (CI), number of inseminations (NOI) and number of services per conception (NSPC) were 147.2 ± 60.26, 424.5 ± 60.55, 1.14 ± 0.38 and 1.15 ± 0.39 respectively. Based on AI season there was a significant difference in conception between winter and spring (P = 0.021). There is a 45.04 days extension in the mean calving to conception interval in cows that did not conceive at their first AI but conceived by 2nd and 3rd AI than in cows that did conceive at their first AI. A total of 21,665.3 ETB extra costs was spent on reproductive treatment and other management for cows that failed to conceive at their first AI but conceived by second and third service. In cows that did not conceive totally the owner losses on average 473.7 ETB per cow per day extra costs until the cows will be culled.

Conclusion

Therefore to increase the conception rate and decrease the economic loss the owners of the dairy cows should supervise the cows regularly and should be trained on how to identify cows on estrous, the AI technicians should be trained to conduct the AI service accurately.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12917-022-03325-1.

Resynchronizing the first eligible estrus in dairy cattle after a prior insemination and fertility of the prior insemination after gonadotropin-releasing hormone and progesterone treatments

The hypothesis of this study tested whether application of designed treatments to synchronize estrus in nonpregnant previously inseminated lactating dairy cows increased the proportion of nonpregnant cows in estrus before early pregnancy diagnosis on Day 32 after the previous insemination (Day 0) and increase fertility of the pretreatment insemination. A progesterone insert (CIDR) and GnRH were applied to cows after insemination to resynchronize the returning estrus of cows that failed to conceive on Day 0. The combination of GnRH (Day 14) and a CIDR insert (d 17 through 24) in experiment 1 (n = 347 cows) did not increase (P = 0.13) the proportion of nonpregnant cows returning to estrus before pregnancy diagnosis, but increased (P < 0.01) the synchrony of their return by 24.4% points, and delayed (P < 0.01) that return by 2.3 ± 0.3 d compared with controls. Ovulation risk after GnRH treatment on Day 14 was only 10%. For cows that failed to return to estrus before Day 32, progesterone concentration on Days 14 and 17 were less than that in cows that returned to estrus by Day 32 and in pregnant cows. Cows that returned to estrus had larger follicles and fewer numbers of CL on Day 21 than pregnant cows and cows that failed to return to estrus, but concentrations of pregnancy-associated glycoproteins on Day 28 indicated that cows failing to return to estrus were likely pregnant but suffered embryo death. In experiment 2 (n = 881), use of GnRH alone (Day 7), a CIDR insert alone (Days 14 through 21), or in combination, failed to increase the proportion of nonpregnant cows in estrus before pregnancy diagnosis on Day 32 compared with controls. Cows receiving the CIDR insert had increased (P < 0.01) synchrony of estrus by 24-34% points compared with cows that did not receive a CIDR insert. More cows receiving GnRH had 2 or more CL on Days 14 and 21 compared with controls. Ovulation risk after GnRH on Day 7 was greater than 66%. In both experiments combined, treatments with GnRH or GnRH + CIDR insert increased (P = 0.015) pretreatment pregnancy per AI by 7.1% points, but did not affect pregnancy loss. Although administering GnRH with or without a CIDR insert synchronized returns to estrus, treatments failed to increase the proportion of nonpregnant cows reinseminated before pregnancy diagnosis, but increased pretreatment pregnancy risk.

Timing of early resynchronization protocols affects subsequent pregnancy outcome in dairy cows

The aim of this study was to evaluate the outcomes of an early resynchronization protocol (Resynch) initiated at different timepoints after timed artificial insemination (TAI) and with unknown pregnancy status. Holstein cows (n = 164) were submitted to the following TAI protocol: D0, insertion of an intravaginal progesterone (P4) device and 2 mg im estradiol benzoate (EB); D8, removal of P4 device and treatment with 0.5 mg im sodium cloprostenol (PGF); D9, 0.1 mg im Lecirelin (LEC); and D10, TAI1. Cows were then randomly assigned to Resynch protocols starting either on day 20 (Resynch20D, n = 82) or 25 after TAI1 (Resynch25D, n = 82) with the insertion of a new P4 device and EB treatment. In both groups, P4 device was removed on day 8 after the beginning of Resynch, the same day of pregnancy diagnosis by ultrasonography. In pregnant cows there was no further action. Non-pregnant cows were treated with 0.5 mg im PGF, had a blood sample collected for serum P4 analysis and we measured and recorded the size of the largest follicle and the presence or absence of a corpus luteum (CL). One day later, cows were treated with 0.1 mg im LEC and TAI2 occurred 12-14 h later. The diameter of the largest follicle and serum P4 were compared between groups by ANOVA for the main effects of treatment, presence of a CL, and their interaction, whereas pregnancy per artificial insemination (P/AI) and the percentage of cows with a CL on the day of ultrasonography were analyzed using the Chi-square test. Follicle diameter on day 8 of Resynch was greater for cows in the Resynch20D group compared with Resynch25D (15.9 ± 3.9 vs 12.2 ± 2.5 mm, respectively; P = 0.046). The Resynch25D group had a greater percentage of cows with a CL (51.9 vs 18.9%, respectively; P = 0.0008) and higher serum P4 (2.8 ± 1.1 vs 1.7 ± 0.8 ng/mL; P = 0.041) at the end of the protocol compared with Resynch20D. P/AI at TAI1 was 35.4 and 36.6% (P > 0.10) for cows enrolled in Resynch20D and Resynch25D groups, respectively. P/AI to TAI2, after Resynch protocols, was greater in Resynch25D than Resynch20D (44.2 vs 22.6%, respectively; P < 0.05). In conclusion, starting an early resynchronization protocol 25 days after TAI increases P/AI compared with starting 20 days after TAI, and this was associated with a presumed greater proportion of cows with a functional CL at the moment of P4 device removal.

Reproductive Performance in a Selected Sample of Dairy Farms in Una-Sana Canton, Bosnia and Herzegovina

Background

The production of milk and dairy products and their placement on the market represent a constant profit for the farmers/producers in Bosnia and Herzegovina (BH). The profitable operation of the dairy farms is influenced by the reproductive performance of the lactating animals. This study assessed individual animal reproductive characteristics in selected dairy farms and described their reproductive performance indicators.

Results

The median age at first insemination was 493 days (5^th–95^th percentile range 429–840), while the age at first calving was 802 days (5^th–95^th percentile range 708–1168). The median pregnancy proportion at first insemination was 40% (5^th–95^th percentile range 17–62), while the cumulative pregnancy rate calculated at day-60, day-80, day-100, and day-120 showed that approximately 64% of all pregnancies happened before day-120. The calculated interservice intervals showed that approximately 69% of the repeat breeding animals came back to the oestrus in the period of 18 to 24 days. This is an indication of very good oestrus detection in selected dairy farms. The mean number of services per pregnancy was 2.61 (range 1–12). The median calving-to-first-insemination interval was 62.5 days (5^th–95^th percentile range 16–408). The calving-to-conception interval was 101 day (5^th–95^th percentile range 36–506). Finally, the calving interval was 385 days (5^th–95^th percentile range 329–773).

Conclusions

There is a need for an organised, regular, and more comprehensive recording system for the reproduction of dairy cattle among dairy farms in Una-Sana Canton. The calculated reproductive measures indicated an undulant trend in reproductive performance among selected dairy farms in Una-Sana Canton. Knowing the apparent reproductive indicators described in this study, the farmers and veterinary authorities may identify and correct areas in their management that contribute to the reproductive underperformance.

Genetic and genomic analysis of long insemination interval in Israeli dairy cattle as an indicator of early abortions

One of the causes of observed low fertility is embryo loss after fertilization. Previous findings suggested that more than half of fertilizations result in embryo loss before pregnancy is detected. We proposed reinsemination between 49 and 100 d after the first insemination as an indicator trait for early abortion (EA) in dairy cattle based on the mean estrus interval of 21 d. This trait was compared with conception rate from first insemination and conception status, computed as the inverse of the number of inseminations to conception. Animal model variance components were estimated by REML, including parents and grandparents of cows with records. First-parity heritability for first insemination conception rate was 3%. In the multitrait analysis of parities 1 to 3 for putative EA, heritabilities ranged from 8.9% for first parity to 10.4% for second parity. All genetic correlations were >0.9, whereas all environmental correlations were <0.12. The variance component for the service sire effect for putative EA rate was less than half the variance component for conception rate. Thus, genetic control of the 2 traits is clearly different, and analysis of EA rate by a single-trait animal model is justified. Genetic evaluation for putative EA was computed using this model, including all first- through third-parity cows with freshening dates from January 1, 1985, through December 31, 2016, that either became pregnant on first insemination or were reinseminated between 49 and 100 d after the first insemination. All known parents and grandparents of cows with records were included in the analysis. The regression of the breeding value for non-abortion rate on the cows' birth year was 0.083%/yr. The genetic correlation between first-parity EA and conception status was 0.995. The genetic correlations between first-parity EA and milk, fat, and protein production were all negative, whereas the genetic correlation between EA and herd life was 0.33. Inclusion of putative EA in the selection index instead of conception status resulted in 10 to 20% greater genetic gain for both fertility traits. In a genome-wide association study based on 1,200 dairy bulls with reliabilities >50% for abortion rate genotyped for 41,000 markers, 6 markers were found with nominal probabilities of <10^-12 to reject the null hypothesis of no effect on EA rate. The markers with the lowest probabilities for EA rate were also included among the markers with the lowest probabilities for female fertility, but not vice versa. The marker explaining the most variance for abortion rate is located within the ABCA9 gene, which is found within an ATP-binding cassette (ABC) genes cluster. The ABC family is the major class of primary active transporters in the placenta.

Association of lameness and mastitis with return-to-service oestrus detection in the dairy cow

Oestrus detection is an important part of maintaining efficient reproductive performance in dairy herds. Both lameness and mastitis are common diseases of dairy cows that may impact oestrus detection. A set of data from 28 herds identified as having good recording of clinical mastitis and lameness incidents was used for the study. Logistic regression was used to identify associations between disease episodes within 100 days of insemination and changes in the probability of reinsemination at either 18-24 or 19-26 days after an unsuccessful insemination. Population attributable risk was calculated to understand the impact these diseases may have at a herd level. Lameness 0-28 days after the first insemination of the interval decreased the odds of a reinsemination at an appropriate time by approximately 20 per cent. Clinical mastitis 1-28 days prior to the first insemination of the interval increased the odds of reinsemination at the expected time by approximately 20 per cent. The associations were similar for either interservice interval outcome. Population attributable risk suggested that the effect of these diseases on the probability of reinsemination at the expected time at a population level would likely be extremely small.