Insemination factors affecting the conception rate in seasonal calving Holstein-Friesian cows

Buckley, F.; Mee, John F.; O’Sullivan, Kathleen; Evans, R.D.; Berry, D.P.; Dillon, P.

doi:10.1051/rnd:2004002

Cited by 32 publications

(19 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Do-it-yourself AI was not found to be associated with the chance of pregnancy at VWP plus 30 d, which is in contrast to our previous results (Löf et al, 2007b) and to the results of McCoy et al (2006). However, Buckley et al (2003a) recorded no difference between AI by technicians and DIY AI by farmers in terms of pregnancy rates with first inseminations in well-managed herds. In the model, we controlled for many factors, some of which might have co-varied with herds using DIY AI, even though we found no indications of collinearity between predictor variables.…”

Section: Comparisoncontrasting

confidence: 99%

Factors influencing the chance of cows being pregnant 30 days after the herd voluntary waiting period

Löf

Gustafsson

Emanuelson

2014

Journal of Dairy Science

View full text Add to dashboard Cite

The objective of this study was to study factors affecting a reproductive performance indicator at the cow level adjusted for herd management strategy. Associations between the outcome variable, pregnant or not at the herd voluntary waiting period (VWP) plus 30d (pregnant at VWP+30), and the predictor variables were analyzed using a multivariable, generalized estimation equations model that adjusted for clustering of the data at the herd level. The statistical analysis was stratified on parity. In total, 132,721 cows were retained for analyses, of which 29,113 (22%) were pregnant at VWP+30d. Of the nonpregnant cows, 81,483 cows had records of artificial inseminations (AI) and 22,125 cows had no records of AI. The chance of pregnancy was higher for cows of the Swedish Red and for other/crossbreeds compared with Swedish Holstein, for cows from herds with high heat detection efficiency compared with cows from herds with medium and low heat detection efficiency, for cows from herds with long VWP (i.e., >51d) compared with cows from herds with short VWP (<51d), and for cows in freestalls compared with cows in tiestalls. The chance for pregnancy was lower for cows with severe problems at claw trimming compared with cows with no problems at trimming (only for second- and higher-parity cows), for cows that had a record of reproduction-related disease, for cows that had a record of any other disease compared with cows without record, for second- and higher-parity cows with records of dystocia compared with cows with no record of dystocia, for first-parity cows in the group with the highest milk yield compared with first-parity cows in the group with the lowest milk yield, for cows of third and higher parity in the group with the lowest milk yield compared with cows in higher yielding groups, for cows bred in summer compared with those bred in winter-spring (not significant for first-parity cows), and for cows with a twin birth had compared with cows with a single birth. We observed associations of the dose-response type, such that when the milk fat-to-protein ratio increased, the chance for pregnancy decreased, and as the somatic cell count increased, the chance for pregnancy decreased. In conclusion, factors that are known to affect reproductive efficiency also affect the chance of cows being pregnant at the herd VWP plus 30d.

show abstract

Section: Comparisoncontrasting

confidence: 99%

Factors influencing the chance of cows being pregnant 30 days after the herd voluntary waiting period

Löf

Gustafsson

Emanuelson

2014

Journal of Dairy Science

View full text Add to dashboard Cite

show abstract

“…This would ensure that the number of insemination doses per ejaculate is maximised, thus resulting in an increase in the use of individual sires. In contrast to the results of this study, previous studies have shown that similar conception rates can be achieved with liquid and frozen-thawed semen [31] and that NRRs of liquid and frozen-thawed semen diluted to 2.5 x 10 6 and 20 x 10 6 sperm, respectively, do not differ up to Day 2 of storage [32]. However, over-compensation of sperm numbers typically occurs in the preparation of frozen-thawed semen, resulting in a sperm concentration which considerably exceeds the number of sperm necessary for maximum fertility, thus, masking the 'true fertility' potential of a bull [33].…”

Section: Accepted Manuscriptcontrasting

confidence: 99%

Effect of storage temperature, nitrogen gassing and sperm concentration on the in vitro semen quality and in vivo fertility of liquid bull semen stored in INRA96

et al. 2018

View full text Add to dashboard Cite

The aim of this study was to assess the effect of storage temperature, nitrogen (N) gassing and sperm concentration on in vitro characteristics and calving rate (CR) following artificial insemination (AI) of liquid bull semen stored in INRA96. In Experiment 1 the effect of liquid bull semen diluted in either N bubbled or non-bubbled INRA96 at a concentration of 5 × 10 sperm per 0.25 mL insemination dose and stored at 5 or 15 °C was assessed subjectively for total and progressive motility on Days 0, 1, 2, 3 and 4 post collection. In Experiment 2a, the effect of stored liquid semen at three sperm concentrations (3, 4 or 5 × 10 sperm per 0.25 mL insemination dose) on total and progressive motility was assessed subjectively on Days 0, 1 and 2 post collection. In Experiment 2b, the field fertility of liquid semen stored at ambient temperature at a concentration of 3, 4 or 5 × 10 sperm per 0.25 mL dose and inseminated on Days 1 or 2 post collection was assessed in comparison to frozen-thawed semen (total of n = 5742). In Experiment 1, total and progressive motility decreased with increased duration of storage (P < 0.01); however, there was no effect of N bubbling on motility on Days 0, 1, 2, 3 and 4 of storage. There was an effect of temperature on total and progressive motility, regardless of treatment, as semen stored at 15°C recorded higher motility values than semen stored at 5°C (P < 0.01). In Experiment 2a, there was no effect of sperm concentration on total or progressive motility on Days 0, 1 or 2 of storage. There was a linear decrease in motility with increased duration of storage (P < 0.01); however, there was no sperm concentration by day interaction. In Experiment 2b, there was an effect of sperm concentration on CR (P < 0.01); semen diluted to 3 and 4 × 10 sperm per dose resulted in a lower CR after 2 days of storage (41.1 and 44.7%, respectively) in comparison to frozen-thawed semen (55.2%) but did not differ to CR of semen diluted to 5 × 10 sperm per dose on Day 2 of storage. There was an effect of parity, fertility sub-index and days in milk (DIM) at AI on CR (P < 0.01). In conclusion, N bubbling and sperm concentration had no effect on in vitro sperm motility of liquid semen, but this study demonstrated a reduction in CR on Day 2 of storage at lower sperm concentrations in comparison to frozen-thawed semen.

show abstract

“…These results show that the change to DIY inseminations could have negative effects on reproductive performance, which is in agreement with a study by McCoy et al (2006), who suggested that poor DIY techniques contributed to impaired reproductive performance on dairy farms in Northern Ireland. In contrast, Buckley et al (2003) recorded no difference between farmers and AI technicians in pregnancy rates to first inseminations in well-managed herds. Our results, however, indicate that DIY inseminations must be regarded as a risk factor for decreasing reproductive efficiency and that herds using DIY insemination should be closely supervised.…”

Section: Associations Between Herd Characteristics and Reproductive Ementioning

confidence: 76%

Associations Between Herd Characteristics and Reproductive Efficiency in Dairy Herds

Löf

Gustafsson

Emanuelson

2007

Journal of Dairy Science

View full text Add to dashboard Cite

Dairy herds worldwide are experiencing a decline in reproductive efficiency at the same time as management methods are changing. This study aimed to investigate the extent to which herd-level characteristics were associated with reproductive performance. Data from herds using artificial insemination (AI) in the Swedish Official Milk Recording Scheme that had more than 45 cows were included in the study (total of 2,728 herds). Reproductive performance was measured as the average for each herd for the calving interval, calving to first AI interval, calving to last AI interval, number of AI per animal submitted for AI, and culling attributed to reproductive problems. Herds with mainly Swedish Holstein cows had longer calving intervals, calving to first AI, and calving to last AI compared with herds with mainly Swedish Red and White cows. Large herds had shorter calving to first AI but a greater number of AI than small herds, whereas small herds had greater culling attributed to reproductive problems than large herds. Low-yielding herds had longer calving intervals, calving to first AI, and calving to last AI and had greater culling attributed to reproductive problems than high-yielding herds, whereas herds with high milk yields had a greater number of AI than low-yielding herds. Herds with automatic milking systems had shorter calving intervals, calving to first AI, and calving to last AI and had lesser odds for culling attributed to reproductive problems when compared with herds with ordinary pipeline milking systems. Herds that used Advanced Feed Advisory Services had shorter calving to first AI but a greater number of AI and greater culling attributed to reproductive problems. Herds using TMR had longer calving intervals and calving to last AI than herds that did not. Herds with tie stalls had longer calving intervals, calving to first AI, and calving to last AI, and organic herds had shorter calving intervals, calving to first AI, and calving to last AI compared with conventional herds. We found that herds with do-it-yourself inseminations had longer calving intervals and calving to first AI. Our study showed numerous associations between herd characteristics and reproductive performance. When allocating advisory service resources to improve reproductive performance, the focus should be on herd characteristics that are easy to influence, such as TMR and do-it-yourself inseminations.

show abstract

Insemination factors affecting the conception rate in seasonal calving Holstein-Friesian cows

Cited by 32 publications

References 39 publications

Factors influencing the chance of cows being pregnant 30 days after the herd voluntary waiting period

Factors influencing the chance of cows being pregnant 30 days after the herd voluntary waiting period

Effect of storage temperature, nitrogen gassing and sperm concentration on the in vitro semen quality and in vivo fertility of liquid bull semen stored in INRA96

Associations Between Herd Characteristics and Reproductive Efficiency in Dairy Herds

Contact Info

Product

Resources

About