The Effect of Introducing Estrus Detection System on Hanwoo Industry

2019 ◽  
Vol 46 (2) ◽  
pp. 168-187
Author(s):  
Ho Young Rho ◽  
Jun Byeong Hwang ◽  
Ye Bon Cha ◽  
Hong Seok Seo ◽  
Chung Hyeon Kim ◽  
...  
2001 ◽  
Author(s):  
Yu-Yao Hu ◽  
Chu-Yang Chou ◽  
Yan-Nian Jiang ◽  
Chih-Hua Wang

2015 ◽  
Vol 16 (9) ◽  
pp. 6236-6246 ◽  
Author(s):  
Suc-June Kim ◽  
Sun-Ho Jee ◽  
Hyun-Chan Cho ◽  
Chun-Su Kim ◽  
Hyeon-Shup Kim

1998 ◽  
Vol 81 (7) ◽  
pp. 1874-1882 ◽  
Author(s):  
M.B.G. Dransfield ◽  
R.L. Nebel ◽  
R.E. Pearson ◽  
L.D. Warnick

2018 ◽  
Author(s):  
Ines Adriaens ◽  
Wouter Saeys ◽  
Chris Lamberigts ◽  
Mario Berth ◽  
Katleen Geerinckx ◽  
...  

Both estrus detection and timely insemination are important factors in optimizing fertility management. The latter is dependent on ovulation time, which is preceded by the LH surge. The performance of an estrus detection system based on activity and based on milk progesterone was evaluated and the timing of the alerts was contrasted against the moment of the LH surge. Activity alerts had a sensitivity of 83% and a positive predictive value of 66%; the LH surge followed average 9.4 ± 16.1 hours later. Using milk progesterone, one can reliably detect luteolysis, which is followed by the LH surge after 62 ± 12 hours.


2005 ◽  
Vol 17 (2) ◽  
pp. 254
Author(s):  
D.J. Schafer ◽  
J.F. Bader ◽  
D.C. Busch ◽  
F.N. Kojima ◽  
M.R. Ellersieck ◽  
...  

The objective of this experiment was to determine the feasibility in substituting EAZI-BREED CIDR inserts (CIDR; Pfizer Animal Health, Groton, CT, USA) for melengestrol acetate (MGA) in progestin-based protocols to synchronize estrus in beef cows. Follicular dynamics, timing of estrus, and ovulation were compared in beef cows synchronized to ovulate first or second wave dominant follicles using short- or long-term MGA- or CIDR-based protocols. The study was conducted with 48 nonsuckled, estrous cycling, crossbred beef cows assigned to one of four treatments (T1 to T4; n = 12/T) by age and body condition. Cows were synchronized to ovulate first wave (T1 and T2) or second wave (T3 and T4) dominant follicles based on assignment to treatment. Cows in T1 were fed MGA (0.5 mg h−1 d−1) for 7 days, and were injected with PGF2α (PG; 25 mg Lutalyse; Pharmacia Animal Health, Kalamazoo, MI, USA) on Day 7, GnRH (100 μg Cystorelin; Merial, Athens, GA, USA) on Day 11, and PG on Day 18. Cows in T2 had CIDR (1.38 g progesterone) inserted for 7 days, and were injected with PG on Day 7, GnRH on Day 9, and PG on Day 16. Cows in T3 were fed MGA for 14 days, and were injected with GnRH on Day 26, and PG on Day 33. Cows in T4 had CIDR inserted for 14 days, and were injected the GnRH on Day 23, and PG on Day 30. Transrectal ultrasonography was performed daily to monitor follicular dynamics from GnRH to estrus after PG; and every 4 h from 20 h after the onset of estrus until ovulation. Estrus detection was performed continuously using the HeatWatch® estrus detection system (DDx, Denver, CO, USA). Blood samples for progesterone (P4) were collected daily beginning one day prior to the initiation of treatment and continuing through ovulation following PG. Data were analyzed using the General Linear Models procedure of SAS (SAS Institute, Inc., Cary, NC, USA) and are summarized in the following table. Animals that responded to treatment and were included in the analysis were those that initiated a new follicular wave after administration of GnRH and that displayed estrus within 144 h after PG. Although estrous response was similar among treatments, there were differences in follicular dynamics, steroid secretion patterns, and timing of events that culminated in differences in timing and synchrony of estrus and ovulation among the short- and long-term groups. These differences may be important in relation to fixed-time AI programs. These data suggest that in situations that are not conducive to feeding MGA, substituting CIDR inserts into MGA-based protocols to synchronize estrus may be feasible. This work was supported by USDA-NRI grant 2000-02163; Pfizer Animal Health, New York, NY; and Merial, Athens, GA, USA.


2021 ◽  
Author(s):  
A.R. Madkar ◽  
P. Boro ◽  
M. Abdullah

Fertility over the past few decades is of serious concern in the dairy industry. Fertility of a dairy herd is determined by composite factors, which in turn depends upon effective management strategies. The reproductive potential of the animals need to be exploited to its maximum to achieve optimum production in a herd. The single most important factor that limits the establishment of pregnancy and survival of the embryo in dairy cattle and buffaloes and thereby reproductive efficiency of a herd is proper estrus detection, Pedometer or activity meter is a motion switches devices within which steps followed by animals are recorded. Activity meters can be attached to the neck or leg of cows and they may be read by a receiver and processed by computer in a milking parlour. By implementing automatic detection system, heat detection rates can be improved, for improving reproductive efficiency. The activity monitoring techniques can also be used to detect the silent ovulation which is helpful for improving efficiency and accuracy of estrus.


Author(s):  
Destaw Worku ◽  
Kefyalew Alemayehu ◽  
Mussie H/Melekote

SummaryComparative study was conducted at Alage and Ardaita Agricultural Technical and Vocational Education Training College dairy farm to evaluate the reproductive performance of Holstein Friesian (HF) and associated factors in the two farms. The data collected from 2000 to 2015 on reproductive traits (n= 1688) were analyzed using general linear model procedures of SAS version 9.2 (SAS, 2008). The result revealed that an overall least square means and standard errors for Age at first Service (AFS), Age at first calving (AFC), Calving interval (CI), Days open (DO) and Number of services per conception were 29.70 ± 0.49 months, 39.75 ± 0.53 months, 465.76 ± 7.22 days, 188.11 ± 7.22 days and 1.31 ± 0.04, respectively. AFC was significantly influenced by agro ecology (P< 0.001) and year of birth (P< 0.01). Besides this, agro ecology (P< 0.001) and year of birth (P< 0.05) was significantly influenced by AFC. Year of calving and parity had significant effect (P< 0.001) on CI and DO. Except CI, agro ecology had significant effect on all traits. Service per conception was significantly influenced by agro ecology (P< 0.05) and year of calving (P< 0.01). Season of birth and season of calving was not significant on all reproductive traits. Except SPC, the result obtained for AFS, AFC, CI and DO were below the standard expected from commercial dairy farm. Poor efficiency of estrus detection and expression were the most probable management factors accounted for longer period of AFS, AFC, CI and DO. Improving the level of nutrition as well as efficiency of estrus detection system is required for optimal reproduction performance of HF breed in the area.


2010 ◽  
Vol 22 (1) ◽  
pp. 178 ◽  
Author(s):  
J. N. S. Sales ◽  
G. A. Crepaldi ◽  
M. Fosado ◽  
E. P. Campos Filho ◽  
P. S. Baruselli

The objectives of this study were to evaluate the follicular dynamics (experiment 1) and the effects of the timing of insemination with sexed or nonsexed semen on pregnancy rates (experiment 2) of Jersey heifers detected in heat by a radiotelemetric estrus detection system. In experiment 1, 43 Jersey heifers, around 12 mo old and BCS of 2.68 ± 0.11 (1 to 5 scale) were used. The Heat Watch (HW) system was utilized to detect the onset of estrus and mounting behavior associated with estrus. Ultrasound examinations to monitor follicular dynamics occurred every 12 h from estrus onset for 48 h. Statistical analyses were performed using GLM and GLIMMIX procedure of SAS (SAS Institute, Cary, NC, USA). The results of experiment 1 indicated a mean ovulatory follicle diameter of 14.1 ± 0.3 mm, ovulation rate of 86.1% (37/43), and an interval of 31.2 ± 0.9 h from onset of heat to ovulation. In experiment 2, 753 Jersey heifers were allocated in a 2 × 4 factorial with semen (sexed and nonsexed) and AI period (0 to 6, 6 to 12, 12 to 18, and 18 to 24 h after heat onset) as parameters. Semen from 3 bulls was used, with ejaculates divided in 2 fractions: one fraction was submitted to the traditional freezing procedure and the other was submitted to the sexing process and then frozen. The statistical analysis was performed using GLIMMIX procedure of SAS. There was no interaction among the semen, bull, and AI period. There were effects on pregnancy rate by type of semen [sexed 49.5% (189/382) and nonsexed 64.2% (238/371); P = 0.001] and by bull [bull A 53.5% (107/200)b, bull B 50.0% (108/216)b and bull C 63.4% (211/333)a; P = 0.008]. Semen from bull C resulted in a greater pregnancy rate for both sexed and nonsexed semen. Within semen type, there were no differences in pregnancy rates by AI moment [sexed: 0 to 6 h 48.2% (41/85), 6 to 12 h 48.7% (54/111), 12 to 18 h 49.5% (49/99), 18 to 24h 52.4% (44/84) and nonsexed: 0 to 6h 62.8% (49/78), 6 to 12h 60.6% (63/104), 12 to 18h 68.0% (68/100), 18 to 24h 64.8% (57/88); P = 0.77]. We conclude that the use of sexed semen resulted in a lower pregnancy rate than nonsexed semen, and that AI timing does not affect conception rate in Jersey heifers identified in estrus by radiotelemetric estrus detection system. However, there was a bull effect on conception rate. The authors wish to thank Sexing Technologies and Dalhart Jersey Ranch.


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