scholarly journals Evaluation of reproductive health status in government and commercial dairy herds of Bangladesh

2015 ◽  
Vol 1 (1) ◽  
pp. 31-38
Author(s):  
Mohammad Liaquat Osman Mojumder ◽  
Jalal Uddin Ahmed ◽  
Md Musharraf Uddin Bhuiyan ◽  
Md Jahid Hasan ◽  
Md Showkat Ali
Keyword(s):  
Health Status ◽  
Dairy Farm ◽  
Mean Value ◽  
Conception Rate ◽  
Calving Interval ◽  
Optimum Level ◽  
Herd Health ◽  
Cattle Breeding ◽  
Service Conception ◽  
Calf Mortality

To evaluate the reproductive herd health status, the data were collected from Talbag Dairy Farm, Savar; Bangladesh Agricultural University Dairy Farm, Mymensingh and Central Cattle Breeding and Dairy Farm, Savar for a period of two years. A total of 122 lactating cows were selected to collect data on productive and reproductive performance from the farms record book maintained by three farms. The mean value ± SD of breeding age, calving age, age at first conception, calving to first estrus, calving to first service, days open, calving interval, first service conception rate, number of service per conception, calf per year of Talbag Dairy Farm, BAU Dairy Farm, Central Cattle Breeding and Dairy Farm were 25.10 ± 2.68, 219.23 ± 12.23 and 27.40 ± 7.56 months; 34.30 ± 8.54, 55.88 ± 11.60 and 38.93 ± 8.58 months; 26.20 ± 4.05, 52.71 ± 12.55 and 29.83 ± 8.72 months; 165.00 ±73.82, 219.23 ± 121.83 and 190.50 ± 104.19 days; 165.00 ±73.82, 240.77 ± 128.59 and 190.50 ± 104.19 days; 201.00 ± 72.48, 250.38 ± 72.82 and 335.08 ± 118.61 days; 383.30 ± 57.87, 526.44 ± 196.80 and 523.17 ± 216.37 days; 73.50 ± 29.25, 64.75 ± 30.53 and 61.85 ± 31.87 %; 1.95 ± 0.44, 1.99 ± 0.72 and 2.30 ± 1.02; 383.30 ±57.87, 526.44 ± 196.80 and 523.17 ± 216.37 days, respectively. The overall calf mortality (%) in Talbag Dairy Farm, BAU Dairy Farm, Central Cattle Breeding and Dairy Farm were 4%, 0.70% and 4.06%, respectively. The calf mortality (%) at birth and birth to 30 days in Talbag Dairy Farm, BAU Dairy Farm, Central Cattle Breeding and Dairy Farm were 3%, 1% and 1.85%; 3.5%, 5% and 6.39%; respectively. It is concluded that commercial farms reasonably better due to optimum level of breeding age, first service conception rate, less calving interval and less service per conception.Asian J. Med. Biol. Res. June 2015, 1(1): 31-38

scholarly journals Semen characteristics of breeding bulls at the Central Cattle Breeding and Dairy Farm of Bangladesh

2012 ◽  
Vol 41 (1) ◽  
pp. 1-5
Author(s):  
ME Hossain ◽  
MM Khatun ◽  
MM Islam ◽  
OF Miazi
Keyword(s):  
Sperm Concentration ◽  
Chemical Properties ◽  
Dairy Farm ◽  
Mean Value ◽  
Cattle Breeding ◽  
Bull Semen ◽  
Before And After ◽  
The Mean ◽  
Physical And Chemical ◽  
And Chemical Properties

The experiment was conducted on 97 breeding bulls at the central cattle breeding and dairy farm, Savar, Dhaka to find out the physical and chemical properties of different bull semen. Out of 97 bulls, 9 were Local (L), 9 were Friesian (F), 13 were Sahiwal (SL), 12 were Local×Friesian (L×F), 10 were Sahiwal×Friesian (SL×F), 26 were Local×Friesian×Friesian (LF1×F), 18 were Local×Friesian× Friesian×Friesian (LF2×F) bulls. The semen of different crossbred and local bulls was examined for ejaculate volume, concentration, pH and motility percent of sperm before and after freezing. It was observed that, the maximum average ejaculate was obtained from SL×F and the mean value was 12.9 ml. However, the minimum average ejaculate was obtained from LF×F and the mean value was 7.4 ml. Before freezing, the maximum average sperm concentration was obtained from SL and the mean value was 1858.4 million/ml. The minimum average sperm concentration was obtained from LF1×F and the mean value was 1286.6 million/ml. The maximum average pH was obtained from LF2×F and the mean value was 6.5. The maximum average motility was obtained from SL and the mean value was 68.8%. However, the minimum average motility was obtained from L×F and the mean value was 63.7%. After freezing, sperm concentration, pH and motility reduced substantially irrespective of type of breed. It could therefore be inferred that freezing of semen should be undertaken with special care to maintain optimum semen quality.http://dx.doi.org/10.3329/bjas.v41i1.11968

scholarly journals Morphological sperm abnormalities of different breeds of AI bull and its impact on conception rate of cows in AI programme

1970 ◽  
Vol 2 (2) ◽  
pp. 129-135 ◽  
Author(s):  
MJU Sarder
Keyword(s):  
Artificial Insemination ◽  
Morphological Characteristics ◽  
Dairy Farm ◽  
Conception Rate ◽  
Genetic Groups ◽  
Sperm Abnormalities ◽  
Total Head ◽  
Service Conception ◽  
Positive Correlations ◽  
Rectal Palpation

The main objective of this study was to evaluate the effect of genetic groups of bulls on morphological characteristics of spermatozoa in relation to conception rate of first inseminated cows. For this purpose, 1390 ejaculates of semen were collected from 71 bull of six genetic groups at Central Cattle Breeding Station and Dairy Farm (CCBSDF), Savar, Dhaka; Rajabarihat Dairy Cattle Improvement Farm (RDCIF), Rajshahi, and District Artificial Insemination Centre, Rajshahi, from January 1997 to March 2002. A total of 20936 cows were inseminated by 40 technicians of different AI Sub-centre or points under the District Artificial Insemination Centre, Rajshahi, and pregnancy was confirmed on rectal palpation at 90 to 120 days after insemination. The average values of total head abnormalities, free loose head, mid-piece, tail abnormalities, proximal and distal cytoplasmic droplets, total tail abnormalities and total sperm abnormalities were 5.45%, 2.44%, 1.19%, 6.19%, 0.74%, 0.57%, 11.16% and 16.38%, respectively. Genetic groups of bull had significant (p < 0.05) effect on all the morphological characteristics of spermatozoa. The lower incidence of total sperm abnormalities (13.45%) was found in the genetic groups of 100% SL and higher (19.28%) in 75% F x 25% L bulls. The genetic groups of bulls had significant effect on first service conception rate of cows. The conception rate was higher in cows inseminated with 100% Local than those inseminated with genetic groups of 75% F x 25% L (53.13% vs 45.88%; p < 0.05). Significantly strong positive correlations were found between total head abnormalities and total sperm abnormalities (r = 0.828; p < 0.01) as well as between total tail abnormalities and total sperm abnormalities (r = 0.892; p < 0.01). It appears from the results that minimum total sperm abnormalities are found for pure breed bulls than cross-bred bulls, and 100% Local, 100% Friesian and 50% SL x 50% F bulls had better conception rates on cows.Key words: Spermatozoa; abnormalities; bull; genetic group; AI; conception ratedoi: 10.3329/bjvm.v2i2.2555Bangl. J. Vet. Med. (2004). 2 (2): 129-135

Reproductive Performance and Repeatability Estimation of Some Traits of Crossbred Cows in Savar Dairy Farm

2018 ◽  
Vol 10 (2) ◽  
pp. 87-94
Author(s):  
MS Islam ◽  
A Akhtar ◽  
MA Hossain ◽  
MF Rahman ◽  
SS Hossain
Keyword(s):  
Post Partum ◽  
Dairy Farm ◽  
Reproductive Traits ◽  
Calving Interval ◽  
Cattle Breeding ◽  
Crossbred Cows ◽  
Genetic Groups ◽  
Breeding Station ◽  
Heat Period ◽  
Age At Puberty

The study was conducted on 244 crossbred cows of CCBS Savar, Dhaka to evaluate the effect of different genetic groups on their lifetime performance of various reproductive traits using twenty years data. Data were accumulated from a prescribed data sheet maintained by Central Cattle Breeding Station, Dhaka. Genetic groups for this experiment were (LF), (LJ), (LH x F), (LF x LF) and (LJ x LJ). The studied parameters were age at puberty, service per conception, post-partum heat period, calving interval, total number of calving in lifetime. ANOVA showed that genetic groups had a significant effect on age at puberty, post-partum heat period, total number of calving in lifetime and calving interval (P<0.05). From result it was found that earliest age at puberty were in L x F (749.27±99.01), service per conception, postpartum heat period was lower in L x F (1.60±0.19 and (145.75±94.44 days respectively). Calving interval was lower in L x J (411.18±136.87 days) and almost similar results were obtained for L x F (432.26±96.26 days). Total number of calving in lifetime were observed higher in (LH x F) with mean of 1468.30±198.58 days.J. Environ. Sci. & Natural Resources, 10(2): 87-94 2017

scholarly journals Studies on Treatments Results from Cows with Ovarian Disorders in Relation to Year and Season

2012 ◽  
Vol 45 (3) ◽  
pp. 87-100
Author(s):  
Elena Ruginosu ◽  
Mariana Sofronie ◽  
I. Borş ◽  
Şt. Creangă ◽  
L. Dascălu
Keyword(s):  
Heat Stress ◽  
Annual Variation ◽  
Dairy Farm ◽  
Dairy Farms ◽  
Cold Season ◽  
Conception Rate ◽  
Active Movement ◽  
Cattle Breeding ◽  
Annual Variations ◽  
Conception Rates

Abstract The studies were performed in the dairy farm from Dancu Research and Development Station for Cattle Breeding, Iaşi, Romania, for a period of 5 consecutive years (2007- 2011), an effective annual rolled of 450 cows Bălţată cu Negru Românească (Romanian Black Spotted) breed.The experimental groups were composed of cows with anoestrus in 60 days postpartum interval, diagnosed by rectal examination with various ovarian disorders: persistent corpus luteum - group E1-162 cows and luteal cysts- group E2-138 cows. The treatments according to diagnosis were applied: PGF2α-,500 mcg/cow- group E1 and Gn-RH, (Receptal, 5 ml/cow-group E2). In relation to the year in which treatments were applied some variations in reproduction indices were found. Regarding to average intervals from treatment to first insemination and from treatment to conception respectively, significant differences were not found. Regarding to average conception rates after treatments, significant differences were found: in E1group, conception rate at the first insemination was 30,9% (with annual variations between 15,0% in 2008 and 41,1% in 2009) (p<0,01); per total insemination was 64,42 % (with annual variations between 44,7% - 2011 and 76,9% - 2007) (p<0,001) and pregnancy index was of 2,4 (with annual variations between 1,9 - 2009 and 2,8 - 2008); in E2 group, conception rate to first insemination was 25,96% (with annual variations between 16,66% - 2011 and 40% - 2010) (p<0,01); per total insemination was 77,88% (with annual variation between 52,17% - 2008 and 85,0% - 2010) (p<0,001) and pregnancy index of 2,4 (with annual variations between 2,1 - 2007 and 2,6 - 2008 and 2009). In relation to season in which treatments were applied, we found different variations in conception rates: in group E1, the average conception rates at the first insemination were between 24,24 % (autumn) and 40,7% (summer) (p<0,05) and per total inseminations between 75,0% (spring) and 85,71% (autumn) (p<0,05); in group E2, the average conception rates at the first insemination were between 5,3% (summer) and 48,5% (spring) (p<0,001) and per total inseminations between 68,4% (summer) and 81,8% (spring) (p<0,05). We believe that annual and seasonal variations found in this work are due to some deficiencies of management system in dairy farms, such as the stalls prolonged maintenance and lack of active movement in the cold season, inadequate microclimate of shelters, heat stress and deficiencies in cows feeding , especially those with higher milk production.

scholarly journals 260 Genetic prediction for first-service conception rate in Angus heifers using a random regression model

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 197-198
Author(s):  
Miguel A Sánchez-Castro ◽  
Milt Thomas ◽  
Mark Enns ◽  
Scott Speidel
Keyword(s):  
Conception Rate ◽  
Random Regression ◽  
State University ◽  
Base Function ◽  
Genetic Prediction ◽  
Colorado State University ◽  
Random Regression Model ◽  
Service Conception ◽  
Available Information ◽  
Angus Heifers

Abstract First-service conception rate (FSCR) can be defined as the probability of a heifer conceiving in response to her first artificial insemination (AI). Given the binary nature of its phenotypes, FSCR has been typically evaluated using animal threshold models (ATM). However, susceptibility of these models to the extreme-category problem (ECP) limits their ability to use all available information to calculate Expected Progeny Differences (EPD). Random regression models (RRM) represent an alternative method to evaluate binary traits, and they are not affected by ECP. Nevertheless, RRM were originally developed to analyze longitudinal traits, so their usefulness to evaluate traits with singly observed phenotypes remains unclear. Therefore, objectives herein were to evaluate the feasibility of a RRM genetic prediction for heifer FSCR by comparing its resulting EPD and genetic parameters to those obtained with a traditional ATM. Breeding and ultrasound records of 4,334 Angus heifers (progeny of 354 sires and 1,626 dams) collected between 1992 to 2019 at the Colorado State University Beef Improvement Center were utilized. Observations for FSCR (1, successful; 0, unsuccessful) were defined by fetal age at pregnancy inspections performed approximately 130 d post-AI. Traditional FSCR evaluation was performed using a univariate BLUP threshold animal model, whereas an alternative evaluation was performed by regressing FSCR on age at AI using a linear RRM with Legendre Polynomials as the base function. Heritability estimates were 0.03 ± 0.02 for the ATM and 0.005 ± 0.001 for the average age at AI with the RRM, respectively. Pearson and rank correlations between EPD obtained with each method were 0.63 and 0.60, respectively. The regression coefficient of RRM predictions on those obtained with the ATM was 0.095. In conclusion, these results suggested that although a RRM genetic prediction for FSCR was feasible, a considerable degree of re-ranking occurred between the two methodologies.

scholarly journals Influence of seasonality, timing of insemination and rectal temperature on conception rate of crossbred dairy cows

2016 ◽  
Vol 37 (1) ◽  
pp. 155 ◽  
Author(s):  
Fransérgio Rocha de Souza ◽  
Carla Cristian Campos ◽  
Natascha Almeida Marques da Silva ◽  
Ricarda Maria dos Santos
Keyword(s):  
Dairy Cows ◽  
Rectal Temperature ◽  
Artificial Insemination ◽  
Dairy Farm ◽  
Fixed Time ◽  
Conception Rate ◽  
Digital Thermometer ◽  
Pregnancy Diagnosis ◽  
Chi Squared

This study aimed to evaluate the effects of rectal temperature (RT) on conception rate (CR), as well as the effects of seasonality (spring-summer vs. autumn-winter) and timing of artificial insemination (AI) (morning vs. afternoon) on RT and CR in crossbred dairy cows (Holstein x Gyr). The experiment was conducted on a dairy farm in Centralina, MG, where 1,219 conventional and fixed-time inseminations were analyzed. The RT was measured immediately before AI using a digital thermometer. Pregnancy diagnosis was performed using ultrasonography between 28 and 60 days after AI. T The effects of seasonality and timing of AI on RT were analyzed with a Mann-Whitney U test and the effects of RT (above or below the average), seasonality and timing of AI on CR were analyzed with a Chi-squared test, both using the SAS program. The RT average was 39.4°C. Cows with RT ? 39.4°C had lower CR than cows with RT < 39.4°C (25.78% vs. 32.54%; P = 0.0096). During spring-summer, cows had higher RT (39.44°C ± 0.025 vs. 39.27°C ± 0.022; P < 0.0001) and lower CR (25.49% vs. 31.75%; P = 0.0146) compared with autumn-winter. Cows inseminated in the morning had lower RT (38.96°C ± 0.022 vs. 39.60°C ± 0.018; P < 0.0001) and higher CR (32.86% vs. 26.06%; P = 0.0102) than cows inseminated in the afternoon. In conclusion, crossbred dairy cows with rectal temperature equal to or greater than 39.4°C had lower conception rate. Moreover, rectal temperature and conception rate were affected by seasonality and insemination time.

scholarly journals Productive indicators of cows and milk quality, when adding amide-vitamin-mineral concentrate to the diet

2020 ◽  
Vol 11 (2) ◽  
pp. 1511-1514
Author(s):  
Sergey Yu. Smolentsev ◽  
Galiya R Yusupova ◽  
Nikita V Nikolaev ◽  
Zaira F Aukhadieva ◽  
Renat A Volkov ◽  
...  
Keyword(s):  
Capital Investment ◽  
Dairy Farm ◽  
Feed Additive ◽  
Cattle Breeding ◽  
Black And White ◽  
Lactating Cows ◽  
Dairy Cattle Breeding ◽  
White Breed ◽  
Animal Feeding ◽  
The Republic

The effectiveness of dairy cattle breeding largely depends on the intensity of use of the breeding stock. At the same time, the factor of the duration of economic use of animals is gaining importance, which affects not only the production economy, but also the improvement of stocks and breeds. The lifelong productivity, the quantitative and qualitative growth of the stock, the amount of capital investment in its formation and the efficiency of operation depend on the term for the productive use of cows. The terms of breeding and production use of animals are direct linked with the biologically possible longevity of each animal, in turn, the duration of the productive period of cattle is in the range of 12-17 lactations. The influence of feed on production is associated primarily with the level of digestion and assimilation. The digestive capacity of the digestive tract of animals can be improved by selecting the optimal ratio in the diet of rough, juicy and concentrated feeds, i.e. optimization of animal feeding types. We conducted an analysis of milk productivity in lactating cows, when using AVMC feed additive in the diet. The experiment was conducted in the conditions of the dairy farm of Biryuli CJSC of the Vysokogorsky District of the Republic of Tatarstan on three groups of lactating cows. For the experiment, 30 cows were selected, 10 in each Holstein black-and-white breed according to the principle of analogues. Studies have shown that AVMC with rapeseed oil seeds and AVMC with fus in the diet of lactating cows provided higher animal productivity and positively affected the chemical composition of milk.

scholarly journals Health status and bio-security plans on pig farms

2010 ◽  
Vol 26 (1-2) ◽  
pp. 29-35
Author(s):  
B. Stankovic ◽  
S. Hristov ◽  
T.J. Bojkovski ◽  
N. Maksimovic
Keyword(s):  
Health Status ◽  
Security Measures ◽  
Herd Health ◽  
Swine Herd ◽  
Farm Production ◽  
Prophylactic Measures ◽  
Pig Farm ◽  
Disease Spreading ◽  
Swine Disease ◽  
Security Standards

Preservation of necessary level of swine herd health status is the most important aspect of bio-security, farm production and successful welfare protection. It involves a list of bio-security measures which must be essential part of production technology, including good rearing conditions and other prophylactic measures appliance. According to previously performed investigations, a list of elements required to establish standards for bio-security for particular pig farm was created. The list includes elements related to assure spatial., microclimate and hygienic conditions for pigs rearing, care, nutrition and watering, surveillance, regrouping and transport of swine, disease outbreak control, barns equipment and production process organization which are performed by veterinarians and zootechnicians. Bio-security standards must concern necessary level of swine herd health status and organization, size and type of operation and anticipate all compulsory measures for health control and disease spreading prevention, particularly those whose outbreak must be reported. In bio-security plan structure present epidemiological situation, potential herd health and production threats, as well as possible solutions must be concerned.

Key issues in dairy herd health management

2021 ◽  
pp. 3-26
Author(s):  
John Remnant ◽  
◽  
James Breen ◽  
Peter Down ◽  
Chris Hudson ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Business Models ◽  
Health Management ◽  
Dairy Farm ◽  
Dairy Herd ◽  
Population Level ◽  
Holistic Approach ◽  
Herd Health ◽  
Health Target ◽  
Cow Health

Dairy herd health management benefits dairy farmers, the environment, dairy cows and citizens. It is an important part of modern dairy farm veterinary care. Dairy herd health management is assessing, monitoring and improving the health of dairy cows at a population level. Good herd health management takes a holistic approach and is ongoing and cyclical. All members of the dairy farm team and their advisors are involved, decisions are informed by data generated by the herd. These data may come from numerous sources. The data are processed and analysed to monitor cow health, target investigations and evaluate progress. To make lasting change on farms, advisors must communicate appropriately with farm managers to understand behaviour and motivate change. This chapter reviews these aspects of dairy herd health management, giving practical suggestions on how to get started, how to incorporate herd health management into business models and how to maintain momentum.

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