scholarly journals Factors Affecting Twinning and the Impacts of Twinning in Cattle

2019 ◽  
Vol 29 (1) ◽  
pp. 13
Author(s):  
Lisa Praharani
Keyword(s):  
Dairy Cows ◽  
Metabolic Disorders ◽  
Genetic Factors ◽  
Calving Interval ◽  
Intensive Management ◽  
Cattle Production ◽  
Factors Affecting ◽  
High Incidence ◽  
Embryonic Loss ◽  
Pros And Cons

Efforts to increase cattle production can be done through increasing the population and productivity of cattle, one of which is through the birth of two offsprings per parent (twin). The incidence of twinning in cattle ranged 1-10%, and influenced by genetic/breed, parity, management, season of breeding. This paper presented factors and technology that increase twinning rate and the impacts of twin births in cattle. There are genetic and non genetic factors affecting twinning rate. Increased twin births can be done through some technologies such as selection, reproduction and management. The problems in twinnings are the high incidence of abortion, early embryonic loss, distochia, retained placenta, metabolic disorders, and ketosis resulting in longer calving interval. Intensive management to dam bearing twins can reduce the problems. Economically, the profits of twinning are different between beef and dairy cattle. Twin births give benefit to beef cattle farming through the increase in total weaning per cattle. The pros and cons of twin births occur in dairy cows farming, especially on milk production.

scholarly journals The Analysis of Reproduction in Population of the Slovak Spotted Dairy Cows

2019 ◽  
Vol 67 (6) ◽  
pp. 1419-1426
Author(s):  
Jozef Bujko ◽  
Juraj Candrák ◽  
Peter Strapák ◽  
Július Žitný ◽  
Cyril Hrnčár ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Fixed Effects ◽  
Linear Models ◽  
Correlation Coefficients ◽  
Calving Interval ◽  
Factors Affecting ◽  
Actual Computation ◽  
Reproduction Traits ◽  
Days Open ◽  
Basic Statistical Analysis

The aim of study was to analyse the reproduction and factors affecting on reproduction traits of dairy cows in population of Slovak Spotted cattle from 2007 to 2016 the results for 37,274 dairy cows: days to first service (DFS), days open (DO), number of inseminations per conception (NIC), age of first calving (AFC) and calving interval (CI). The basic statistical analysis were analysed using the SAS version 9.3. For the actual computation a linear models with fixed effects was used: For the actual computation a linear models with fixed effects was used: yijklm = μ + HYSi + BTj+ Fk+ Bl +eijklm. The linear model represents coefficients determination R2 = 0.452117% (P < 0.001) for DFS, R2 = 0.377715% (P < 0.001) for DO, R2 = 0.348442% (P < 0.001) for NIC and R2 = 0.317128% (P < 0.001) for CI with all fixed effects. Correlation coefficients among DFS with DO, NIC, AFC and CI were r = 0.37275, r = -0.06881, r = 0.06493 and r = 0.08348. These coefficients were highly statistically significant (P < 0.001).

Non Genetic Factors Affecting Calving Interval in Surti Buffaloes

2019 ◽  
pp. 1
Author(s):  
Vallabh Pawar ◽  
Nikhil Dangar ◽  
Gaurav Pandya ◽  
Balkrishna Brahmkshtri ◽  
Vishnu Kharadi ◽  
...  
Keyword(s):  
Genetic Factors ◽  
Calving Interval ◽  
Factors Affecting

scholarly journals Non-genetic factors affecting calving interval and weaning weight in a buffalo herd located in flooded savannas,Cojedes state, Venezuela

2007 ◽  
Vol 6 (sup2) ◽  
pp. 1351-1353
Author(s):  
O. Colmenares ◽  
P. Monasterio ◽  
P. Herrera ◽  
B. Birbe ◽  
N. Martínez
Keyword(s):  
Genetic Factors ◽  
Calving Interval ◽  
Weaning Weight ◽  
Factors Affecting

scholarly journals Analysis of non-genetic factors affecting calving difficulty in the Czech Holstein population

2008 ◽  
Vol 53 (No. 7) ◽  
pp. 284-291 ◽  
Author(s):  
M. Fiedlerová ◽  
D. Řehák ◽  
M. Vacek ◽  
J. Volek ◽  
J. Fiedler ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Genetic Factors ◽  
Management Tool ◽  
Gestation Length ◽  
Calving Interval ◽  
Data Set ◽  
Age At First Calving ◽  
Factors Affecting ◽  
Calving Difficulty ◽  
Holstein Population

The objective of this study was to analyze the effects of non-genetic factors affecting calving difficulty in the Holstein population of the Czech Republic for subsequent compilation of the model for genetic evaluation as well as for herd management practice. Calving difficulty recorded in 1997–2006 was assessed in three categories: 1 = normal, 2 = hard pull, 3 = complicated. The original observations were transformed to an underlying normal scale. A data set containing 409 255 records was analysed by a linear model with fixed effects of season, parity of dam, sex of calf and Holstein gene proportion. All these effects were significant, and their appropriate categorization was considered. Analyses of additional factors such as gestation length, age at first calving and preceding calving interval were performed. The results revealed that gestation length was in a non-linear relationship with calving difficulty. A higher risk of difficult calving was associated with short or long gestation and with a prolonged preceding calving interval in multiparous cows. Calving difficulty should be adjusted for these factors. A decreased risk of difficult calving could be achieved by an altering of calving interval and age at first calving as a management tool.

scholarly journals Non Genetic Factors Affecting Production and Reproduction Traits of Graded Murrah Buffaloes

2021 ◽  
Author(s):  
M. Srinivasa Reddy ◽  
V. Jagadeeswary ◽  
J. Sai Prasanna
Keyword(s):  
Genetic Factors ◽  
Meteorological Parameters ◽  
Climatic Factors ◽  
Calving Interval ◽  
Factors Affecting ◽  
Murrah Buffaloes ◽  
Lactation Length ◽  
Reproduction Traits ◽  
Dairy Animals ◽  
Maximum Minimum

Background: Environmental factors play a major role and influence the economically important traits in dairy animals. The present investigation was undertaken to study the influence of season on production and reproduction traits of graded Murrah buffaloes reared under farm conditions. Methods: The data pertaining to 164 graded Murrah buffaloes was utilized to study influence of seasons on various climatic factors like maximum, minimum and mean temperature, relative humidity (morning and evening), rainfall, sunshine, wind speed, evaporation and production and reproduction traits like lactation length, lactation yield, days to attain peak yield, persistency, calving interval, birth weight and number of lactations. Result: The present investigation revealed significant effect of season on all the meteorological parameters, production and reproduction parameters studied. The correlations among meteorological parameters and production and reproduction traits were also significant.

Predicting the time of ovulation in dairy cows using milk progesterone kits

1989 ◽  
Vol 1989 ◽  
pp. 146-146
Author(s):  
B.J. McLeod ◽  
R.F. Weller ◽  
R.H. Phipps ◽  
J.A. Foulkes
Keyword(s):  
Dairy Cows ◽  
Reproductive Performance ◽  
Practical Method ◽  
Dairy Herds ◽  
Cycle Period ◽  
Detection Rates ◽  
High Incidence ◽  
Conception Rates ◽  
Embryonic Loss ◽  
On Farm

Poor reproductive performance of dairy herds is seldom attributable to a high incidence of embryonic loss or to long periods of anoestrus, but is generally due to the failure to inseminate cows that are cycling normally.Even in the best managed herds, oestrus detection rates rarely exceed 70-80%, and often 10-20% of non-oestrous animals may be recorded as being on heat. These shortcomings in oestrus detection can be overcome by monitoring oestrous cycles in Individual animals, thus enabling the time of ovulation to be predicted. For example, when cows that failed to show oestrus, were inseminated on the basis of milk progesterone profiles, the conception rates achieved were similar to those in cows inseminated at observed oestrus (Ball and Jackson, 1979). In addition, in groups of animals inseminated at progesterone-timed rather than at observed oestrus, the number of cows served over a one-cycle period increased dramatically (98 v 71%), and days from calving to first service decreased (78 v 92 days), (Foulkes, Cookson and Sauer, 1982). In this study, the feasibility of using on-farm milk progesterone kits as a practical method of predicting ovulation, and its effects on herd reproductive performance were assessed.

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