Non Genetic Factors Affecting Age at First Calving in Surti Buffaloes

2018 ◽  
pp. 1
Author(s):  
Vallabh Pawar ◽  
Nikhil Dangar ◽  
Umed Ramani ◽  
Gaurav Pandya ◽  
Vishnu Kharadi ◽  
...  
Keyword(s):  
Genetic Factors ◽  
Age At First Calving ◽  
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 Genetic predictors of participation in optional components of UK Biobank

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jessica Tyrrell ◽  
Jie Zheng ◽  
Robin Beaumont ◽  
Kathryn Hinton ◽  
Tom G. Richardson ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Genetic Variants ◽  
Genetic Factors ◽  
Mendelian Randomization ◽  
Genetic Correlations ◽  
Mr Studies ◽  
Uk Biobank ◽  
Factors Affecting ◽  
Participation Bias ◽  
Genetic Predictors

AbstractLarge studies such as UK Biobank are increasingly used for GWAS and Mendelian randomization (MR) studies. However, selection into and dropout from studies may bias genetic and phenotypic associations. We examine genetic factors affecting participation in four optional components in up to 451,306 UK Biobank participants. We used GWAS to identify genetic variants associated with participation, MR to estimate effects of phenotypes on participation, and genetic correlations to compare participation bias across different studies. 32 variants were associated with participation in one of the optional components (P < 6 × 10−9), including loci with links to intelligence and Alzheimer’s disease. Genetic correlations demonstrated that participation bias was common across studies. MR showed that longer educational duration, older menarche and taller stature increased participation, whilst higher levels of adiposity, dyslipidaemia, neuroticism, Alzheimer’s and schizophrenia reduced participation. Our effect estimates can be used for sensitivity analysis to account for selective participation biases in genetic or non-genetic analyses.

Genetic factors affecting intelligence: Symposium

1954 ◽  
Vol 1 (1) ◽  
pp. 44-52 ◽  
Author(s):  
S. C. Reed ◽  
W. Reed ◽  
J. D. Palm
Keyword(s):  
Genetic Factors ◽  
Factors Affecting

The Nature and Origin of Common Phobic Fears

1979 ◽  
Vol 134 (4) ◽  
pp. 343-351 ◽  
Author(s):  
Svenn Torgersen
Keyword(s):  
Environmental Factors ◽  
Social Adjustment ◽  
Twin Study ◽  
Genetic Factors ◽  
Factor Analyses ◽  
Factors Affecting ◽  
Five Factors

SummaryBy means of a twin study an attempt was made to throw light upon the aetiology and nosology of phobic fears. Factor analyses revealed five factors, namely separation fears, animal fears, mutilation fears, social fears and nature fears. The study demonstrated that, apart from separation fears, genetic factors play a part in the strength as well as content of phobic fears. Environmental factors, affecting the development of dependence, reserve and neurotic traits generally, seemed also to be of some importance. It was further demonstrated that phobic fears were related to emotional and social adjustment and this was true to an even greater extent for separation fears.

scholarly journals Environmental and genetic factors affecting the weaning-estrus interval in sows

2011 ◽  
Vol 10 (4) ◽  
pp. 2692-2701 ◽  
Author(s):  
C.D.S. Leite ◽  
J.F. Lui ◽  
L.G. Albuquerque ◽  
D.N.M. Alves
Keyword(s):  
Genetic Factors ◽  
Factors Affecting

scholarly journals Factors affecting the milk production of dairy cattle in northern rural areas of Bangladesh

2015 ◽  
Vol 4 (2) ◽  
pp. 41-45 ◽  
Author(s):  
MR Begum ◽  
M Anaruzzaman ◽  
MSI Khan ◽  
M Yousuf
Keyword(s):  
Body Weight ◽  
Dairy Cattle ◽  
Milk Production ◽  
Rural Areas ◽  
Binary Logistic Regression ◽  
Cross Sectional Study ◽  
Lactation Period ◽  
Cross Sectional ◽  
Age At First Calving ◽  
Factors Affecting

A cross sectional study was conducted to observe the factors affecting the productive performance of dairy cattle from northern rural areas of Bangladesh during July and September 2013. Data of 105 cows, 85 (80.95%) from local and 20 (19.05%) cows from cross breed, were randomly selected for the study. A binary logistic regression, expressed by odds ratio with 95% confidence interval, was done to determine the association of daily milk production categorized into ? 2 and > 2 liters (L), based on median, with the significant explanatory variables of body weight, age at first calving, lactation period, vitamin use, type of floor and milking person. The result demonstrated that the probability of milk production of >2 L was 6.16, 4.5, 20.65 and 5.7 times higher from the with animal body weight of >140 kg, age at first calving of >36 m, lactation period of >8 m and vitamin use than that of body weight of 140 kg, age at first calving of ?36 m, lactation period of ? 8 m, and not vitamin used respectively. The chance of milk production of > 2 L was 0.25 and 0.22 times lower for mud floor, and owner milking than that of brick floor and gowala (professional milking person) respectively. DOI: http://dx.doi.org/10.3329/ijarit.v4i2.22646 Int. J. Agril. Res. Innov. & Tech. 4 (2): 41-45, December, 2014

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