scholarly journals 299 Genetic analysis of temperament and its correlation with production, reproduction, type, health and longevity in Chinese Holstein

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 29-30
Author(s):  
Yao Chang ◽  
Yachun Wang
Keyword(s):  
Genetic Correlation ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Threshold Model ◽  
Residual Effect ◽  
Additive Genetic Effect ◽  
Age At First Calving ◽  
Chinese Holstein

Abstract The objectives of this study were to estimate genetic parameters for temperament via three approaches and to examine associations of temperament with other economically important traits in Chinese Holstein. Records for temperament score (TS) on 6,586 lactating cows from 2015 to 2017 were obtained. Temperament assessed during rectal temperature measurements was recorded on a 3-point scale (1 = quiet; 2 = average; 3 = nervous). TS was treated as a ternary trait or a binary trait in different scenarios. The genetic parameters were estimated by: 1) a linear model using AI-REML; 2) a Generalized Linear Mixed Model (GLMM); or 3) a Bayesian threshold model via Gibbs sampling. Each record was partitioned into the fixed effects of herd-scorer and parity, an additive genetic effect and a residual effect. Then approximate genetic correlation between TS with production traits [milk yield (MY), fat and protein percentage (FP and PP)], fertility traits [age at first service (AFS), age at first calving (AFC), stillbirth (SB)], overall type, health traits [somatic cell score (SCS), udder diseases (UD) claw and leg diseases (CLD) metabolic disorders (MD)] and productive life (PL) were estimated. Estimates of heritability and accuracy of EBV for TS were listed in Table 1. Low to moderate genetic correlation between TS and above-mentioned traits were found. There was a favorable genetic correlation between TS and FP (-0.35), PP (-0.42), AFC (0.31), UD (0.58) and PL (-0.24); however, undesirable genetic correlation existed between TS and the other traits (-0.43~0.27). Current results suggested that a Bayesian threshold model can be the most recommended algorithm for analyzing temperament since it brought a relatively higher heritability and consequently EBV with higher accuracy, and selection for calmer individuals will translate into increased fat and protein yields, a lower age at first calving, better resistance to udder diseases and a longer functional longevity.

scholarly journals Estimation of genetic parameters for female fertility traits in the Czech Holstein population

2019 ◽  
Vol 64 (No. 5) ◽  
pp. 199-206 ◽  
Author(s):  
Michaela Brzáková ◽  
Ludmila Zavadilová ◽  
Josef Přibyl ◽  
Petr Pešek ◽  
Eva Kašná ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Reproductive Traits ◽  
Additive Genetic Effect ◽  
Data Set ◽  
Age At First Calving ◽  
Fertility Traits ◽  
Holstein Population

Genetic parameters for fertility traits in Czech Holstein population were estimated. The database obtained from the Czech-Moravian Breeders Corporation with 6 414 486 insemination records between years 2005–2015 was used. Date of calving of the selected animals was taken from the database of milk records from 2005–2015. Fertility traits were age at first service (AFS), age at first calving (AFC), days open (DO), calving interval (CI) and first service to conception interval in cows (FSC-C) and heifers (FSC-H). The heritability of each trait was estimated using single-trait animal models. The model included fixed effects of herd-year-season of birth, herd-year-month of calving, lactation order, parity, last calving ease, linear and quadratic regressions on age at first insemination in heifers or on age at first calving in cows. Random effects were animal, permanent environmental effect and random residual error. After edits, the final data set included up to 599 901 observations from up to 448 037 animals dependent on traits. The range of heritability estimates was from 0.010 to 0.058. The lowest heritability was for first service to conception interval in heifers, and the highest heritability was for age at first service. Variances of random permanent effects were higher than variance of additive genetic effect in all traits manifested in mature cows. Repeatability ranged from 0.060 to 0.090. Genetic correlations between traits were estimated using a bivariate animal model. High positive genetic correlations were found between AFS–AFC, DO–CI, FSC-C–DO and FSC-C–CI. A moderate genetic correlation was found between AFS–FSC-H and between AFC. A negative correlation was found between AFS–FSC-C. Correlations between other traits were close to zero. The results suggest that the level of these reproductive traits can be improved by selection of animals with high genetic merit.

scholarly journals PSVIII-38 Late-Breaking Abstract: Estimating genetic parameters of feed efficiency traits in American mink

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 347-347
Author(s):  
Pourya Davoudi ◽  
Duy Ngoc Do ◽  
Guoyu Hu ◽  
Siavash Salek Ardestani ◽  
Younes Miar
Keyword(s):  
Body Weight ◽  
Genetic Correlation ◽  
Feed Intake ◽  
Feed Efficiency ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
American Mink ◽  
Genetic Correlations ◽  
Final Body Weight ◽  
Selection For

Abstract Feed cost is the major input cost in the mink industry and thus improvement of feed efficiency through selection for high feed efficient mink is necessary for the mink farmers. The objective of this study was to estimate the heritability, phenotypic and genetic correlations for different feed efficiency measures, including final body weight (FBW), daily feed intake (DFI), average daily gain (ADG), feed conversion ratio (FCR) and residual feed intake (RFI). For this purpose, 1,088 American mink from the Canadian Center for Fur Animal Research at Dalhousie Faculty of Agriculture were recorded for daily feed intake and body weight from August 1 to November 14 in 2018 and 2019. The univariate models were used to test the significance of sex, birth year and color as fixed effects, and dam as a random effect. Genetic parameters were estimated via bivariate models using ASReml-R version 4. Estimates of heritabilities (±SE) were 0.41±0.10, 0.37±0.11, 0.33±0.14, 0.24±0.09 and 0.22±0.09 for FBW, DFI, ADG, FCR and RFI, respectively. The genetic correlation (±SE) was moderate to high between FCR and RFI (0.68±0.15) and between FCR and ADG (-0.86±0.06). In addition, RFI had low non-significant (P > 0.05) genetic correlations with ADG (0.04 ± 0.26) and BW (0.16 ± 0.24) but significant (P < 0.05) high genetic correlation with DFI (0.74 ± 0.11) indicating that selection for lower RFI will reduce feed intake without adverse effects on the animal size and growth rate. The results suggested that RFI can be implemented in genetic/genomic selection programs to reduce feed intake in the mink production system.

scholarly journals Goats Given Transdermal Flunixin Meglumine Displayed Less Pain Behavior After Castration

2020 ◽  
Author(s):  
Amanda Lee ◽  
Meggan Graves ◽  
Andrea Lear ◽  
Sherry Cox ◽  
Marc Caldwell ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Body Position ◽  
Random Effect ◽  
Pain Behavior ◽  
Bout Duration ◽  
Flunixin Meglumine ◽  
Meat Goats ◽  
Transdermal Application

AbstractPain management should be utilized with castration to reduce physiological and behavioral changes. Transdermal application of drugs require less animal management and fewer labor risks, which can occur with oral administration or injections. The objective was to determine the effects of transdermal flunixin meglumine on meat goats’ behavior post-castration. Male goats (N = 18; mean body weight ± standard deviation: 26.4 ± 1.6 kg) were housed individually in pens and randomly assigned to 1 of 3 treatments: (1) castrated, dosed with transdermal flunixin meglumine; (2) castrated, dosed with transdermal placebo; and (3) sham castrated, dosed with transdermal flunixin meglumine. Body position, rumination, and head- pressing were observed for 1 h ± 10 minutes twice daily on days −1, 0, 1, 2, and 5 around castration. Each goat was observed once every 5-minutes (scan samples) and reported as percentage of observations. Accelerometers were used to measure standing, lying, and laterality (total time, bouts, and bout duration). A linear mixed model was conducted using GLIMMIX. Fixed effects of treatment, day relative to castration, and treatment*day relative to castration and random effect of date and goat nested within treatment were included. Treatment 1 goats (32.7 ± 2.8%) and treatment 2 goats (32.5 ± 2.8%) ruminated less than treatment 3 goats (47.4 ± 2.8%, P = 0.0012). Head pressing was greater on day of castration in treatment 2 goats (P < 0.001). Standing bout duration was greatest in treatment 2 goats on day 1 post-castration (P < 0.001). Lying bout duration was greatest in treatment 2 goats on day 1 post-castration compared to treatment 1 and treatment 3 goats(P < 0.001). Transdermal flunixin meglumine improved goats’ fluidity of movement post-castration and decreased head pressing, indicating a mitigation of pain behavior.

Generalized linear mixed models for multi-reader multi-case studies of diagnostic tests

2015 ◽  
Vol 26 (3) ◽  
pp. 1373-1388 ◽  
Author(s):  
Wei Liu ◽  
Norberto Pantoja-Galicia ◽  
Bo Zhang ◽  
Richard M Kotz ◽  
Gene Pennello ◽  
...  
Keyword(s):  
Mixed Models ◽  
Diagnostic Tests ◽  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Generalized Linear Mixed Models ◽  
Characteristic Curve ◽  
Linear Mixed Models ◽  
Parametric Bootstrap ◽  
Pseudo Likelihood

Diagnostic tests are often compared in multi-reader multi-case (MRMC) studies in which a number of cases (subjects with or without the disease in question) are examined by several readers using all tests to be compared. One of the commonly used methods for analyzing MRMC data is the Obuchowski–Rockette (OR) method, which assumes that the true area under the receiver operating characteristic curve (AUC) for each combination of reader and test follows a linear mixed model with fixed effects for test and random effects for reader and the reader–test interaction. This article proposes generalized linear mixed models which generalize the OR model by incorporating a range-appropriate link function that constrains the true AUCs to the unit interval. The proposed models can be estimated by maximizing a pseudo-likelihood based on the approximate normality of AUC estimates. A Monte Carlo expectation-maximization algorithm can be used to maximize the pseudo-likelihood, and a non-parametric bootstrap procedure can be used for inference. The proposed method is evaluated in a simulation study and applied to an MRMC study of breast cancer detection.

scholarly journals Genetic effects on reproductive traits in Warmblood horses

2009 ◽  
Vol 89 (2) ◽  
pp. 215-218 ◽  
Author(s):  
A. Wolc ◽  
G. Torzynski ◽  
T. Szwaczkowski
Keyword(s):  
Key Words ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
Genetic Effect ◽  
Reproductive Traits ◽  
Additive Genetic Effect ◽  
Reproductive Efficiency ◽  
Horse Breeding ◽  
Estimate Heritability ◽  
Genetic Trends

Reproductive efficiency is an important issue in horse breeding. However, almost no estimates of genetic parameters of reproductive traits in horses can be found in the literature. The objective of the study was to estimate heritability and genetic trends of foaling rate and number of reproductive seasons in Warmblood horses. The records of 3965 mares from six studs were analyzed. Mares were on average kept for 7.3 reproductive seasons with a foaling rate of 66%. Models included fixed effects of stud, period of birth, breed and random additive genetic effect. Heritability estimates were 0.12 for foaling rate and 0.17 for number of reproductive seasons. Key words: Heritability, reproduction, horse

scholarly journals Quantifying the Effects of Fusarium Head Blight on Grain Yield and Test Weight in Soft Red Winter Wheat

2015 ◽  
Vol 105 (3) ◽  
pp. 295-306 ◽  
Author(s):  
Jorge David Salgado ◽  
Laurence V. Madden ◽  
Pierce A. Paul
Keyword(s):  
Winter Wheat ◽  
Grain Yield ◽  
Fusarium Head Blight ◽  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Test Weight ◽  
Head Blight ◽  
Soft Red Winter Wheat ◽  
Red Winter Wheat

Fusarium head blight (FHB), caused by the fungus Fusarium graminearum, is known to negatively affect wheat grain yield (YLD) and test weight (TW). However, very little emphasis has been placed on formally quantifying FHB–YLD and FHB–TW relationships. Field plots of three soft red winter wheat cultivars—‘Cooper’ (susceptible to FHB), ‘Hopewell’ (susceptible), and ‘Truman’ (moderately resistant)—were grown during the 2009, 2010, 2011, and 2012 seasons, and spray inoculated with spore suspensions of F. graminearum and Parastagonospora nodorum to generate a range of FHB and Stagonospora leaf blotch (SLB) levels. FHB index (IND) and SLB were quantified as percent diseased spike and flag leaf area, respectively, and YLD (kg ha−1) and TW (kg m−3) data were collected. Using IND as a continuous covariate and cultivar (CV) and SLB as categorical fixed effects, linear mixed-model regression analyses (LMMR) were used to model the IND–YLD and IND–TW relationship and to determine whether these relationships were influenced by CV and SLB. The final models fitted to the data were of the generic form y = a + b (IND), where a (intercept) or b (slope) could also depend on other factors. LMMR analyses were also used to estimate a and b by combining the studies from these 4 years with an additional 16 experiments conducted from 2003 to 2013, and bivariate random-effects meta-analysis was used to estimate population mean b ([Formula: see text]) and a (ā) for the IND–YLD relationship. YLD and TW decreased as IND increased, with b ranging from −3.2 to −2.3 kg m−3 %−1 for TW. For the IND–YLD relationship, [Formula: see text] was −51.7 kg ha−1 %IND−1 and ā was 4,426.7 kg ha−1. Neither cultivar nor SLB affected the IND–YLD relationship but SLB affected a of the IND–TW regression lines, whereas cultivar affected b. Plots with the highest levels of SLB (based on ordinal categories for SLB) had the lowest a and Hopewell had the highest b. The level of IND at which a 50-kg m−3 reduction in TW was predicted to occur was 19, 16, and 22% for Cooper, Hopewell, and Truman, respectively. A yield loss of 1 MT ha−1 was predicted to occur at 19% IND. The rate of reduction in relative TW or YLD per unit increase in IND was between −0.39 and −0.32%−1 for TW and −1.17%−1 for YLD. Results from this study could be integrated into more general models to evaluate the economics of FHB management strategies.

Misspecification of the random effect structure: Implications for the linear mixed model

2020 ◽  
Author(s):  
Brandon LeBeau
Keyword(s):  
Fixed Effects ◽  
Serial Correlation ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Type I Error ◽  
Random Effect ◽  
Correlated Data ◽  
Unbiased Estimation ◽  
Type I ◽  
Nested Data

<p>The linear mixed model is a commonly used model for longitudinal or nested data due to its ability to account for the dependency of nested data. Researchers typically rely on the random effects to adequately account for the dependency due to correlated data, however serial correlation can also be used. If the random effect structure is misspecified (perhaps due to convergence problems), can the addition of serial correlation overcome this misspecification and allow for unbiased estimation and accurate inferences? This study explored this question with a simulation. Simulation results show that the fixed effects are unbiased, however inflation of the empirical type I error rate occurs when a random effect is missing from the model. Implications for applied researchers are discussed.</p>

scholarly journals Exercise-induced hypoalgesia in women with varying levels of menstrual pain

2018 ◽  
Vol 18 (2) ◽  
pp. 303-310 ◽  
Author(s):  
Mervyn Travers ◽  
Penny Moss ◽  
William Gibson ◽  
Dana Hince ◽  
Sheree Yorke ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Random Effect ◽  
Activity Levels ◽  
Menstrual Pain ◽  
Isometric Handgrip ◽  
Pressure Pain Thresholds ◽  
Significant Difference ◽  
Exercise Induced

Abstract Background and aims: Exercise-induced hypoalgesia (EIH) is a well-established phenomenon in pain-free individuals that describes a decrease in pain sensitivity after an acute bout of exercise. The EIH response has been demonstrated to be sub-optimal in the presence of persisting pain. Menstrual pain is a common recurrent painful problem with many women experiencing high levels of pain each cycle. However, the EIH response has not been examined in a cohort of women with high levels of menstrual pain. This research aimed to examine whether EIH manifests differently in women with varying levels of menstrual pain. The primary hypothesis was that women with high levels of menstrual pain would demonstrate compromised EIH. Secondary aims were to explore relationships between EIH and emotional state, sleep quality, body mass index (BMI) or physical activity levels. Methods: Pressure pain thresholds (PPT) were measured in 64 participants using a digital handheld algometer before and after a submaximal isometric-handgrip exercise. EIH index was compared between low (VAS 0–3), moderate (VAS 4–7) and high (VAS 8–10) pain groups, using a linear mixed model analysis with participant as a random effect, and site, menstrual pain category and the interaction between the two, as fixed effects. Results: EIH was consistently induced in all groups. However, there was no statistically significant difference between the pain groups for EIH index (p=0.835) or for any co-variates (p>0.05). Conclusions: EIH was not found to differ between women who report regular low, moderate or high levels of menstrual pain, when measured at a point in their menstrual cycle when they are pain free. Implications: This study provides insight that EIH does not vary in women with differing levels of menstrual pain when they are not currently experiencing pain. The current findings indicate that, although menstrual pain can involve regular episodes of high pain levels, it may not be associated with the same central nervous system dysfunctions as seen in sustained chronic pain conditions.

Linear and threshold model genetic parameters for disease, fertility and milk production in dairy cattle

2000 ◽  
Vol 71 (3) ◽  
pp. 411-419 ◽  
Author(s):  
H. N. Kadarmideen ◽  
R. Thompson ◽  
G. Simm
Keyword(s):  
Dairy Cattle ◽  
Milk Production ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
Threshold Model ◽  
Production Traits ◽  
Milk Production Traits ◽  
Model Framework ◽  
Data Set ◽  
Fertility Traits

AbstractThis study provides estimates of genetic parameters for various diseases, fertility and 305-day milk production traits in dairy cattle using data from a UK national milk recording scheme. The data set consisted of 63891 multiple lactation records on diseases (mastitis, lameness, milk fever, ketosis and tetany), fertility traits (calving interval, conception to first service, number of services for a conception, and number of days to first service), dystocia and 305-day milk, fat and protein yield. All traits were analysed by multi-trait repeatability linear animal models (LM). Binary diseases and fertility traits were further analysed by threshold sire models (TM). Both LM and TM analyses were based on the generalized linear mixed model framework. The LM included herd-year-season of calving (HYS), age at calving and parity as fixed effects and genetic, permanent environmental and residual effects as random. The TM analyses included the same effects as for LM, but HYS effects were treated as random to avoid convergence problems when HYS sub-classes had 0 or 100% incidence. Because HYS effects were treated as random, herd effects were fitted as fixed effects to account for effect of herds in the data. The LM estimates of heritability ranged from 0•389 to 0•399 for 305-day milk production traits, 0•010 to 0•029 for fertility traits and 0•004 to 0•038 for diseases. The LM estimates of repeatability ranged from 0•556 to 0•586 for 305-day milk production traits, 0•029 to 0•086 for fertility traits and 0•004 to 0•100 for diseases. The TM estimates of heritabilities and repeatabilities were greater than LM estimates for binary traits and were in the range 0•012 to 0•126 and 0•013 to 0•168, respectively. Genetic correlations between milk production traits and fertility and diseases were all unfavorable: they ranged from 0•07 to 0•37 for milk production and diseases, 0•31 to 0•54 for milk production and poor fertility and 0•06 to 0•41 for diseases and poor fertility. These results show that future selection programmes should include disease and fertility for genetic improvement of health and reproduction and for sustained economic growth in the dairy cattle industry.

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