• Asian-Australasian Journal of Animal Sciences
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• v.13 no.2
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• pp.149-154
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• 2000

The objectives of this study of Hanwoo (Korean Cattle) were 1) to estimate genetic parameters for direct and maternal genetic effects for birth weight, weaning weight, and six months weight which can be used for genetic evaluations and 2) to compare models with and without grandmatemal effects. Data were obtained from the National Livestock Research Institute in Rural Development Administration (RDA) of Korea and were used to estimate genetic parameters for birth weight (BW, n=10,889), weaning weight at 120-d (WW, n=8,637), and six month weight (W6, n=8,478) in Hanwoo. Total number of animals in pedigrees was 14,949. A single-trait animal model was initially used to obtain starting values for multiple-trait animal models. Estimates of genetic parameters were obtained with MTDFREML using animal models and derivative-free REML (Boldman et al., 1995). Estimates of direct heritability for BW, WW, and W6 analyzed as single-traits were 0.09, 0.03, and 0.02 from Model 3 which included direct and maternal genetic, maternal permanental environmental effects, and effects due to sire ${\times}$ region ${\times}$ year-season interaction, respectively. Ignoring sire ${\times}$ region ${\times}$ year-season interaction effect in the model (Model 2) resulted in larger estimates for direct heritability than for Model 3. Estimates of maternal heritability for BW, WW and W6 were 0.04, 0.05, and 0.07 from Model 3, respectively. The estimates of direct-maternal genetic correlation were positive for BW, WW, and W6 with Model 3 but were negative with Model 2 for WW and W6. Estimates of direct genetic correlations between BW and WW, BW and W6, and WW and W6 were large: 0.52, 0.45, and 0.90, respectively. Genetic correlations were also large and positive for maternal effects for BW with maternal effects for WW and W6 (0.69 and 0.74), and even larger for WW with W6 (0.97). The log likelihood values were the same for models including grandmatemal effects as for models including maternal effects for all traits. These results indicate that grandmatemal effects are not important for these traits for Hanwoo or that the data structure was not adequate for estimating parameters for a grandmatemal model.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.11
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• pp.1445-1454
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• 2010

Two separate animal trials were conducted to evaluate the coincidence of dry matter intake (DMI) and average daily gain (ADG) predicted by the Cornell Net Carbohydrate and Protein System (CNCPS) and observed actually in crossbred growing bulls kept in a traditionally confined feeding system in China. In Trial 1, 45 growing Simmental${\times}$Mongolia crossbred F1 bulls were assigned to three treatments (T1-3) with 15 animals in each treatment. Trial 2 was conducted with 60 Limousin${\times}$Fuzhou crossbred F2 bulls allocated to 4 treatments (t1-4). All of the animals were confined in individual stalls. DMI and ADG for each bull were measured as a mean of each treatment. All of the data about animals, environment, management and feeds required by the CNCPS model were collected, and model predictions were generated for animals on each treatment. Subsequently, model-predicted DMI and ADG were compared with the actually recorded results. In the three treatments in Trial 1, 93.3, 80.0 and 73.3% of points fell within the range from -0.4 to 0.4 kg/d for DMI mean bias; similarly, in the four treatments in Trial 2, about 86.7, 73.3, 73.3 and 80.0% of points fell within the same range. These results indicate that the CNCPS model can accurately predict DMI of crossbred bulls in the traditionally confined feeding system in China. There were no significant differences between predicted and observed ADG for T1 (p = 0.06) and T2 (p = 0.09) in Trial 1, and for t1 (p = 0.07), t2 (p = 0.14) and t4 (p = 0.83) in Trial 2. However, significant differences between predicted and observed ADG values were observed for T3 in Trial 1 (p<0.01) and for t3 in Trial 2 (p = 0.04). By regression analysis, a statistically different value of intercept from zero for the regression equation of DMI (p<0.01) or an identical value of ADG (p = 0.06) were obtained, whereas the slopes were significantly different (p<0.01) from unity for both DMI and ADG. Additionally, small root mean square error (RMSE) values were obtained for the unbiased estimator of the two variances (DMI and ADG). Thus, the present results indicated that the CNCPS model can give acceptable estimates of DMI and ADG of crossbred growing bulls kept in a traditionally confined feeding system in China.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.1
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• pp.12-18
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• 2007

The objective of the study was to compare ranking of Sahiwal bulls selected on the basis of highest lactation milk yield of their dams with their estimated breeding values (EBVs) using an animal model. Data on 23,761 lactation milk yield records of 5,936 cows from five main Livestock Experiment Stations in Punjab province of Pakistan (1964-2004) were used for the study. At present the young A.I bulls are required to be from A-category bull-dams. Dams were categorized as A, B, C and D if they had highest lactation milk yield of ${\geq}$2,700, 2,250-2,699, 1,800-2,249 and <1,800 litres, respectively. The EBVs for lactation milk yield were estimated for all the animals using an individual animal model having fixed effect of herd-year and season of calving and random effect of animal. Fixed effect of parity and random effect of permanent environment were incorporated when multiple lactation were used. There were 396 young bulls used for semen collection and A.I during 1973-2004. However, progeny with lactation yields recorded, were available only for 91 bulls and dams could be traced for only 63 bulls. Overall lactation milk yield averaged 1,440.8 kg. Milk yield was 10% heritable with repeatability of 39%. Ranking bulls on highest lactation milk yield of their dams, the in-vogue criteria of selecting bulls, had a rank correlation of 0.167 (p<0.190) with ranking based on EBVs from animal model analysis. Bulls' EBVs for all lactations had rank correlation of 0.716 (p<0.001) with EBVs based on first lactation milk yield and 0.766 (p<0.001) with average EBVs of dam and sire (pedigree index). Ranking of bulls on highest lactation yield of their dams has no association with their ranking based on animal model evaluation. Young Sahiwal bulls should be selected on the basis of pedigree index instead of highest lactation yield of dams. This can help improve the genetic potential of the breed accruing to conservation and development efforts.

• Korean Journal of Poultry Science
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• v.44 no.2
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• pp.103-111
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• 2017

The quail (Coturnix japonica) has been used as a model animal in many research fields and its application is still expanding in other fields. Compared to the chicken, the quail is quicker to reach sexually maturity, has short generation intervals, is easy to handle, requires less space and feed, and is sturdy. In addition, it produces many eggs and the research tools developed for chicken can be applied directly to quail or with some modifications. Due to recent advances in next-generation sequencing, abundant sequence data for the quail genome and transcripts have been generated. These sequence data are valuable sources for studying functional genomics using quail, which is one of the model animal used to investigate gene function and networks. Although there are some obstacles to be removed, the quail is the best optimized model to study the functional genomics of poultry. In many research fields, functional genomics study using the quail model will provide the best opportunity to understand the phenomena and principles of life. We review why, among many other birds, the quail is the best model for studying poultry functional genomics.

• Journal of Embryo Transfer
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• v.31 no.1
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• pp.97-107
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• 2016

Although many diseases could be treated by the development of modern medicine, there are some incurable diseases including brain cancer, Alzheimer disease, etc. To study human brain cancer, various animal models were reported. Among these animal models, mouse models are valuable tools for understanding brain cancer characteristics. In spite of many mouse brain cancer models, it has been difficult to find a new target molecule for the treatment of brain cancer. One of the reasons is absence of large animal model which makes conducting preclinical trials. In this article, we review a recent study of molecular characteristics of human brain cancer, their genetic mutation and comparative analysis of the mouse brain cancer model. Finally, we suggest the need for development of large animal models using somatic cell nuclear transfer in translational research.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.1
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• pp.1-6
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• 2001

Additive and dominance genetic variances were estimated for purebred Landrace selected with line breeding from 1989 to 1995 at Miyazaki Livestock Experiment Station, Kawaminami Branch. Ten body measurements, two reproductive traits and fifteen carcass traits were analyzed with single-trait mixed model analysis. The estimates of narrow-sense heritabilities by additive model were in the range of 0.07 to 0.46 for body measurements, 0.05 to 0.14 for reproductive traits, and 0.05 to 0.68 for carcass traits. The additive model tended to slightly overestimate the narrow-sense heritabilities as compared to the additive and dominance model. The proportion of the dominance variance to total genetic variance ranged from 0.11 to 0.91 for body measurements, 0.00 to 0.65 for reproductive traits, and 0.00 to 0.86 for carcass traits. Large differences among traits were found in the ratio of dominance to total genetic variance. These results suggested that dominance effect would affect the expression of all ten body measurements, one reproductive trait, and nine carcass traits. It is justified to consider the dominance effects in genetic evaluation of the selected lines for those traits.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.22 no.2
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• pp.74-81
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• 2009

Background and Objective : There are a lot of theories that explained the aging process, and the oxidative stress is one of the important theory that explained the aging process. The aim of this study was to investigate active oxygen and antioxidant capacity of Qi deficiency and Blood deficiency animal models. Material and Methods : Sprague-Dawley rats were divided into three groups: normal group, Qi deficiency group and Blood deficiency group. The Qi deficiency animal model was induced through restriction of food (12g/kg/day) for 20 days. Blood deficiency animal model was induced by bleeding from tail vein(0.4ml/time) 8 times. The normal animal model was kept without any intervention. The oxidative stress was observed by measuring the active oxygen and antioxidant capacity. Results and Conclusion : 1. Active oxygen was significantly increased in the Qi deficiency group and Blood deficiency group. (P=0.061) 2. Antioxidant capacity was increased in the Qi deficiency group and Blood deficiency group. But there is no significant difference. (P=0.113)

• Animal Bioscience
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• v.36 no.8
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• pp.1151-1155
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• 2023

Objective: This study analyzes interactions of body condition score (BCS) with other factors and the effect of BCS on estimates of genetic paremeters of conception rate (CR) in Japanese Black cows. Methods: Factors affecting CR were analyzed through the linear mixed model, and genetic parameters of CR were estimated through the threshold animal model. Results: The interactions between BCS and each season and the number of artificial inseminations (AI) was significant (p<0.05), but that between BCS and parity showed no significance for CR. High CR was observed with BCS 3 in autumn (0.56±0.01) and BCS 4 in summer (0.56±0.02). The highest CR with BCS 3 (0.56±0.02) and BCS 4 (0.55±0.01) was observed at first AI. With BCS 5, however, the highest CR (0.55±0.08) was observed at second AI. Conclusion: The model with BCS was notably conducive to the estimation of genetic parameters because of a low deviance information criterion of heritability that, nevertheless, was slightly lower than the model without BCS.

• Food Science of Animal Resources
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• v.31 no.6
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• pp.899-906
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• 2011

The objectives of this study were to apply the Baranyi model to predict the growth of natural microflora in liver sausage with added kimchi powder. Kimchi powder was added to the meat products at 0, 1, 2, and 3% levels. To determine and quantify the natural microflora in the meat products, total plate counts and counts of anaerobic bacteria and lactic acid bacteria were examined throughout the 28 d of storage. The obtained data were applied to the Baranyi growth model. The indices used for comparing predicted and observed data were $B_f$, $A_f$, root mean square error (RMSE), and $R^2$. Twelve predictive models were characterized by a high $R^2$ and small RMSE. The Baranyi model was useful in predicting natural microflora levels in these meat products with added kimchi powder during storage.

• Animal Bioscience
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• v.34 no.7
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• pp.1202-1209
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• 2021

Objective: The intestinal microbiota plays an important role in host physiology, metabolism, immunity, and behavior. And host genetics could influence the gut microbiota of hybrid animals. The three-way cross model is commonly utilized in commercial pig production; however, the use of this model to analyse the gut microbial composition is rarely reported. Methods: Two three-way hybrid pigs were selected, with Saba pigs as the starting maternal pig: Duroc× (Berkshire×Saba) (DBS) pig, Berkshire×(Duroc×Saba) (BDS) pig. One hundred pigs of each model were reared from 35 days (d) to 210 d. The body weight or feed consumption of all pigs were recorded and their feed/gain (F/G) ratio was calculated. On day 210, 10 pigs from each three-way cross were selected for slaughter, and cecal chyme samples were collected for 16S rRNA gene sequencing. Results: The final body weight (FBW) and average daily gain (ADG) of DBS pigs were significantly higher than those of BDS pigs (p<0.05), while the F/G ratios of DBS pigs were significantly lower than those of BDS pigs (p<0.05). The dominant phyla in DBS and BDS pigs were Bacteroidetes (55.23% vs 59%, respectively) and Firmicutes (36.65% vs 34.86%, respectively) (p>0.05). At the genus level, the abundance of Prevotella, Roseburia, and Anaerovibrio in DBS pigs was significantly lower than in BDS pigs (p<0.01). The abundance of Eubacterium, Clostridium XI, Bacteroides, Methanomassiliicoccus, and Parabacteroides in DBS pigs was significantly higher than in BDS pigs (p<0.05). The FBWs and ADGs were positively correlated with Bacteroides, ClostridiumXI, and Parabacteroides but negatively correlated with the Prevotella, Prevotella/Bacteroides (P/B) ratio, Roseburia, and Anaerovibrio. Conclusion: These results indicated that host genetics affect the cecal microbiota composition and the porcine gut microbiota is associated with growth performance, thereby suggesting that gut microbiota composition may be a useful biomarker in porcine genetics and breeding.