• KOREAN JOURNAL OF CROP SCIENCE
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• v.30 no.3
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• pp.326-333
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• 1985

The genetic information was required to improve several plant characteristics of the two modified opaque-2 synthetics, which were synthesized in 1980 at the Chungnam National University. Genetic analysis to obtain the information was carried out by the method of Hallauer and Wright. The information obtained from the analysis indicates that plant characteristics such as plant height, ear height, kernel weight and yield of the two synthetics can be improved by proper breeding procedures, since these characteristics were showing high estimates of genetic and additive variance. The study also shows that some characteristics such as ear length or kernel row number may be not improved effectively and with ease.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.8
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• pp.1031-1040
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• 2011

The objective of this study was to characterize factors influencing genetic improvement of dairy cattle for milk production at farm level. Data were accumulated from 305-day milk yields and pedigree information from 1,921 first-lactation dairy cows that calved from 1990 to 2007 on 161 farms in Central Thailand. Variance components were estimated using average information restricted maximum likelihood procedures. Animal breeding values were predicted by an animal model that contained herd-year-season, calving age, and regression additive genetic group as fixed effects, and cow and residual as random effects. Estimated breeding values from cows that calved in a particular month were used to estimate genetic trends for each individual farm. Within-farm genetic trends (b, regression coefficient of farm milk production per month) were used to classify farms into 3 groups: i) farms with negative genetic trend (b<-0.5 kg/mo), ii) farms with no genetic trend (-0.5 kg/$mo{\leq}b{\leq}0.5$ kg/mo), and iii) farms with positive genetic trend (b>0.5 kg/mo). Questionnaires were used to gather information from individual farmers on educational background, herd characteristics, farm management, decision making practices, and opinion on dairy farming. Farmer's responses to the questionnaire were used to test the association between these factors and farm groups using Fisher's exact test. Estimated genetic trend for the complete population was $0.29{\pm}1.02$ kg/year for cows. At farm level, most farms (40%) had positive genetic trend ($0.63{\pm}4.67$ to $230.79{\pm}166.63$ kg/mo) followed by farms with negative genetic trend (35%; $-173.68{\pm}39.63$ to $-0.62{\pm}2.57$ kg/mo) and those with no genetic trend (25%; $-0.52{\pm}3.52$ to $0.55{\pm}2.68$ kg/mo). Except for educational background (p<0.05), all other factors were not significantly associated with farm group.

• Animal Bioscience
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• v.35 no.7
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• pp.955-963
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• 2022

Objective: The aim of this study was to estimate genetic parameters for 305-day cumulative milk yield and components, growth, and reproductive traits in Guzerá cattle. Methods: The evaluated traits were 305-day first-lactation cumulative yields (kg) of milk (MY305), fat (FY305), protein (PY305), lactose (LY305), and total solids (SY305); age at first calving (AFC) in days; adjusted scrotal perimeter (cm) at the ages of 365 (SP365) and 450 (SP450) days; and adjusted body weight (kg) at the ages of 210 (W210), 365 (W365), and 450 (W450) days. The (co)variance components were estimated using the restricted maximum likelihood method for single-trait, bi-trait and tri-trait analyses. Contemporary groups and additive genetic effects were included in the general mixed model. Maternal genetic and permanent environmental effects were also included for W210. Results: The direct heritability estimates ranged from 0.16 (W210) to 0.32 (MY305). The maternal heritability estimate for W210 was 0.03. Genetic correlation estimates among milk production traits and growth traits ranged from 0.92 to 0.99 and from 0.92 to 0.99, respectively. For milk production and growth traits, the genetic correlations ranged from 0.33 to 0.56. The genetic correlations among AFC and all other traits were negative (-0.43 to -0.27). Scrotal perimeter traits and body weights showed genetic correlations ranging from 0.41 to 0.46, and scrotal perimeter and milk production traits showed genetic correlations ranging from 0.11 to 0.30. The phenotypic correlations were similar in direction (same sign) and lower than the corresponding genetic correlations. Conclusion: These results suggest the viability and potential of joint selection for dairy and beef traits in Guzerá cattle, taking into account reproductive traits.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.9
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• pp.1237-1246
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• 2013

The objective of this study was to estimate variance components and genetic parameters for lactation milk yield (LY), lactation length (LL), average milk yield per day (YD), initial milk yield (IY), peak milk yield (PY), days to peak (DP) and parameters (ln(a) and c) of the modified incomplete gamma function (MIG) in an Ethiopian multibreed dairy cattle population. The dataset was composed of 5,507 lactation records collected from 1,639 cows in three locations (Bako, Debre Zeit and Holetta) in Ethiopia from 1977 to 2010. Parameters for MIG were obtained from regression analysis of monthly test-day milk data on days in milk. The cows were purebred (Bos indicus) Boran (B) and Horro (H) and their crosses with different fractions of Friesian (F), Jersey (J) and Simmental (S). There were 23 breed groups (B, H, and their crossbreds with F, J, and S) in the population. Fixed and mixed models were used to analyse the data. The fixed model considered herd-year-season, parity and breed group as fixed effects, and residual as random. The single and two-traits mixed animal repeatability models, considered the fixed effects of herd-year-season and parity subclasses, breed as a function of cow H, F, J, and S breed fractions and general heterosis as a function of heterozygosity, and the random additive animal, permanent environment, and residual effects. For the analysis of LY, LL was added as a fixed covariate to all models. Variance components and genetic parameters were estimated using average information restricted maximum likelihood procedures. The results indicated that all traits were affected (p<0.001) by the considered fixed effects. High grade $B{\times}F$ cows (3/16B 13/16F) had the highest least squares means (LSM) for LY ($2,490{\pm}178.9kg$), IY ($10.5{\pm}0.8kg$), PY ($12.7{\pm}0.9kg$), YD ($7.6{\pm}0.55kg$) and LL ($361.4{\pm}31.2d$), while B cows had the lowest LSM values for these traits. The LSM of LY, IY, YD, and PY tended to increase from the first to the fifth parity. Single-trait analyses yielded low heritability ($0.03{\pm}0.03$ and $0.08{\pm}0.02$) and repeatability ($0.14{\pm}0.01$ to $0.24{\pm}0.02$) estimates for LL, DP and parameter c. Medium heritability ($0.21{\pm}0.03$ to $0.33{\pm}0.04$) and repeatability ($0.27{\pm}0.02$ to $0.53{\pm}0.01$) estimates were obtained for LY, IY, PY, YD and ln(a). Genetic correlations between LY, IY, PY, YD, ln(a), and LL ranged from 0.59 to 0.99. Spearman's rank correlations between sire estimated breeding values for LY, LL, IY, PY, YD, ln(a) and c were positive (0.67 to 0.99, p<0.001). These results suggested that selection for IY, PY, YD, or LY would genetically improve lactation milk yield in this Ethiopian dairy cattle population.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.91-91
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• 2017

Drought is the most serious abiotic stress limiting rice production. However, little progress has been made in the genetic analysis of drought tolerance, because it is a complex trait controlled by a number of genes and affected by various environmental factors. In here, we screened 218 rice genetic resources for drought tolerance at vegetative stage and selected 32 highly drought tolerant varieties in greenhouse. Under rain-fed conditions, Grain yield of Nagdong was decreased by 53.3% from 517 kg/10a to 241 kg/10a when compare to irrigation condition. By comparison, grain yield of Samgang was decreased by 23.6% from 550 kg/10a to 420 kg/10a. The variety Samgang exhibited strong drought tolerance and stable yield in rain-fed conditions and was selected for further study. To identify QTLs for drought tolerance, we examined visual drought tolerance (VDT) and relative water content (RWC) using a doubled haploid (DH) population consisted of 101 lines derived from a cross between Samgang (a drought tolerance variety) and Nagdong (a drought sensitive variety). Three QTLs for VDT were located on chromosomes 2, 6, and 11, respectively, and explained 41.8% of the total phenotypic variance. qVDT2, flanked by markers RM324 and S2016, explained 8.8% of the phenotypic variance with LOD score of 3.3 and an additive effect of -0.6. qVDT6 was flanked by S6022 and S6023 and explained 12.7% of the phenotypic variance with LOD score of 5.0 and an additive effect of -0.7. qVDT11, flanked by markers RM26765 and RM287, explained 19.9% of the phenotypic variance with LOD score of 7.1 and an additive effect of -1.0. qRWC11 was the only QTL for RWC to be identified; it was in the same locus as qVDT11. qRWC11 explained 19.6% of the phenotypic variance, with a LOD score of 4.0 and an additive effect of 9.7. To determine QTL effects on drought tolerance in rain-fed paddy conditions, seven DH lines were selected according to the number of QTLs they contained. Of the drought tolerance associated QTLs, qVDT2 and qVDT6 did not affect tiller formation, but qVDT11increased tiller number. Tiller formation was most stable when qVDT2 and qVDT11 were combined. DH lines with both of these drought tolerance associated QTLs exhibited the most stable tiller formation. These results suggest that qVDT11 is important for drought tolerance and stable tiller formation under drought stress condition in field.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.9
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• pp.1387-1399
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• 2020

Objective: The objective of this study was to estimate the genetic parameters and trends for milk, fat, and protein yields in the first three lactations of Thai dairy cattle using a 3-trait,-3-lactation random regression test-day model. Methods: Data included 168,996, 63,388, and 27,145 test-day records from the first, second, and third lactations, respectively. Records were from 19,068 cows calving from 1993 to 2013 in 124 herds. (Co) variance components were estimated by Bayesian methods. Gibbs sampling was used to obtain posterior distributions. The model included herd-year-month of testing, breed group-season of calving-month in tested milk group, linear and quadratic age at calving as fixed effects, and random regression coefficients for additive genetic and permanent environmental effects, which were defined as modified constant, linear, quadratic, cubic and quartic Legendre coefficients. Results: Average daily heritabilities ranged from 0.36 to 0.48 for milk, 0.33 to 0.44 for fat and 0.37 to 0.48 for protein yields; they were higher in the third lactation for all traits. Heritabilities of test-day milk and protein yields for selected days in milk were higher in the middle than at the beginning or end of lactation, whereas those for test-day fat yields were high at the beginning and end of lactation. Genetics correlations (305-d yield) among production yields within lactations (0.44 to 0.69) were higher than those across lactations (0.36 to 0.68). The largest genetic correlation was observed between the first and second lactation. The genetic trends of 305-d milk, fat and protein yields were 230 to 250, 25 to 29, and 30 to 35 kg per year, respectively. Conclusion: A random regression model seems to be a flexible and reliable procedure for the genetic evaluation of production yields. It can be used to perform breeding value estimation for national genetic evaluation in the Thai dairy cattle population.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.9
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• pp.1216-1222
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• 2012

Somatic cells count (SCC), milk yield (MY) and pedigree information of 2,791 first lactation cows that calved between 1990 and 2010 on 259 Thai farms were used to estimate genetic parameters and trends for SCC and its genetic association with MY. The SCC were log-transformed (lnSCC) to make them normally distributed. An average information-restricted maximum likelihood procedure was used to estimate variance components. A bivariate animal model that considered herd-yr-season, calving age, and regression additive genetic group as fixed effects, and animal and residual as random effects was used for genetic evaluation. Heritability estimates were 0.12 (SE = 0.19) for lnSCC, and 0.31 (SE = 0.06) for MY. The genetic correlation estimate between lnSCC and MY was 0.26 (SE = 0.59). Mean yearly estimated breeding values during the last 20 years increased for SCC (49.02 cells/ml/yr, SE = 26.81 cells/ml/yr; p = 0.08), but not for MY (0.37 kg/yr, SE = 0.87 kg/yr; p = 0.68). Sire average breeding values for SCC and MY were higher than those of cows and dams (p<0.01). Heritability estimates for lnSCC and MY and their low but positive genetic correlation suggested that selection for low SCC may be feasible in this population as it is in other populations of dairy cows. Thus, selection for high MY and low SCC should be encouraged in Thai dairy improvement programs to increase profitability by improving both cow health and milk yield.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.9
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• pp.1242-1246
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• 2003

Data pertained to 335 crossbred cows comprising of 1/2 Friesian (F) + 1/2 Hariana (H), 1/2 F + 1/4 Jersey (J) + 1/4 H, 1/2 F + 1/4 Brown Swiss (BS) + 1/4 H, 1/2 F + 1/4 Red Dane (R) + 1/4 H, FR (I) and FRH (I) genetic groups extending over a period of 21 years (1970-1990) maintained at Animal Farm of CCS HAU, Hisar. The averages for first lactation milk yield was $2,486.24{\pm}80.26kg$ and peak yield of first three lactation were $11.35{\pm}0.72kg$, $13.97{\pm}0.60kg$ and $16.02{\pm}0.42kg$, respectively. The lifetime milk production was observed as $11,305.16{\pm}1,004.52kg$ in crossbred cattle. The average first lactation fat yield was observed as $102.06{\pm}0.01kg$ and peak fat yield of first three lactation were $0.458{\pm}0.01$, $0.490{\pm}0.01$ and $0.500{\pm}0.02kg$, respectively. The lifetime fat production was estimated as $502.31{\pm}45.90kg$. LTMP and LTFP had reasonably good additive genetic variance which could be exploited either through mass selection/combined with family or pedigree selection. FLMY, peak yields and LTMP had significant positive phenotypic correlation with FLFY and LTFP and the correlation at the genetic level were also higher and positive for these traits. Finally, peak week milk yield of first lactation (PMY1) was the earliest available trait having desirable and significant correlation at phenotypic and positive at genetic level with FLFY, PFY1 and PFY2, PFY3 and LTFP and selection for this trait will help in early evaluation of sires and dams and will increase genetic advancement per unit of time.

• Journal of Animal Science and Technology
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• v.55 no.2
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• pp.103-107
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• 2013

A crucial first step in the planning of any scientific experiment is to evaluate an appropriate sample size to permit sufficient statistical power to detect the desired effect. In this study, we investigated the optimal sample size of quantitative trait locus (QTL) linkage analysis for simple random sibship samples in pedigreed chicken populations, under the variance component framework implemented in the genetic power calculator program. Using the program, we could compute the statistical power required to achieve given sample sizes in variance component linkage analysis in random sibship data. For simplicity, an additive model was taken into account. Power calculations were performed to relate sample size to heritability attributable to a QTL. Under the various assumptions, comparative power curves indicated that the power to detect QTL with the variance component method is highly affected by a function of the effect size of QTL. Hence, more power can be achievable for QTL with a larger effect. In addition, a marked improvement in power could be obtained by increasing the sibship size. Thus, the use of chickens is advantageous regarding the sampling unit issue, since desirable sibship size can be easily obtained compared with other domestic species.

• Journal of Sericultural and Entomological Science
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• v.35 no.2
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• pp.100-104
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• 1993

The genetics analysis for weight of matured silkworm(WMS) and number of eggs produced per moth(NEM) was studied by the seven parents diallel. Mean squares of additive effect, dominant effect, maternal effect and reciprocal effect were significant for two characters observed. The component of genetic variance analysis for WMS and NEM showed that dominant effect was higher than additive effect. Narrow sense heritability(h2ns) estimates were 0.773 and 0.228, in the WMS and NEM. The estimate of broad sense heritability(h2bs) value was higher than that of h2ns because of the low importance of dominance effect. Incomplete dominance was shown by Vr-Wr graphic analysis in the weight of matured silkworm and overdominance in the number of eggs produced per moth. In general combining ability effect, Jam 107 and Jam 124 was showed positively high for WMS and Jam 107 and S1 was expressed positively high for NEM. In specific combining ability effect, hybrids in S1XC51, S1XJam124 and Jam 107XJam 108 were exhibited positively high for WMS and Jam 107XN63, S1XC51, N74XJam 108 and Jam 107XJam 108 were found positively high for NEM.