Estimates Of Phenotypic Correlations Research Articles

Estimation of genetic parameters for maintenance energy requirements and residual feed intake in Nellore cattle.

We estimated heritabilities and genetic and phenotypic correlation estimates for maintenance energy requirements (NEmR), residual feed intake (RFI), growth, carcass and reproductive indicator traits, using data from 41 feed efficiency trials in Brazil, comprising 4381 males and females. Continuous traits were analysed using a linear animal model and threshold traits were analysed using a threshold animal model. The heritability estimates were low for RFI (0.190) and NEmR (0.193); other heritabilities were mainly moderate (growth and carcass traits) or high (sexual precocity traits). The genetic correlation of RFI with NEmR was high (0.701). The genetic correlations of NEmR were low with carcass and reproductive traits, and moderate with growth traits. Thus, selection to improve weaning weight and female sexual precocity indicator traits would not affect maintenance energy requirement. Genetic selection to reduce maintenance energy requirements is feasible and would also reduce DMI and RFI. Selection to improve RFI can be used to identify animals with lower maintenance energy requirements. Long-term selection to reduce RFI and NEmR would have favourable effects on yearling weight, carcass muscle indicator traits and female sexual precocity. Genetic (co)variance component estimates for NEmR, in conjunction with economic values of selection criteria, may be used to develop novel approaches for genetic selection to improve efficiency of beef production.

Estimating genetic parameters of digital behavior traits and their relationship with production traits in purebred pigs

BackgroundWith the introduction of digital phenotyping and high-throughput data, traits that were previously difficult or impossible to measure directly have become easily accessible, offering the opportunity to enhance the efficiency and rate of genetic gain in animal production. It is of interest to assess how behavioral traits are indirectly related to the production traits during the performance testing period. The aim of this study was to assess the quality of behavior data extracted from day-wise video recordings and estimate the genetic parameters of behavior traits and their phenotypic and genetic correlations with production traits in pigs. Behavior was recorded for 70 days after on-test at about 10 weeks of age and ended at off-test for 2008 female purebred pigs, totaling 119,812 day-wise records. Behavior traits included time spent eating, drinking, laterally lying, sternally lying, sitting, standing, and meters of distance traveled. A quality control procedure was created for algorithm training and adjustment, standardizing recording hours, removing culled animals, and filtering unrealistic records.ResultsProduction traits included average daily gain (ADG), back fat thickness (BF), and loin depth (LD). Single-trait linear models were used to estimate heritabilities of the behavior traits and two-trait linear models were used to estimate genetic correlations between behavior and production traits. The results indicated that all behavior traits are heritable, with heritability estimates ranging from 0.19 to 0.57, and showed low-to-moderate phenotypic and genetic correlations with production traits. Two-trait linear models were also used to compare traits at different intervals of the recording period. To analyze the redundancies in behavior data during the recording period, the averages of various recording time intervals for the behavior and production traits were compared. Overall, the average of the 55- to 68-day recording interval had the strongest phenotypic and genetic correlation estimates with the production traits.ConclusionsDigital phenotyping is a new and low-cost method to record behavior phenotypes, but thorough data cleaning procedures are needed. Evaluating behavioral traits at different time intervals offers a deeper insight into their changes throughout the growth periods and their relationship with production traits, which may be recorded at a less frequent basis.

Correlations and path analysis of second-crop corn hybrids for maximum grain yield performance

The aim was to estimate the correlation coefficients and their direct and indirect effects through path analysis between agronomic traits that modulate the grain yield of second-crop corn hybrids. The hybrids SYN7G17 TL, 30F53VYHR, B2433PWU and AG 8700 PRO3 were employed. The following agronomic traits were evaluated: leaf nitrogen content, ear height, ear length, ear diameter, number of rows of grains per ear, number of grains per row, mass of a thousand grains, grain yield and grain protein content. Estimates of phenotypic correlation of all combinations of traits were calculated, and then the development of phenotypic correlations in direct and indirect effects was evaluated through path analysis, where grain yield was considered the main variable and the others were considered explanatory variables. Grain yield correlated strongly and positively with thousand-grain mass (0.83) and ear diameter (0.72). In the path analysis to tested conditions, no significant indirect effect was observed. However, the mass of a thousand grains and the ear diameter had a significant direct effect on the grain yield of corn, indicating that the selection of these characteristics can help to improve the grain yield in lines of corn

Estimation of Genetic Parameters for Weights at Different Ages in Anatolian Buffalo Calves

Background: The determination of the breeding potential and direction of the population in terms of traits of interest depends on the genetic variation. Therefore, it is essential to know the genetic parameters of economic traits to improve yields in animal breeding. The objective of this study was to investigate the heritability, genetic and phenotypic correlations among growth traits in Anatolian buffaloes of ìstanbul province. Methods: A total records of 7649 birth weights, 4623 sixth-month weights and 3133 yearling weights belonging to buffalo calves born between 2012 and 2021 were used. Genetic and phenotypic parameters were estimated from univariate and bivariate animal model using restricted maximum likelihood (REML) procedure in Wombat software. Village, year, season, sex and age of dam were considered as fixed effects and animal additive genetic effect was taken as random effect. Result: The heritability estimates for birth, sixth-month and yearling weights were 0.14±0.03; 0.22±0.05; 0.39±0.07 respectively. Genetic and phenotypic correlations among growth traits were generally significant and positive and ranged from 0.28±0.02 to 0.97±0.02. As a consequence, the moderate to high estimates of heritability, genetic and phenotypic correlations on growth traits showed that there were some opportunities for genetic improvement in buffaloes of ìstanbul. These genetic parameters should be considered in selection programs.

GWAS and genetic and phenotypic correlations of plasma metabolites with complete blood count traits in healthy young pigs reveal implications for pig immune response.

Introduction: In this study estimated genetic and phenotypic correlations between fifteen complete blood count (CBC) traits and thirty-three heritable plasma metabolites in young healthy nursery pigs. In addition, it provided an opportunity to identify candidate genes associated with variation in metabolite concentration and their potential association with immune response, disease resilience, and production traits. Methods: The blood samples were collected from healthy young pigs and Nuclear Magnetic Resonance (NMR) was used to quantify plasma metabolites. CBC was determined using the ADVIA® 2120i Hematology System. Genetic correlations of metabolite with CBC traits and single step genome-wide association study (ssGWAS) were estimated using the BLUPF90 programs. Results: Results showed low phenotypic correlation estimates between plasma metabolites and CBC traits. The highest phenotypic correlation was observed between lactic acid and plasma basophil concentration (0.36 ± 0.04; p < 0.05). Several significant genetic correlations were found between metabolites and CBC traits. The plasma concentration of proline was genetically positively correlated with hemoglobin concentration (0.94 ± 0.03; p < 0.05) and L-tyrosine was negatively correlated with mean corpuscular hemoglobin (MCH; -0.92 ± 0.74; p < 0.05). The genomic regions identified in this study only explained a small percentage of the genetic variance of metabolites levels that were genetically correlated with CBC, resilience, and production traits. Discussion: The results of this systems approach suggest that several plasma metabolite phenotypes are phenotypically and genetically correlated with CBC traits, suggesting that they may be potential genetic indicators of immune response following disease challenge. Genomic analysis revealed genes and pathways that might interact to modulate CBC, resilience, and production traits.

Genetic parameter estimates for litter traits in Jakhrana breed of Indian goat

The litter size and litter weight are the most important indicators of growth production system in goats as they are directly related to the survival and growth of the kids. The present attempt was made to estimate genetic parameters of litter traits such as litter size at birth (LSB), litter size at weaning (LSW), litter weight at birth (LWB) and litter weight at weaning (LWW) of Jakhrana breed of Indian goat. These traits were subjected to study variation due to direct additive genetic effects by adjusting non-genetic factors under linear mixed model. The data of litter records of 101 Jakhrana goats including pedigree information were processed and the results showed that the least-square means for LSB, LSW, LWB and LWW were 1.20 ± 0.05, 1.19 ± 0.05, 3.08 ± 0.11 and 12.11 ± 0.49, respectively. The direct heritability estimates for LSB, LSW, LWB and LWW were 0.17, 0.01, 0.001 and 0.10, respectively. The genetic (0.70–0.97) and phenotypic (0.61–0.92) correlation estimates among litter traits were high and positive. This study indicated that the additive variation among the early reproductive traits was low in range which does not provide a warrant for the improvement through selection. However, the evaluation of these traits has provided the current state of litter performance of Jakhrana goat which may be upgraded by managerial practices specially care and feeding of pregnant goats.

Heritabilities and genetic and phenotypic correlations for milk production and fertility traits of spring-calved once-daily or twice-daily milking cows in New Zealand

The objectives of this study were to estimate the genetic and phenotypic correlations and heritabilities for milk production and fertility traits in spring-calved once-daily (OAD) milking cows for the whole season in New Zealand and compare those estimates with twice-daily (TAD) milking cows. Data used in the study consisted of 69,252 first parity cows from the calving seasons 2015-2016 to 2017-2018 in 113 OAD and 531 TAD milking herds. Heritability estimates for production and fertility traits were obtained through single-trait animal models, and estimates of genetic and phenotypic correlations were obtained through bivariate animal models. Heritability estimates of production traits varied from 0.26 to 0.61 in OAD and from 0.13 to 0.63 in TAD. Heritability estimates for fertility traits were low in both OAD and TAD milking cow populations, and estimates were consistent (OAD: 0.01 to 0.10 and TAD: 0.01 to 0.08) across milking regimens. Estimates of phenotypic and genetic correlations among production traits were consistent across populations. In both populations, phenotypic correlations between milk production and fertility traits were close to zero, and most of the genetic correlations were antagonistic. In OAD milking cows, genetic correlations of milk and lactose yields with the start of mating to conception, 6-wk in-calf, not-in-calf, and 6-wk calving rate were close to zero. Interval from first service to conception was negatively genetically correlated with milk and lactose yields in OAD milking cows. Protein percentage was positively genetically correlated with 3-wk and 6-wk submission, 3-wk in-calf, 6-wk in-calf, first service to conception, 3-wk calving, and 6-wk calving rate in the TAD milking cow population, but these correlations were low in the OAD milking cow population. Further studies are needed to understand the relationship of protein percentage and fertility traits in the OAD milking system. The phenotypic correlations between fertility traits were similar in OAD and TAD milking populations. Genetic correlations between fertility traits were strong (≥0.70) in cows milked TAD, but genetic correlations varied from weak to strong in cows milked OAD. Further research is required to evaluate the interaction between genotype by milking regimen for fertility traits in terms of sire selection in the OAD milking cow population.

Estimates of genetic and phenotypic parameters for feeding behaviour and feed efficiency-related traits in Nelore cattle.

The objective of this study was to obtain (co)variance components, heritability, and genetic and phenotypic correlation estimates for feed efficiency and feed behaviour-related indicator traits. Further, it aimed to predict the direct and correlated responses for feed efficiency traits when selection was applied for feeding behaviour-related traits in Nelore cattle. Phenotypic records (n=4840) from 125 feed efficiency tests (RFI: Residual feed intake and DMI: Dry matter intake) carried out between 2011 and 2018 were considered in this study. Animals belonged to five farms located in two Brazilian geographical regions (Midwest and Southeast). Animals under similar management and environmental conditions in the feedlot were evaluated when they attained an average of 13.5± 4.15 months of age. Feed behaviour-related traits were also obtained, including meal criteria (MC), meal frequency (MF), average meal duration (AMD), meal duration (MD), average consumption per meal (ACM), and consumption rate (CR) through the GrowSafe System® electronic bunk system. The contemporary groups for all traits were composed of farm, management group, feed efficiency test, sex, and birth year. The (co)variance components were estimated using the restricted maximum likelihood method considering a multi-trait (n=8) animal model. The heritability estimates for RFI (0.23± 0.02), DMI (0.31± 0.02), MF (0.65± 0.02), AMD (0.29± 0.02), ACM (0.24± 0.02), MD (0.41± 0.02), MC (0.48± 0.02), and CR (0.42± 0.02) were moderate to high. The highest genetic correlation was obtained between CR and MD (-0.91 ± 0.04), MD and AMD (0.73± 0.03), CR and AMD (-0.68± 0.04), and RFI and DMI (0.81± 0.02). The highest phenotypic correlation was between ACM and AMD (0.76 ± 0.02), DMI and MD (0.77± 0.02), and DMI and RFI (0.77± 0.02). Genetic improvement for feed efficiency and feeding behaviour-related traits is feasible and the results obtained herein provided valuable information regarding the genetic background of Nelore feeding behaviour-related traits. The genetic association between feeding behaviour and feed efficiency-related traits suggested that animals spending less time feeding at a low feeding rate also had lower DMI and higher feed efficiency (RFI), and likely had lower energy maintenance requirements. The relative efficiency of selection showed that feeding behaviour-related traits were not adequate indicator traits to improve RFI and DMI. The DMI might be an effective selection criterion to improve RFI and reduce the herd's maintenance requirements.

Cross-trait assortative mating is widespread and inflates genetic correlation estimates.

The observation of genetic correlations between disparate human traits has been interpreted as evidence of widespread pleiotropy. Here, we introduce cross-trait assortative mating (xAM) as an alternative explanation. We observe that xAM affects many phenotypes and that phenotypic cross-mate correlation estimates are strongly associated with genetic correlation estimates (R2=74%). We demonstrate that existing xAM plausibly accounts for substantial fractions of genetic correlation estimates and that previously reported genetic correlation estimates between some pairs of psychiatric disorders are congruent with xAM alone. Finally, we provide evidence for a history of xAM at the genetic level using cross-trait even/odd chromosome polygenic score correlations. Together, our results demonstrate that previous reports have likely overestimated the true genetic similarity between many phenotypes.

Genetic variability and correlation studies in chickpea (Cicer arietinum L.)

The present investigation on genetic variability and correlation studies in chickpea (Cicer arietinum L.) were carried out with 25 genotypes in a Randomized Block Design with three replications and observations were recorded on five randomly selected plants for 13 characters to study the amount of genetic variability, correlation, heritability at field experimentation center, department of genetics and plant breeding, Sam Higginbottom university of agriculture, technology and sciences, Prayagraj during Rabi-2019-2020. a detailed analysis of the results on per se performances revealed PHULE-G-5 followed by ICC-244263, RVG-202 and NEC-799, CSQ-512. Found superior for seed yield over the check (PUSA-362). Higher estimates of phenotypic and genotypic co-efficient of variation were observed for number of primary branches and number of pods per plant. High heritability was observed in number of primary branches number of seeds per plant. High genetic advance and genetic advance has percentage mean was observed in harvest index. High estimates of phenotypic correlation and genotypic correlation were recorded for test weight and biological yield per plant maximum positive direct effect were observed in test weight by biological yield, number of pods per plant and harvest index.

Factors affecting average daily gain in Sonadi sheep

Data on 1408 Sonadi lambs born during 2012 to 2019 at ICAR-Mega Sheep Seed Project, College of Veterinary and Animal Science, Navania (Rajasthan) were analyzed to assess the effect of period, season, sex and type of birth on average daily gain (ADG) traits. The overall least squares means for ADG were 77.69±3.53, 48.81±3.04, 34.09±3.04 and 55.22±4.06 g for ADG1 (0–3M), ADG2 (3–6M), ADG3 (6–9M) and ADG4 (9–12M), respectively. Period and sex of lamb had significant (p<0.01) effect on all ADG traits. Season of birth had significant (p<0.01) effect on ADG4 only. Type of birth had significant (p<0.05) effect on ADG1 only. Heritability estimates for ADG1, ADG2, ADG3 and ADG4 were 0.77±0.17, 0.24±0.09, 0.41±0.13 and 0.07±0.11, respectively. Genetic correlation was negative between ADG1 and ADG3 as well as between ADG1 and ADG4 whereas positive among other ADGs. The estimates of phenotypic correlations among average daily gain were negative and low to high. The results indicated that growth rate in Sonadi lambs was higher during pre-weaning age which declined with advancement of age. To improve the performance, the environmental factors should be given weightage in the management of flocks.

Heritability and genetic correlations of plasma metabolites of pigs with production, resilience and carcass traits under natural polymicrobial disease challenge

Metabolites in plasma of healthy nursery pigs were quantified using nuclear magnetic resonance. Heritabilities of metabolite concentration were estimated along with their phenotypic and genetic correlations with performance, resilience, and carcass traits in growing pigs exposed to a natural polymicrobial disease challenge. Variance components were estimated by GBLUP. Heritability estimates were low to moderate (0.11 ± 0.08 to 0.19 ± 0.08) for 14 metabolites, moderate to high (0.22 ± 0.09 to 0.39 ± 0.08) for 17 metabolites, and highest for l-glutamic acid (0.41 ± 0.09) and hypoxanthine (0.42 ± 0.08). Phenotypic correlation estimates of plasma metabolites with performance and carcass traits were generally very low. Significant genetic correlation estimates with performance and carcass traits were found for several measures of growth and feed intake. Interestingly the plasma concentration of oxoglutarate was genetically negatively correlated with treatments received across the challenge nursery and finisher (− 0.49 ± 0.28; P < 0.05) and creatinine was positively correlated with mortality in the challenge nursery (0.85 ± 0.76; P < 0.05). These results suggest that some plasma metabolite phenotypes collected from healthy nursery pigs are moderately heritable and genetic correlations with measures of performance and resilience after disease challenge suggest they may be potential genetic indicators of disease resilience.

Genetic and non-genetic factors affecting first parity growth, reproductive and lactation traits in Barbari goats under semi-intensive management in semi-arid region of India

Barbari is most preferred goat breed of commercial farmers in India and information on its first parity growth, reproduction and production traits are valuable for making present and future genetic progress of flock. Data for present study pertains to 2,554 kids, progeny of 227 sires and 1645 dam born during 2001 to 2019 at Central Institute for Research on Goats, Makhdoom, Mathura, Uttar Pradesh. The least squares means of body weight of kids at birth, 3, 6, 9 and 12 months of age were 1.69±0.02, 7.48±0.13, 11.45±0.21, 16.08±0.28 and 20.21±0.33 kg, respectively. Period, sex, type of birth, and weight of dam at kidding were significant sources of non-genetic variation affecting body weights. The least squares mean of weight at first conception, weight at first kidding, age at first conception, age at first kidding and first gestation period were 18.04±0.07 kg, 21.79±0.09 kg, 381.65±2.51 days, 523.23±2.52 days and 143.33±0.21 days, respectively. Period of birth was major source of variation though these traits were also significantly affected by season and type of birth. The least squares means of first lactation 90-days milk yield, 140-days milk yield, total Lactation period milk yield, first lactation Length, milk yield per day of first lactation length and milk yield per day of first kidding interval were 50.22±0.41 litre, 69.94±1.05 litre, 57.32±0.53 litre, 123.01±0.53 days, 48.91±0.35 litre and 19.39±0.22 litres, respectively. Period, season, type of kidding, age and weight of dam at kidding were significant sources of non-genetic variation affecting above lactation traits. The h2 for growth and production traits were moderate whereas low to moderate for reproductive traits except weight at first conception and kidding which have moderate h2 estimates. The genetic and phenotypic correlations among the growth traits at different ages were moderate to high (0.3 to 0.8), however decrease with distant ages. Very high genetic and phenotypic correlation estimates were obtained among lactation traits suggesting that judicious selection of animals' for any lactation traits would yield consistent genetic improvement in the other milk production traits in the flock. The economic traits which were significantly influenced by non-genetic factors with high magnitude need attention for strategic management interventions such as planned breeding of females to avoid kidding in adverse weather conditions, better attention in suckling of milk for kids born with low birth weight, hygiene of shed, adequate supplementation of concentrate ration to those kids which have less pre-weaning growth regardless of type of birth, better nutrition level to maiden goats before and after mating and extension of weaning age for triplets by 10-15 days to obtain higher post weaning weight gains, optimization of breeding weight at first mating and strategic supplementary concentrate feeding as per milk yield.

Strong phenotypic trait correlations between mating partners do not result from assortative mating in wild great tits (Parus major)

There is considerable debate about the occurrence of assortative mating between phenotypic traits measured within natural populations. Meta-analyses have implied that assortative mating occurs generally in natural populations, but recent work indicates these conclusions largely result from biased data. Specifically, estimates of phenotypic correlations between mating partners do not solely result from nonrandom associations between individual-level traits of partners but also from other biological processes (joint phenotypic plasticity, indirect genetic effects), methodological practices (observer bias) and other unexplained residual correlations (e.g. correlated measurement error). This paper puts this critique to test. First, we estimated the overall phenotypic correlation between phenotypic traits of mating partners for a wild population of great tits. Second, we estimated various key variance components to reveal the extent to which phenotypic correlations between partners resulted from assortative mating, reversible plasticity, social partner effects and methodological practices. We performed our analyses for a range of phenotypic traits (body mass, breathing rate, exploration behaviour, wing and tarsus length) to derive general conclusions not hinging on the specifics of the traits involved. Our analyses support the conclusion that patterns of assortative mating exist at first glance but occur because of the biasing effects of correlated residuals likely caused by a combination of phenotypic responses to unknown environmental factors or measurement error-not because of intrinsic patterns of assortative mating.

Genetic analysis of egg production traits in turkeys (Meleagris gallopavo) using a single-step genomic random regression model

BackgroundEgg production traits are economically important in poultry breeding programs. Previous studies have shown that incorporating genomic data can increase the accuracy of genetic prediction of egg production. Our objective was to estimate the genetic and phenotypic parameters of such traits and compare the prediction accuracy of pedigree-based random regression best linear unbiased prediction (RR-PBLUP) and genomic single-step random regression BLUP (RR-ssGBLUP). Egg production was recorded on 7422 birds during 24 consecutive weeks from first egg laid. Hatch-week of birth by week of lay and week of lay by age at first egg were fitted as fixed effects and body weight as a covariate, while additive genetic and permanent environment effects were fitted as random effects, along with heterogeneous residual variances over 24 weeks of egg production. Predictions accuracies were compared based on two statistics: (1) the correlation between estimated breeding values and phenotypes divided by the square root of the trait heritability, and (2) the ratio of the variance of BLUP predictions of individual Mendelian sampling effects divided by one half of the estimate of the additive genetic variance.ResultsHeritability estimates along the production trajectory obtained with RR-PBLUP ranged from 0.09 to 0.22, with higher estimates for intermediate weeks. Estimates of phenotypic correlations between weekly egg production were lower than the corresponding genetic correlation estimates. Our results indicate that genetic correlations decreased over the laying period, with the highest estimate being between traits in later weeks and the lowest between early weeks and later ages. Prediction accuracies based on the correlation-based statistic ranged from 0.11 to 0.44 for RR-PBLUP and from 0.22 to 0.57 for RR-ssGBLUP using the correlation-based statistic. The ratios of the variances of BLUP predictions of Mendelian sampling effects and one half of the additive genetic variance ranged from 0.17 to 0.26 for RR-PBLUP and from 0.17 to 0.34 for RR-ssGBLUP. Although the improvement in accuracies from RR-ssGBLUP over those from RR-PBLUP was not uniform over time for either statistic, accuracies obtained with RR-ssGBLUP were generally equal to or higher than those with RR-PBLUP.ConclusionsOur findings show the potential advantage of incorporating genomic data in genetic evaluation of egg production traits using random regression models, which can contribute to the genetic improvement of egg production in turkey populations.

Estimation of genetic parameters for production and reproductive traits in Indian Karan-Fries cattle using multi-trait Bayesian approach.

Estimates of variance components are needed for implementing genetic selection. This study was conducted to genetic parameters for production and reproductive traits on Indian Karan-Fries cattle using multi-trait repeatability animal model. Data collected from ICAR-National Dairy Research Institute, Karnal, India (from 1988 to 2019) were used. Single-trait and multi-trait repeatability animal models were used for parameter estimation. The posterior mean of Heritability estimates for 305-day milk yield (305-DMY), lactation milk yield (LMY), lactation length (LL) were 0.20 ± 0.03, 0.19 ± 0.03 and 0.06 ± 0.02, respectively. For age at first calving (AFC), calving interval (CI), and days open (DO), the posterior mean of heritability estimates were 0.24 ± 0.08, 0.06 ± 0.01, and 0.07 ± 0.02, respectively. The repeatability estimates for 305-DMY, LMY, LL, CI, and DO were 0.37 ± 0.02, 0.34 ± 0.02, 0.15 ± 0.02, 0.09 ± 0.02, and 0.12 ± 0.02, respectively. Genetic correlation between milk production traits (305-DMY, LMY, and LL) was positive and strong (> 0.80). However, the genetic correlation between milk production trait and AFC ranges from - 0.31 to 0.12. Unfavorable strong genetic correlations were observed between production and reproductive traits (CI and DO) with values ranged from 0.5 to 0.7. Phenotypic correlations among 305-DMY, LMY, and LL were generally positive and high. The moderate heritability estimates and potential genetic variation for 305-DMY, TMY, and AFC suggested that genetic gain can be obtained for these traits through genetic selection. Low heritability estimates found for LL, CI and DO, indicating that the possibility of changing these traits through genetic selection is small. High genetic correlation observed between productive and fertility traits were unfavorable. The existed strong genetic and phenotypic correlation estimates between CI and DO indicates that recording only one of them would be sufficient in the herd. As the multi-trait model showed slight improvements in the h2 as well as r estimates for both productive and reproductive traits over univariate analysis, future selection with a multi-trait animal model applying Bayesian approach would be recommended.

Genetic Analysis Of Rabbit Litter Traits At Birth And Weaning

Data on 260 litters were used to provide therefore to estimate the heritability and estimates of heritability, repeatability, genetic and phenotypic correlations for litter traits at birth and at weaning. Breed, sire within breed and doe within sire effects were found to be significant, (P&lt;0.05) for litter size at birth and at weaning and for litter weight at birth and at weaning. Heritability estimates of 0.33±0.08, 0.38±0.02, 0.03±0.02 and 0.16±0.05 were obtained for litter birth weight, litter size at birth, litter size at weaning and litter weaning weight, respectively. Repeatability estimates were found to be generally moderate to high. Genetic and phenotypic correlations were positive and significant (P&lt;0.01). Selection for litter size at birth and litter birth weight are likely to result in improved litter size at weaning and litter weaning weight respectively.

GENETIC ASPECTS OF PREWEANING PERFORMANCE OF NDAMA CATTLE

Records on birth weight (BW), preweaning daily gain (PWG) and weaning weight (WW) of Ndama beef cattle were obtained from the Fashola Livestock Farm in Oyo State of Nigeria between 1954 and 1964 and were analyzed to estimate the phenotypic and genetic parameters of preweaning performances of this breed of cattle. For birth weight, preweaning daily gain and weaning weight respectively heritability was estimated as 0.13 ± 0.08, 0.30 ± 0.14 and 0.25 ± 0.12 from paternal half-sib relationship. The estimates of genetic and phenotypic correlations obtained from these data among the three pre-weaning traits were found to be similar to those already in the general literature on beef cattle.

INHERITANCE OF GROWTH AND LACTATION PARAMETERS IN YANKASA SHEEP

Estimates of genetic and phenotypic parameters for lactation records of 143 ewes and growth performance of 134 lambs were examined using the paternal half-sib mixed model analysis. Heritability (h2) estimates for the curve parameters were 1.4, 0.3, 0.2 and 0.5 for a (level of general production), b (pre-peak curvature), c (post-peak curva-ture) and total lactation (T). The estimates of phenotypic and genetic correlations between the various curve parameters were mostly positive and moderate in magnitude. For the growth parameters, h2 estimates of 0.3 and 0.7 were obtained for birth weight (BWT) and 90- day weaning weight (WWT) respectively. The genetic and phenotypic correlations between these traits were 0.7 and 0.3 respectively. In conclusion the moderate estimates of h2 obtained for curve parameters in this study indicate that improvement of milk production performance of the Yankasa sheep through selection is possible. Similarly, the magnitude of the estimate of correlations between BWT and WWT probably indicates that selection based on BWT will improve WWT. Furthermore, preliminary, culling based on BWT is also possible.

ESTIMATES OF PHENOTYPIC AND GENETIC CORRELATIONS IN WEST AFRICAN DWARF GOATS

Records on 848 West African dwarf goat kids and 220 kiddings over a period of eight year's (1982-1989) were analyzed. The records were used to provide estimates of phenotypic and venetic correlations among parity, kidding interval, litter size at birth and body weight at various ages. Plenotypic correlation coefficients of +0.33 (P&lt;0.01) and -0,17 (P&lt;0.01) were obtained when parity was correlated with litter size at birth and kidding interval respectively. Phenotypic correlations among body weights were generally positive and significant (P&lt;0.01). Parity was positively correlated (P&lt;0.01) with body weight at the various ages except at 1 year (P&gt;0.05). Litter size was, however, negatively correlated (P&lt;0.01) with body weight at the various ages except at 1 year (P&lt;0.05). The genetic correlations among body weights at variuus ages were positive and significant (P&lt;0.01). Selection for body weight at in earlier age especially at 3 months is likely to result in improvement of yearling body weight.