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  Subjects -> AGRICULTURE (Total: 821 journals)
    - AGRICULTURAL ECONOMICS (74 journals)
    - AGRICULTURE (576 journals)
    - CROP PRODUCTION AND SOIL (95 journals)
    - POULTRY AND LIVESTOCK (48 journals)


Showing 1 - 48 of 48 Journals sorted alphabetically
Acta Agriculturae Scandinavica, Section A - Animal Sciences     Hybrid Journal   (Followers: 9)
Acta Scientiarum. Animal Sciences     Open Access   (Followers: 3)
Advances in Animal Biosciences     Full-text available via subscription   (Followers: 9)
African Journal of Livestock Extension     Full-text available via subscription   (Followers: 1)
Animal Biotechnology     Hybrid Journal   (Followers: 10)
Animal Cells and Systems     Hybrid Journal   (Followers: 4)
Animal Nutrition     Open Access   (Followers: 17)
Animal Production     Open Access   (Followers: 3)
Animal Production Science     Hybrid Journal   (Followers: 2)
Animal Reproduction     Open Access   (Followers: 3)
Animal Reproduction Science     Hybrid Journal   (Followers: 6)
Animal Research International     Full-text available via subscription   (Followers: 6)
Animal Science Journal     Hybrid Journal   (Followers: 6)
Archives Animal Breeding     Open Access   (Followers: 3)
Archives of Animal Nutrition     Hybrid Journal   (Followers: 7)
Asian-Australasian Journal of Animal Sciences     Open Access  
Bangladesh Journal of Animal Science     Open Access   (Followers: 2)
Boletim de Indústria Animal     Open Access  
Bulletin of Animal Health and Production in Africa     Full-text available via subscription   (Followers: 2)
Canadian Journal of Animal Science     Hybrid Journal   (Followers: 5)
Indian Journal of Animal Sciences     Open Access   (Followers: 7)
International Journal of Health, Animal Science and Food Safety     Open Access   (Followers: 3)
International Journal of Livestock Production     Open Access   (Followers: 1)
Journal of Animal Breeding and Genetics     Hybrid Journal   (Followers: 4)
Journal of Animal Science     Full-text available via subscription   (Followers: 13)
Journal of Animal Science and Biotechnology     Open Access   (Followers: 6)
Journal of Animal Science and Technology     Open Access   (Followers: 2)
Journal of Applied Animal Nutrition     Hybrid Journal   (Followers: 3)
Journal of Applied Animal Welfare Science     Hybrid Journal   (Followers: 14)
Journal of Applied Poultry Research     Hybrid Journal   (Followers: 5)
Journal of World's Poultry Research     Open Access   (Followers: 2)
Jurnal Agripet     Open Access   (Followers: 1)
Jurnal Ilmu Produksi dan Teknologi Hasil Peternakan     Open Access  
La Chèvre     Full-text available via subscription  
Nigerian Journal of Animal Science     Full-text available via subscription   (Followers: 1)
Nutrición Animal Tropical     Open Access   (Followers: 2)
Online Journal of Animal and Feed Research     Open Access   (Followers: 4)
Open Journal of Animal Sciences     Open Access   (Followers: 5)
Porcine Health Management     Open Access  
Poultry Science     Hybrid Journal   (Followers: 4)
Poultry Science Journal     Open Access   (Followers: 2)
Research in Agriculture, Livestock and Fisheries     Open Access  
Revista Brasileira de Saúde e Produção Animal     Open Access  
Revista Mexicana de Ciencias Pecuarias     Open Access   (Followers: 1)
The Professional Animal Scientist     Hybrid Journal  
Tropical Animal Health and Production     Hybrid Journal  
Veeplaas     Full-text available via subscription  
World Rabbit Science     Open Access  
Journal Cover Journal of Animal Breeding and Genetics
  [SJR: 0.737]   [H-I: 39]   [4 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0931-2668 - ISSN (Online) 1439-0388
   Published by John Wiley and Sons Homepage  [1597 journals]
  • On individual‐specific prediction of hidden inbreeding depression
    • Authors: J. Casellas
      Abstract: Inbreeding depression is caused by increased homozygosity in the genome and merges two genetic mechanisms, a higher impact from recessive mutations and the waste of overdominance contributions. It is of major concern for the conservation of endangered populations of plants and animals, as major abnormalities are more frequent in inbred families than in outcrosses. Nevertheless, we lack appropriate analytical methods to estimate the hidden inbreeding depression load (IDL) in the genome of each individual. Here, a new mixed linear model approach has been developed to account for the inbreeding depression‐related background of each individual in the pedigree. Within this context, inbred descendants contributed relevant information to predict the IDL contained in the genome of a given ancestor; moreover, known relationships spread these predictions to the remaining individuals in the pedigree, even if not contributing inbred offspring. Results obtained from the analysis of weaning weight in the MARET rabbit population demonstrated that the genetic background of inbreeding depression distributed heterogeneously across individuals and inherited generation by generation. Moreover, this approach was clearly preferred in terms of model fit and complexity when compared with classical approaches to inbreeding depression. This methodology must be viewed as a new tool for a better understanding of inbreeding in domestic and wild populations.
      PubDate: 2017-12-11T21:21:26.653824-05:
      DOI: 10.1111/jbg.12308
  • A comparison of accuracy validation methods for genomic and
           pedigree‐based predictions of swine litter size traits using Large White
           and simulated data
    • Authors: A.M. Putz; F. Tiezzi, C. Maltecca, K.A. Gray, M.T. Knauer
      Abstract: The objective of this study was to compare and determine the optimal validation method when comparing accuracy from single‐step GBLUP (ssGBLUP) to traditional pedigree‐based BLUP. Field data included six litter size traits. Simulated data included ten replicates designed to mimic the field data in order to determine the method that was closest to the true accuracy. Data were split into training and validation sets. The methods used were as follows: (i) theoretical accuracy derived from the prediction error variance (PEV) of the direct inverse (iLHS), (ii) approximated accuracies from the accf90(GS) program in the BLUPF90 family of programs (Approx), (iii) correlation between predictions and the single‐step GEBVs from the full data set (GEBVFull), (iv) correlation between predictions and the corrected phenotypes of females from the full data set (Yc), (v) correlation from method iv divided by the square root of the heritability (Ych) and (vi) correlation between sire predictions and the average of their daughters' corrected phenotypes (Ycs). Accuracies from iLHS increased from 0.27 to 0.37 (37%) in the Large White. Approximation accuracies were very consistent and close in absolute value (0.41 to 0.43). Both iLHS and Approx were much less variable than the corrected phenotype methods (ranging from 0.04 to 0.27). On average, simulated data showed an increase in accuracy from 0.34 to 0.44 (29%) using ssGBLUP. Both iLHS and Ych approximated the increase well, 0.30 to 0.46 and 0.36 to 0.45, respectively. GEBVFull performed poorly in both data sets and is not recommended. Results suggest that for within‐breed selection, theoretical accuracy using PEV was consistent and accurate. When direct inversion is infeasible to get the PEV, correlating predictions to the corrected phenotypes divided by the square root of heritability is adequate given a large enough validation data set.
      PubDate: 2017-11-27T01:26:07.406634-05:
      DOI: 10.1111/jbg.12302
  • Effects of breed proportion and components of heterosis for semen traits
           in a composite cattle breed
    • Authors: N. Khayatzadeh; G. Mészáros, Y. T. Utsunomiya, F. Schmitz-Hsu, F. Seefried, U. Schnyder, M. Ferenčaković, J. F. Garcia, I. Curik, J. Sölkner
      Abstract: The aim of this study was to estimate the non‐additive genetic effects of the dominance component of heterosis as well as epistatic loss on semen traits in admixed Swiss Fleckvieh, a composite of Simmental (SI) and Red Holstein Friesian (RHF) cattle. Heterosis is the additional gain in productivity or fitness of cross‐bred progeny over the mid‐purebred parental populations. Intralocus gene interaction usually has a positive effect, while epistatic loss generally reduces productivity or fitness due to lack of evolutionarily established interactions of genes from different breeds. Genotypic data on 38,205 SNP of 818 admixed, as well as 148 RHF and 213 SI bulls as the parental breeds were used to predict breed origin of alleles. The genomewide locus‐specific breed ancestries of individuals were used to calculate effects of breed difference as well as the dominance component of heterosis, while proxies for two definitions of epistatic loss were derived from 100,000 random pairs of loci. The average Holstein Friesian ancestry in admixed bulls was estimated 0.82. Results of fitting different linear mixed models showed including the dominance component of heterosis considerably improved the model adequacy for three of the four traits. Inclusion of epistatic loss increased the accuracy of the models only for our new definition of the epistatic effect for two traits, while the other definition was so highly correlated with the dominance component that statistical separation was impossible.
      PubDate: 2017-11-22T03:48:11.625129-05:
      DOI: 10.1111/jbg.12304
  • BIBI: Bayesian inference of breed composition
    • Authors: C. A. Martínez; K. Khare, M. A. Elzo
      Abstract: The aim of this paper was to develop statistical models to estimate individual breed composition based on the previously proposed idea of regressing discrete random variables corresponding to counts of reference alleles of biallelic molecular markers located across the genome on the allele frequencies of each marker in the pure (base) breeds. Some of the existing regression‐based methods do not guarantee that estimators of breed composition will lie in the appropriate parameter space, and none of them account for uncertainty about allele frequencies in the pure breeds, that is, uncertainty about the design matrix. To overcome these limitations, we proposed two Bayesian generalized linear models. For each individual, both models assume that the counts of the reference allele at each marker locus follow independent Binomial distributions, use the logit link and pose a Dirichlet prior over the vector of regression coefficients (which corresponds to breed composition). This prior guarantees that point estimators of breed composition such as the posterior mean pertain to the appropriate space. The difference between these models is that model termed BIBI does not account for uncertainty about the design matrix, while model termed BIBI2 accounts for such an uncertainty by assigning independent Beta priors to the entries of this matrix. We implemented these models in a data set from the University of Florida's multibreed Angus‐Brahman population. Posterior means were used as point estimators of breed composition. In addition, the ordinary least squares estimator proposed by Kuehn et al. () (OLSK) was also computed. BIBI and BIBI2 estimated breed composition more accurately than OLSK, and BIBI2 had a 7.69% improvement in accuracy as compared to BIBI.
      PubDate: 2017-11-22T02:55:25.098032-05:
      DOI: 10.1111/jbg.12305
  • Adjusting for heterogeneity of experimental data in genetic evaluation of
           dry matter intake in dairy cattle
    • Authors: M. E. Uddin; T. Meuwissen, R. F. Veerkamp
      Abstract: The objectives of the present study were (i) to find the best fitted model for repeatedly measured daily dry matter intake (DMI) data obtained from different herds and experiments across lactations and (ii) to get better estimates of the genetic parameters and better genetic evaluations. After editing, there were 572,512 daily DMI records of 3,495 animals (Holstein cows) from 11 different herds across 13 lactations and the animals were under 110 different nutritional experiments. The fitted model for this data set was a univariate repeated‐measure animal model (called model 1) in which additive genetic and permanent environmental (within and across lactations) effects were fitted as random. Model 1 was fitted as two distinct models (called models 2 and 3) based on alternative fixed effect corrections. For unscaled data, each model (models 2 and 3) was fitted as a homoscedastic (HOM) model first and then as a heteroscedastic (HET) model. Then, data were scaled by multiplying with particular herd‐scaling factors, which were calculated by accounting for heterogeneity of phenotypic within‐herd variances. Models were selected based on cross‐validation and prediction accuracy results. Scaling factors were re‐estimated to determine the effectiveness of accounting for herd heterogeneity. Variance components and respective heritability and repeatability were estimated based on a pedigree‐based relationship matrix. Results indicated that the model fitted for scaled data showed better fit than the models (HOM or HET) fitted for unscaled data. The heritability estimates of the models 2 and 3 fitted for scaled data were 0.30 and 0.08, respectively. The repeatability estimates of the model fitted for scaled data ranged from 0.51 to 0.63. The re‐estimated scaling factor after accounting for heterogeneity of residual variances was close to 1.0, indicating the stabilization of residual variances and herd accounted for most of the heterogeneity. The rank correlation of EBVs between scaled and unscaled data ranged from 0.96 to 0.97.
      PubDate: 2017-11-20T04:30:26.70936-05:0
      DOI: 10.1111/jbg.12300
  • Gender differences for growth in North American Atlantic salmon
    • Abstract: An assumption in aquaculture of Atlantic salmon is that male and female growth within families is perfectly genetically correlated. That is, families would rank identically if based on male growth only or female growth only. Also, growth in freshwater and sea water is assumed to be highly correlated between males and females within families. However, structural analysis of the DNA of Atlantic salmon has found that the linkage maps of females differ significantly from that of males. Genetic variability for any trait measured on females could be greater or lesser than on males. Thus, male and female growth might be considered as separate traits giving rise to families ranking differently depending on gender. A multiple trait family model for weight and length at 3 years of age in Atlantic salmon according to gender was applied to data on North American Atlantic salmon obtained from the Oak Bay Hatchery in New Brunswick, Canada. Genetic correlations between male and female growth in both freshwater and sea water were estimated by Bayesian methods. The estimates support the possible existence of gender dimorphism in North American Atlantic salmon for growth traits.
  • Reducing bias in the dairy cattle single‐step genomic evaluation by
           ignoring bulls without progeny
    • Abstract: The number of genotyped animals has increased rapidly creating computational challenges for genomic evaluation. In animal model BLUP, candidate animals without progeny and phenotype do not contribute information to the evaluation and can be discarded. In theory, genotyped candidate animal without progeny can bring information into single‐step BLUP (ssGBLUP) and affect the estimation of other breeding values. We studied the effect of including or excluding genomic information of culled bull calves on genomic breeding values (GEBV) from ssGBLUP. In particular, GEBVs of genotyped bulls with daughters and GEBVs of young bulls selected into AI to be progeny tested (test bulls) were studied. The ssGBLUP evaluation was computed using Nordic test day (TD) model and TD data for the Nordic Red Dairy Cattle. The results indicate that genomic information of culled bull calves does not affect the GEBVs of progeny tested reference animals, but if genotypes of the culled bulls are used in the TD ssGBLUP, the genetic trend in the test bulls is considerably higher compared to the situation when genomic information of the culled bull calves is excluded. It seems that by discarding genomic information of culled bull calves without progeny, upward bias of GEBVs of test bulls is reduced.
  • Comparing deregression methods for genomic prediction of test‐day
           traits in dairy cattle
    • Abstract: We aimed to investigate the performance of three deregression methods (VanRaden, VR; Wiggans, WG; and Garrick, GR) of cows’ and bulls’ breeding values to be used as pseudophenotypes in the genomic evaluation of test‐day dairy production traits. Three scenarios were considered within each deregression method: (i) including only animals with reliability of estimated breeding value (RELEBV) higher than the average of parent reliability (RELPA) in the training and validation populations; (ii) including only animals with RELEBV higher than 0.50 in the training and RELEBV higher than RELPA in the validation population; and (iii) including only animals with RELEBV higher than 0.50 in both training and validation populations. Individual random regression coefficients of lactation curves were predicted using the genomic best linear unbiased prediction (GBLUP), considering either unweighted or weighted residual variances based on effective records contributions. In summary, VR and WG deregression methods seemed more appropriate for genomic prediction of test‐day traits without need for weighting in the genomic analysis, unless large differences in RELEBV between training population animals exist.
  • Plasticity effect of rider–horse interaction on genetic evaluations for
           Show Jumping discipline in sport horses
    • Abstract: To obtain a sport horse that excels in the highest levels of competition, breeders must take into account certain genetic and environmental factors that could influence the sport horse's performance, such as the rider–horse interaction (RHI). The main aim of this study was to describe this interaction in a genetic model by modelling it in relation to the horse's age. A total of 31,129 sport results from Spanish Sport Horses were used from a total of 1,101 animals evaluated, and these were grouped in three age levels and had been ridden by 606 different riders. Only riders who had ridden more than one horse (and vice‐versa) were considered for the analyses. Five linear models with different random effects were analysed according to the covariates, the homogeneity/heterogeneity of the RHI and the relevant residual random effects. The model of best fit was then selected for the genetic evaluation of the animal. In general, models including the RHI effect (M2, M4 and M5) fitted better than the other models, and the best fit was obtained for M4 (with heterogeneous residual variance). The genetic variance increased constantly with age, whereas heritability showed a response on three intervals. This study revealed the varied evolution of the RHI with age, showing the different “plastic abilities” of this relationship.
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  • A century later
  • Following one's scientific compass
  • Improving accuracy of genomic prediction in Brangus cattle by adding
           animals with imputed low‐density SNP genotypes
    • Abstract: Reliable genomic prediction of breeding values for quantitative traits requires the availability of sufficient number of animals with genotypes and phenotypes in the training set. As of 31 October 2016, there were 3,797 Brangus animals with genotypes and phenotypes. These Brangus animals were genotyped using different commercial SNP chips. Of them, the largest group consisted of 1,535 animals genotyped by the GGP‐LDV4 SNP chip. The remaining 2,262 genotypes were imputed to the SNP content of the GGP‐LDV4 chip, so that the number of animals available for training the genomic prediction models was more than doubled. The present study showed that the pooling of animals with both original or imputed 40K SNP genotypes substantially increased genomic prediction accuracies on the ten traits. By supplementing imputed genotypes, the relative gains in genomic prediction accuracies on estimated breeding values (EBV) were from 12.60% to 31.27%, and the relative gain in genomic prediction accuracies on de‐regressed EBV was slightly small (i.e. 0.87%–18.75%). The present study also compared the performance of five genomic prediction models and two cross‐validation methods. The five genomic models predicted EBV and de‐regressed EBV of the ten traits similarly well. Of the two cross‐validation methods, leave‐one‐out cross‐validation maximized the number of animals at the stage of training for genomic prediction. Genomic prediction accuracy (GPA) on the ten quantitative traits was validated in 1,106 newly genotyped Brangus animals based on the SNP effects estimated in the previous set of 3,797 Brangus animals, and they were slightly lower than GPA in the original data. The present study was the first to leverage currently available genotype and phenotype resources in order to harness genomic prediction in Brangus beef cattle.
  • Genetic analyses of linear profiling data on 3‐year‐old
           Swedish Warmblood horses
    • Abstract: A linear profiling protocol was introduced in 2013 at tests for 3‐year‐old Swedish Warmblood horses. In this protocol, traits are subjectively described on a nine‐point linear scale from one biological extreme to the other. This complements the traditional scoring where horses are evaluated in relation to the breeding objective. This study aimed to investigate the suitability of the linear information for genetic evaluation. Data on 22 conformation traits, 17 movement traits, 14 jumping traits and one temperament trait from 3,410 horses tested between 2013 and 2016 were analysed using an animal model. For conformation traits, the heritabilities ranged from 0.10 for description of hock joint from behind to 0.52 for shape of the neck. For movement traits, the highest heritability (0.54) was estimated for elasticity in trot and the lowest (0.08) for energy in walk. The heritabilities for jumping traits ranged from 0.05 for the ability to focus on the assignment to 0.57 for scope. Genetic correlations between linear traits and corresponding traditionally scored traits were strong (−0.37 to in many cases
  • Genetic monitoring of horses in the Czech Republic: A large‐scale study
           with a focus on the Czech autochthonous breeds
    • Abstract: We propose the first comprehensive in‐depth study monitoring horses in the Czech Republic. We scanned 9,289 animals from 44 populations for 17 equine STRs. Other equids analysed involved Equus przewalskii and Equus asinus. The total of 228 different alleles were detected, with the mean number of 13.4 per locus. The highest allelic richness (AR) was found in the Welsh Part Bred (6.01), followed by the Camargue (5.93) and Czech Sport Pony (5.91), whereas the Friesian exhibited the lowest AR (3.06). Interpopulation differences explained approximately nine per cent of the total genetic diversity. Reynold's genetic distance ranged from 0.003 between the Czech Warmblood and the Slovak Warmblood to 0.404 between the Friesian and donkeys. Close genetic proximity between the Silesian Noriker and Noriker was revealed. The Moravian Warmblood was better differentiated and more distant from the Czech Warmblood than the Kinsky Horse and retained the original genes of the old Austro‐Hungarian tribes. A high gene flow level and a lack of genetic structure were found in the seven studied populations. Despite the historical bottlenecks and previous inbreeding, the Czech‐Moravian Belgian Horse, Hucul, Old Kladruber Horse and Silesian Noriker did not suffer a serious loss of genetic diversity due to genetic drift/low effective population size. A NeighborNet dendrogram revealed breeds not classified in their groups according to the nomenclature (the Friesian, Hafling and Merens).
  • Detecting selection signatures on the X chromosome of the Chinese Debao
    • Abstract: The X chromosome shows a special interaction between demographic factors and genetic variation, and the analysis of X‐linked genomic variation can therefore provide insights into the unique effects of demography and selection on the horse genome that cannot be readily detected by autosomal markers. Debao (DB) ponies have experienced intense selective pressure for the development of their small stature (134 cm at adult height) as reference groups, both FST and XP‐EHH revealed that five regions on the X chromosome were under strong selection, resulting in 95 overlapping genes. Seven of these genes, SMS, PHEX, ACSL4, CHRDL1, CACNA1F, DKC1 and CDKL5, are involved in bone development, growth hormone secretion and fat deposition. The region showing the strongest selection pressure was located at the position of 86.6–87.5 Mb. The subsequent genome‐wide association analysis of the adult height of three Chinese horse breeds detected the two most significant SNPs in the same region, and these two SNPs overlapped with the gene CHRDL1. As a member of the bone morphogenetic protein (BMP) superfamily, CHRDL1 antagonizes the function of BMP4 and plays an important role in embryonic bone formation and cartilage generation. Our results provide new insights into the X‐linked selection in Chinese Debao pony.
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Tel: +00 44 (0)131 4513762
Fax: +00 44 (0)131 4513327
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