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Hermesch S.,University of New England of Australia | Ludemann C.I.,AbacusBio Pty Ltd | Amer P.R.,AbacusBio Ltd
Journal of Animal Science | Year: 2014

The objective of this paper was to derive economic weights for performance and survival traits of growing pigs including feed conversion ratio (FCR), daily feed intake (DFI), ADG, postweaning survival of the growing pig (SG), and carcass fat depth at the P2 site (CFD). An independent model was developed for each trait to derive economic values directly based on a typical Australian production system. This flexible approach may be used to customize economic values for different production systems and alternative trait combinations in breeding objectives. Discounted genetic expressions were used as a means of taking into account differences in frequency and timing of expression of traits to obtain economic weights. Economic values for SG were derived based on a costsaving and a lost-revenue approach. The correct formulation of the economic value of ADG depends on how feed cost is included in the breeding objective. If FCR is defined as a breeding objective trait, then savings in feed costs through earlier slaughter should not be counted in the economic value of ADG. In contrast, if DFI is included in the breeding objective instead of FCR, then feed-cost savings through earlier slaughter need to be attributed to the economic value for ADG, as a benefit from faster ADG. The paper also demonstrates that economic weightings in indexes for FCR can potentially be overestimated by 70% when it is assumed that DFI or FCR records taken from a limited duration test period reflect the corresponding trait over the full lifetime of the growing pig destined for slaughter. Postweaning survival of the growing pig was the most important breeding objective trait of growing pigs. The relative importance of each breeding objective trait in a sire-line index based on the genetic SD of each trait was 44.5, 27.0, 17.4, and 11.1% for SG, FCR, ADG, and CFD, respectively. Further studies to better clarify the extent of genetic variation that exists in SG under nucleus-farm and commercial-farm conditions are warranted, given the high economic importance of this survival trait of growing pigs. © 2014 American Society of Animal Science. All rights reserved.


Amer P.R.,AbacusBio Ltd | Hely F.S.,AbacusBio Ltd | Quinton C.D.,AbacusBio Ltd | Cromie A.R.,Irish Cattle Breeding Federation
Animal | Year: 2017

A methodological framework was presented for deriving weightings to be applied in selection indexes to account for the impact genetic change in traits will have on greenhouse gas emissions intensities (EIs). Although the emission component of the breeding goal was defined as the ratio of total emissions relative to a weighted combination of farm outputs, the resulting trait-weighting factors can be applied as linear weightings in a way that augments any existing breeding objective before consideration of EI. Calculus was used to define the parameters and assumptions required to link each trait change to the expected changes in EI for an animal production system. Four key components were identified. The potential impact of the trait on relative numbers of emitting animals per breeding female first has a direct effect on emission output but, second, also has a dilution effect from the extra output associated with the extra animals. Third, each genetic trait can potentially change the amount of emissions generated per animal and, finally, the potential impact of the trait on product output is accounted for. Emission intensity weightings derived from this equation require further modifications to integrate them into an existing breeding objective. These include accounting for different timing and frequency of trait expressions as well as a weighting factor to determine the degree of selection emphasis that is diverted away from improving farm profitability in order to achieve gains in EI. The methodology was demonstrated using a simple application to dairy cattle breeding in Ireland to quantify gains in EI reduction from existing genetic trends in milk production as well as in fertility and survival traits. Most gains were identified as coming through the dilution effect of genetic increases in milk protein per cow, although gains from genetic improvements in survival by reducing emissions from herd replacements were also significant. Emission intensities in the Irish dairy industry were estimated to be reduced by ~5% in the last 10 years because of genetic trends in production, fertility and survival traits, and a further 15% reduction was projected over the next 15 years because of an observed acceleration of genetic trends. © The Animal Consortium 2017


Sadeghi-Sefidmazgi A.,Isfahan University of Technology | Amer P.R.,AbacusBio Ltd
Canadian Journal of Animal Science | Year: 2015

The objectives of this research were (1) to estimate the economic benefits or new marketing opportunities due to a reduction in milk somatic cell count (SCC) for dairy producers through improved management practices and (2) to quantify the production loss associated with SCC under different management systems. A total of 38 530 average lactation SCC records for 10 216 Holstein cows gathered on 25 dairy farms from January 2009 to October 2012 in Isfahan (Iran) were analyzed under 13 types of herd management practices including 40 levels of health, milking and housing conditions. The results show that there are many wellestablished management practices associated with higher-quality payment for SCC that have not yet been applied in Isfahan dairy farms. The lowest and highest economic premium opportunity (US$) from SCC were estimated to be for production systems applying washable towels for teat cleaning (5.69) and production systems with no teat disinfection (31.07) per cow per lactation. Results indicate that any increase of one unit in average lactation somatic cell score is expected to cause a significant reduction in average lactation 305-d milk yield from 36.0 to 173.4 kg, depending on the level of management practices employed. In general, farmers with higher milk yield and well-managed practices for mastitis control would lose more milk when an increase occurs in SCC. © 2015, Agricultural Institute of Canada. All rights reserved.


Sadeghi-Sefidmazgi A.,University of Tehran | Moradi-Shahrbabak M.,University of Tehran | Nejati-Javaremi A.,University of Tehran | Miraei-Ashtiani S.R.,University of Tehran | Amer P.R.,Abacus Bio Ltd
Animal | Year: 2011

The objective of this study was to develop a method for calculating economic values of clinical mastitis (CM) and somatic cell score (SCS) for inclusion in a dairy cattle breeding goal in the context of a country where farm production and economic data are scarce. In order to calculate the costs and derive economic values for SCS, a new model, milk collection method, has been developed and was compared with the Meijering model with individual and average SCS distributions. For the population, estimated economic values using the milk collection method were 1.3 and 2.4 times higher than those of Meijering method with average and individual SCS, respectively. The milk collection method needs no assumptions about normality of the distribution of SCS and because of a lack of normality in Iranian data for SCS, the Meijering method resulted in economic values that were biased downwards. Failing to account for the fact that milk price penalties for SCS are applied at milk collection rather than individual cow level resulted in a further large downward bias in the economic value of SCS. When the distribution of data is unknown or difficult to approximate or when a transformation to normality is not straightforward, the milk collection method would be preferable. Inclusion of SCS and CM in the breeding goal for Iranian dairy cattle is justified based on these results. The model to calculate mastitis costs proposed here could be used to estimate economic values for CM in other developing countries where farm production and economic data are generally poor. Copyright © 2010 The Animal Consortium.


Sadeghi-Sefidmazgi A.,University of Tehran | Sadeghi-Sefidmazgi A.,Isfahan University of Technology | Moradi-Shahrbabak M.,University of Tehran | Nejati-Javaremi A.,University of Tehran | And 2 more authors.
Journal of Dairy Science | Year: 2012

Trait-by-trait and multiple trait bioeconomic modeling were used to derive farm-specific economic weights (EW) for a wide range of traits under different production and economic circumstances to define breeding objectives for Holstein dairy cattle in Iran. Production parameters and economic data were gathered on 10 dairy farms from March 2008 to February 2010. The EW (economic values multiplied by gene expressions, in US dollars per unit of trait per calf born from sires of self-replacing females in planning horizon of 20 yr) were estimated to be $0.15 per kilogram of milk yield; $1.36 per kilogram of fat yield; -$1.02 per kilogram of protein yield; $4.59 per month of longevity; -$1.22 per kilogram of mature cow weight; -$105.67 for combined somatic cell score and clinical mastitis; -$1.35 and -$0.28 for percentage direct and maternal calving difficulties, respectively; -$3.98 for percentage direct stillbirth; -$0.76 per day of age at first calving; -$0.72 per calving interval day; and $0.91 for percentage 56-d nonreturn rate on averages across investigated farms. The coefficient of variation of economic weights across the 10 farms was lowest for direct calving difficulty and highest for calving interval. The proposed Iranian selection index was compared with selection indices of major countries exporting semen to Iran. Average relative emphasis for production, durability, and health and reproduction, across all exporter countries, was 41, 37.5, and 21.5%, respectively, whereas the respective values were 50, 14, and 36% for the Iranian index. Significant differences in selection indices may potentially decrease the utility of importation of semen as a means of achieving sustainable genetic progress in Iran. Results obtained in this study provide important information about economic values of traits that can be used to improve the Iranian national progeny testing program as well as importation rules for semen to Iran. © 2012 American Dairy Science Association.


More robust cattle have the potential to increase farm profitability, improve animal welfare, reduce the contribution of ruminant livestock to greenhouse gas emissions and decrease the risk of food shortages in the face of increased variability in the farm environment. Breeding is a powerful tool for changing the robustness of cattle; however, insufficient recording of breeding goal traits and selection of animals at younger ages tend to favour genetic change in productivity traits relative to robustness traits. This paper has extended a previously proposed theory of artificial evolution to demonstrate, using deterministic simulation, how choice of breeding scheme design can be used as a tool to manipulate the direction of genetic progress, whereas the breeding goal remains focussed on the factors motivating individual farm decision makers. Particular focus was placed on the transition from progeny testing or mass selection to genomic selection breeding strategies. Transition to genomic selection from a breeding strategy where candidates are selected before records from progeny being available was shown to be highly likely to favour genetic progress in robustness traits relative to productivity traits. This was shown even with modest numbers of animals available for training and when heritability for robustness traits was only slightly lower than that for productivity traits. When transitioning from progeny testing to a genomic selection strategy without progeny testing, it was shown that there is a significant risk that robustness traits could become less influential in selection relative to productivity traits. Augmentations of training populations using genotyped cows and support for industry-wide improvements in phenotypic recording of robustness traits were put forward as investment opportunities for stakeholders wishing to facilitate the application of science on robust cattle into improved genetic selection schemes. © 2011 The Animal Consortium.


Nielsen H.M.,432 As | Olesen I.,432 As | Navrud S.,Norwegian University of Life Sciences | Kolstad K.,432 As | Amer P.,AbacusBio Ltd
Journal of Agricultural and Environmental Ethics | Year: 2011

The objective of this paper is to outline challenges associated with the inclusion of welfare issues in breeding goals for farm animals and to review the currently available methodologies and discuss their potential advantages and limitations to address these challenges. The methodology for weighing production traits with respect to cost efficiency and market prices are well developed and implemented in animal breeding goals. However, these methods are inadequate in terms of assessing proper values of traits with social and ethical values such as animal welfare, because such values are unlikely to be readily available from the product prices and costs in the market. Defining breeding goals that take animal welfare and ethical concerns into account, therefore, requires new approaches. In this paper we suggest a framework and an approach for defining breeding goals, including animal welfare. The definition of breeding goals including values related to animal welfare requires a multidisciplinary approach with a combination of different methods such as profit equations, stated preference techniques, and selection index theory. In addition, a participatory approach involving different stakeholders such as breeding organizations, food authorities, farmers, and animal welfare organizations should be applied. We conclude that even though these methods provide the necessary tools for considering welfare issues in the breeding goal, the practical application of these methods is yet to be achieved. © 2010 Springer Science+Business Media B.V.


Smith K.F.,Australian Department of Primary Industries and Fisheries | Smith K.F.,AbacusBio Pty Ltd | Fennessy P.F.,AbacusBio Ltd
Crop and Pasture Science | Year: 2011

Despite the large number of active programs breeding improved forage plants, relatively little is known about the weightings that breeders consciously or subconsciously give to specific traits when selecting individual plants or that agronomists and producers use when assessing the relative merits of contrasting cultivars. This is in contrast to most modern animal breeding programs where the relative merits of novel genetics may be assessed against an index-based breeding objective. These technologies have not been widely used in crop or forage plant breeding but their use in forest tree breeding is relatively common. We have assessed the usefulness of discrete choice experiment techniques in the development of weightings for specific traits in forage plant improvement based on the views of an expert panel (plant breeders and non-breeders agronomists, nutritionists, senior managers in breeding companies and consultants) asked to consider the requirements in four species (white clover, lucerne, perennial ryegrass and tall fescue). The results indicate that criteria related to abiotic stress tolerance, adaptation or the costs of pasture (root growth, drought tolerance, persistence, resistance to invertebrate pests, tolerance of hostile soil conditions) were deemed to be particularly important for white clover, while the highest-rated criteria for lucerne were not dissimilar, being tolerance of hostile soil conditions, persistence and tolerance of transient water-logging. For perennial ryegrass, three of the five highest-weighted criteria (drought tolerance, root growth, rate of recovery of pasture after water) are related to yield in environments where too much or too little water is a problem, highlighting the importance that the experts placed on the ability of the plant to withstand this important abiotic stress. For tall fescue, the highest-rated criteria were seedling vigour, drought tolerance, and persistence. Overall the preference weightings tended to reflect the perceived limitations of the various species, such as the priority of seedling vigour in tall fescue. This focus on the importance of abiotic stress is especially interesting as previous attempts to identify priorities have focused on the forage quality traits rather than analysing their importance relative to traits related to herbage yield or stress tolerance. This study highlights the importance of further work to help determine the focus of breeding objectives and selection criteria for different pasture species across production systems. © 2011 CSIRO.


Yousefi A.R.,University of Tehran | Kohram H.,University of Tehran | Zare Shahneh A.,University of Tehran | Nik-khah A.,University of Tehran | Campbell A.W.,AbacusBio Ltd
Meat Science | Year: 2012

The aim of this study was to compare the meat quality of a traditional fat-tailed breed, Chall, to a tailed Iranian sheep breed, Zel. Lambs were grazed on pasture until weaning, and then were finished until slaughter at 10-12. months. Meat quality traits were measured on the longissimus dorsi (LD) muscle. Zel lambs accumulated more intramuscular fat (IMF) (p < 0.01) and had lower shear force and drip loss than Chall lambs (p < 0.05). The meat color of Zel lambs was higher for both a* (p < 0.001) and b* (p < 0.01) compared to Chall lambs. Meat from Zel lambs was more tender (p < 0.01) and more juicy (p < 0.05) than Chall lambs. The PUFA:SFA fatty acid ratio (P:S) was higher (p < 0.05) and the n-6:n-3 PUFA ratio was lower in Chall compared to Zel lambs (p < 0.05). Overall, these results show that the eating quality of Zel lambs was better, but that this was at the cost of less favorable fatty acid profiles and poorer meat color. © 2012 Elsevier Ltd.


Amer P.R.,AbacusBio Ltd | Banos G.,Aristotle University of Thessaloniki
Journal of Dairy Science | Year: 2010

The aim of this study was to evaluate and quantify the importance of avoiding overlap between training and testing subsets of data when evaluating the effectiveness of predictions of genetic merit based on genetic markers. Genomic selection holds great potential for increasing the accuracy of selection in young bulls and is likely to lead quickly to more widespread use of these young bulls with a shorter generation interval and faster genetic improvement. Practical implementations of genomic selection in dairy cattle commonly involve results of national genetic evaluations being used as the dependent variable to evaluate the predictive ability of genetic markers. Selection index theory was used to demonstrate how ignoring correlations among errors of prediction between animals in training and testing sets could result in overestimates of accuracy of genomic predictions. Correlations among errors of prediction occur when estimates of genetic merit of training animals used in prediction are taken from the same genetic evaluation as estimates for validation of animals. Selection index theory was used to show a substantial degree of error correlation when animals used for testing genomic predictions are progeny of training animals, when heritability is low, and when the number of recorded progeny for both training and testing animals is low. Even when training involves a dependent variable that is not influenced by the progeny records of testing animals (i.e., historic proofs), error correlations can still result from records of relatives of training animals contributing to both the historic proofs and the predictions of genetic merit of testing animals. A simple simulation was used to show how an error correlation could result in spurious confirmation of predictive ability that was overestimated in the training population because of ascertainment bias. Development of a method of testing genomic selection predictions that allows unbiased testing when training and testing variables are estimated breeding values from the same genetic evaluation would simplify training and testing of genomic predictions. In the meantime, a 4-step approach for separating records used for training from those used for testing after correction of fixed effects is suggested when use of progeny averages of adjusted records (e.g., daughter yield deviations) would result in inefficient use of the information available in the data. © 2010 American Dairy Science Association.

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