Economic values for traits of meat sheep in medium to high production potential areas of the tropics

The objective of the present review was (i) to survey different approaches for choosing the complex of traits for which economic values (EVs) are calculated, (ii) to call attention to the proper definition of traits and (iii) to discuss the manner and extent to which relationships among traits have been considered in the calculation of EVs. For this purpose, papers dealing with the estimation of EVs of traits in livestock were reviewed. The most important reasons for incompatibility of EVs for similar traits estimated in different countries and by different authors were found to be inconsistencies in trait definitions and in assumptions being made about relationships among traits. An important problem identified was how to choose the most appropriate criterion to characterise production or functional ability for a particular class of animals. Accordingly, the review covered the following three topics: (i) which trait(s) would best characterise the growth ability of an animal; (ii) how to define traits expressed repeatedly in subsequent reproductive cycles of breeding females and (iii) how to deal with traits that differ in average value between sexes or among animal groups. Various approaches that have been used to solve these problems were discussed. Furthermore, the manner in which diverse authors chose one or more traits from a group of alternatives for describing a specific biological potential were reviewed and commented on. The consequences of including or excluding relationships among economically important traits when estimating the EV for a specific trait were also examined. An important conclusion of the review is that, for a better comparability and interpretability of estimated EVs in the literature, it is desirable that clear and unique definitions of the traits, complete information on assumptions used in analytical models and details on interrelationships between traits are documented. Furthermore, the method and the model used for the genetic evaluation of specific traits in a certain breeding organisation are important for the exact definition of traits, for which the economic values will be calculated, and for the inclusion or exclusion of relationships among traits in the calculation of the EVs in livestock breeding. Keywords: livestock, economic values, definition of traits, relationships among traits ImplicationsA literature review was conducted on different ways of defining traits and considering relationships among them in the calculation of economic values (EVs) in livestock breeding. Diversity among trait definitions makes it difficult to compare EVs from different investigations and individual authors. It was shown that, for the EV of a trait to be correctly interpreted, it is necessary to know exactly how the trait was defined, how its relationships with other traits were accounted for and what assumptions were made in the model for the calculation of EVs. IntroductionHazel (1943) proposed the breeding objective or aggregate genotype of an animal to be defined as 'the sum of its sever...

Section: Definition Of Traits Expressed In Different Sexes or Animal mentioning

confidence: 99%

Strategies for defining traits when calculating economic values for livestock breeding: a review

Wolfová

Wolf

2013

“…The sensitivity of economic values of traits to circumstances also gives information on the likely direction of future genetic improvement and production system (Smith, 1988;Kosgey et al, 2003). Table 6 shows the sensitivities of economic values for sow productivity traits to price changes.…”

Section: Sensitivity Analysesmentioning

confidence: 99%

“…This knowledge should therefore compel the recalculation of the economic value for each economically relevant trait, regardless of the ease with which that trait can be improved. Kosgey et al (2003) ointed out that the effort it takes to change a trait can vary considerably between traits, that is, the trait can be of great economic importance but cannot be changed easily. Where profitability is a primary concern, decisions about which traits to target for genetic improvement should be based on the extent to which each trait affects profitability.…”

Section: Sensitivity Analysesmentioning

confidence: 99%

Integrating economic parameters into genetic selection for Large White pigs

Dube

Mulugeta

Dzama

2013

The objective of the study was to integrate economic parameters into genetic selection for sow productivity, growth performance and carcass characteristics in South African Large White pigs. Simulation models for sow productivity and terminal production systems were performed based on a hypothetical 100-sow herd, to derive economic values for the economically relevant traits. The traits included in the study were number born alive (NBA), 21-day litter size (D21LS), 21-day litter weight (D21LWT), average daily gain (ADG), feed conversion ratio (FCR), age at slaughter (AGES), dressing percentage (DRESS), lean content (LEAN) and backfat thickness (BFAT). Growth of a pig was described by the Gompertz growth function, while feed intake was derived from the nutrient requirements of pigs at the respective ages. Partial budgeting and partial differentiation of the profit function were used to derive economic values, which were defined as the change in profit per unit genetic change in a given trait. The respective economic values (ZAR) were: 61. 26, 38.02, 210.15, 33.34, 221.81, 268.18, 5.78, 4.69 and 21.48. These economic values indicated the direction and emphases of selection, and were sensitive to changes in feed prices and marketing prices for carcasses and maiden gilts. Economic values for NBA, D21LS, DRESS and LEAN decreased with increasing feed prices, suggesting a point where genetic improvement would be a loss, if feed prices continued to increase. The economic values for DRESS and LEAN increased as the marketing prices for carcasses increased, while the economic value for BFAT was not sensitive to changes in all prices. Reductions in economic values can be counterbalanced by simultaneous increases in marketing prices of carcasses and maiden gilts. Economic values facilitate genetic improvement by translating it to proportionate profitability. Breeders should, however, continually recalculate economic values to place the most appropriate emphases on the respective traits during genetic selection.

“…These analyses focus mainly on the impact of changes in economic input parameters (product prices and costs) and on the impact of output or input restrictions (milk or meat quotas, restricted feed resources). See, for example, Kosgey et al (2003), Haghdoost et al (2008) and Byrne et al (2010) in meat sheep and Wolfová et al (2001) and Vargas et al (2002) in dairy cattle. Fewer sensitivity analyses have investigated the influence of performance levels of traits or of management practices on MEVs or on REVs.…”

Section: Impact Of Production Circumstances On Revsmentioning

confidence: 99%

“…Such economic values can be sensitive to differences in production systems, average trait levels in the population, market prices and feed costs (e.g. Amer et al, 1999;Kosgey et al, 2003;Conington et al, 2004). When economic values for 14 production and functional traits for the most widespread Slovak sheep breeds, Improved Valachian and Tsigai, were calculated taking the most common production circumstances into account, milk yield, conception rate of ewes, litter size and ewe productive lifetime were identified as the economically most important traits ).…”

Section: Introductionmentioning

confidence: 99%

Impact of production strategies and animal performance on economic values of dairy sheep traits

Krupová

Wolfová

Krupa

et al. 2012

The objective of this study was to carry out a sensitivity analysis on the impact of various production strategies and performance levels on the relative economic values (REVs) of traits in dairy sheep. A bio-economic model implemented in the program package ECOWEIGHT was used to simulate the profit function for a semi-extensive production system with the Slovak multi-purpose breed Improved Valachian and to calculate the REV of 14 production and functional traits. The following production strategies were analysed: differing proportions of milk processed to cheese, customary weaning and early weaning of lambs with immediate sale or sale after artificial rearing, seasonal lambing in winter and aseasonal lambing in autumn. Results of the sensitivity analysis are presented in detail for the four economically most important traits: 150 days milk yield, conception rate of ewes, litter size and ewe productive lifetime. Impacts of the differences in the mean value of each of these four traits on REVs of all other traits were also examined. Simulated changes in the production circumstances had a higher impact on the REV for milk yield than on REVs of the other traits investigated. The proportion of milk processed to cheese, weaning management strategy for lambs and level of milk yield were the main factors influencing the REV of milk yield. The REVs for conception rate of ewes were highly sensitive to the current mean level of the trait. The REV of ewe productive lifetime was most sensitive to variation in ewe conception rate, and the REV of litter size was most affected by weaning strategy for lambs. On the basis of the results of sensitivity analyses, it is recommended that economic values of traits for the overall breeding objective for dairy sheep be calculated as the weighted average of the economic values obtained for the most common production strategies of Slovak dairy sheep farms and that economic values be adjusted after substantial changes in performance levels of the traits.