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

On-Barn Forecasting Beef Cattle Production Based on Automated Non-Contact Body Measurement System

The main task of selective breeding is to determine the early productivity of offspring. The sooner the economic value of an animal is determined, the more profitable the result will be, due to the proper estimation of high and low productive calves and distribution of the resources among them, accordingly. To predict productivity, we offer to use a systematic assessment of animals by using the main genetic parameters (correlation coefficients, heritability, and regression) based on data such as the measurement of morphological characteristics of animals, obtained using the automated non-contact body measurement system based on RGB-D image capture. The usefulness of the image capture system lies in significant time reduction that is spent on data collection and improvement in data collection accuracy due to the absence of subjective measurement errors. We used the RGB-D image capture system to measure the live weight of mother cows, as well as the live weight and body size of their calves (height at the withers, height in the sacrum, oblique length of the trunk, chest depth, chest girth, pastern girth). Cows and cattle of black-and-white and Holstein breeds (n = 561) were selected as the object of the study. Correlation analysis revealed the main indices for the forecast of meat productivity-live weight and measurements of animals at birth. Calculation of the selection effect is necessary for planning breeding work, since it can determine the value of economically beneficial traits in subsequent generations, which is very important for increasing the profitability of livestock production. This approach can be used in livestock farms for predicting the meat productivity of black-and-white cattle.

Defining smallholders' breeding objectives for common Tigray highland sheep in Northern Ethiopia

A sound breeding objective is a basis for genetic improvement in the overall economic merit of farm animals. This study aimed to define smallholders' sheep breeding objectives using a conjoint-based choice experiment and bio-economic model. Multinomial logistic regression analysis showed differences (p < 0.001) among the derived weights allocated by farmers to body size, twining rate, mothering ability, libido, tail type, colour and lambing interval which formed the high priority traits. The likelihood values of farmer's top three preferred traits for ram were body size (0.659 ± 0.009), tail type (0.325 ± 0.016) and libido (0.247 ± 0.016) while body size (0.459 ± 0.010), twining rate (0.313 ± 0.010) and mothering ability (0.261 ± 0.010) were more preferred traits for selection of breeding ewes. Conjoint-based choice experiment and bio-economic model indicated that live body weight at 6 months of age, twining rate (litter size) and mothering ability (preweaning lamb survival) were the most economically important traits of the breeding ewes. A genetic improvement by one genetic standard deviation (σ_a ) in these traits resulted in a profit of Ethiopian Birr 36.03-60.47/ewe/year. A fair correlation (r = 0.63) was observed between farmers' traits preference (conjoint-based choice card experiment) and the estimated economic value of traits indicating a good relationship between farmers' preferences for traits and economic values of the traits. This would indicate that weighting traits in selection indexes with farmers' trait selection using a conjoint-based choice experiment would direct genetic improvement towards desired profitability. Moreover, the fair correspondence between the two methods suggests that bio-economic modelling, if designed properly considering farmers' concerns, could be used to reflect farmers' breeding objectives. Therefore, for reasonable genetic progress and sheep flock profitability, more attention should be given to litter size, preweaning lamb survival and body weight at 6 months of age as they are preferred by farmers and their economic weights. Further, research on the modalities for complementary use of the two methods to define breeding objectives under smallholder conditions is warranted.

Application of a Bio-Economic Model to Demonstrate the Importance of Health Traits in Herd Management of Lithuanian Dairy Breeds

Simple Summary

The aims of dairy cattle breeding are more often associated with direct health evidence in relation to the net financial gain and the weighting factors are usually economic values that are retrieved from a model of a dairy herd production system. In our study we used a stochastic bio-economic model SimHerd, which allows us to derive economic values for production, fertility, calving, the survival of cows and calves and assign the importance of health traits to the economic values. Special emphasis was placed on the economics values of health traits and their importance for Lithuanian dairy cattle.

Abstract

Assessing the economic importance of traits is crucial for delivering appropriate breeding goals in dairy cattle breeding. The aim of the present study was to calculate economic values (EV) and assign the importance of health traits for three dairy cattle breeds: Lithuanian Black-and-White open population (LBW), Lithuanian Red open population (LR) and Lithuanian Red old genotype (LROG). The EV estimation was carried out using a stochastic bio-economic model SimHerd, which allows the simulation of the expected monetary gain of dairy herds. The simulation model was calibrated for LBW, LR and LROG breeds, taking into account breed-specific phenotypic and economic data. For each trait, two scenarios were simulated with a respective trait at different phenotypic levels. To obtain the EVs, the scenarios were compared with each other in terms of their economic outcomes. In order to avoid the double counting of the effects, the output results were corrected using a multiple regression analysis with mediator variables. The EVs were derived for the traits related to production ECM (energy-corrected milk), fertility, calving traits, calf survival, cow survival and direct health. To demonstrate the importance of health traits in herd management, we provided reliable EVs estimates for functional traits related to herd health. The highest EV for direct health traits, caused by an increase in of 1 percentage point, were those found for mastitis (EUR 1.73 to EUR 1.82 per cow-year) and lameness (EUR 1.07 to EUR 1.27 per cow-year). The total costs per case of ketosis, milk fever and metritis ranged from EUR 1.01 to EUR 1.30, EUR 1.14 to EUR 1.26 and EUR 0.95 to EUR 1.0, respectively. The highest economic values of dystocia were estimated for LROG (EUR −1.32), slightly lower for LBW (EUR −1.31) and LR (EUR −1.23). The results of this study show the importance of health traits to the economic features of cattle herd selection of new breeding goal and this would improve the herd health. The economic evaluation of the functional traits analyzed in this study indicated the significant economic importance of the functional traits in Lithuanian dairy cattle breeds.

Derivation of economic values for German dairy breeds by means of a bio-economic model-with special emphasis on functional traits

To assess the economic importance of breeding traits, economic values (EV) were derived for 3 German dairy cattle breeds: German Holstein (HOL), Angler (ANG), and Red and White Dual-Purpose (RDN). For that purpose, the stochastic bio-economic model SimHerd (SimHerd A/S, Viborg, Denmark) was used, which simulates the expected monetary gain in dairy herds. The EV was calculated as the alteration in average net return of the herd responding to a marginal change in the trait of interest. When deriving EV using SimHerd, economic consequences resulting from changes in the age structure of a dairy herd (i.e., structural herd effects) are considered. However, this requires the simulation of relationships between traits in the bio-economic model. To avoid double counting, the EV of a trait was corrected for effects from alterations in correlated traits using multiple regression analysis. The EV were derived for 23 traits in terms of production, conformation and workability, dairy health, calf survival, and reproduction performance. Furthermore, the relative economic importance of the breeding traits was calculated. Relative emphasis on production was between 39.9 and 44.4% in the breeds studied. Total costs per case of ketosis and metritis ranged from €167 to €196 and €173 to €182, respectively. Highest marginal EV of direct health traits were found for mastitis (€257 to €271 per case) and lameness (€270 to €310 per case). Consequently, relative emphasis on direct health traits was between 15.7 and 17.9%. The EV of reproduction performance showed largest differences among the cattle breeds. Overall relative emphasis on reproduction was 10.5% in HOL, 10.8% in ANG, and 6.5% in RDN. The relative economic importance of cow mortality ranged from 15.5 to 16.0% across the breeds. Collectively, the study showed the high economic importance of functional traits in the cattle breeds studied.

Identification of breeding objectives for Begait goat in western Tigray, North Ethiopia

A sound breeding objective is the basis for genetic improvement in overall economic merit of farm animals. Begait goat is one of the identified breeds in Ethiopia, which is a multipurpose breed as it serves as source of cash income and source of food (meat and milk). Despite its importance, no formal breeding objectives exist for Begait goat. The objective of the present study was to identify breeding objectives for the breed through two approaches: using own-flock ranking experiment and developing deterministic bio-economic models as a preliminary step towards designing sustainable breeding programs for the breed. In the own-flock ranking experiment, a total of 45 households were visited at their homesteads and were asked to select, with reasons, the first best, second best, third best, and the most inferior does from their own flock. Age, previous reproduction, and production information of the identified animals were inquired; live body weight and some linear body measurements were taken. The bio-economic model included performance traits (weights, daily weight gain, kidding interval, litter size, milk yield, kid mortality, pregnancy, and replacement rates) and economic (revenue and costs) parameters. It was observed that there was close agreement between the farmers' ranking and bio-economic model results. In general, the results of the present study indicated that Begait goat owners could improve performance of their goats and profitability of their farms by selecting for 6-month weight, litter size, pre-weaning kid survival rate, and milk yield.

Derivation of economic values for production traits in aquaculture species

BACKGROUND

In breeding programs for aquaculture species, breeding goal traits are often weighted based on the desired gains but economic gain would be higher if economic values were used instead. The objectives of this study were: (1) to develop a bio-economic model to derive economic values for aquaculture species, (2) to apply the model to determine the economic importance and economic values of traits in a case-study on gilthead seabream, and (3) to validate the model by comparison with a profit equation for a simplified production system.

METHODS

A bio-economic model was developed to simulate a grow-out farm for gilthead seabream, and then used to simulate gross margin at the current levels of the traits and after one genetic standard deviation change in each trait with the other traits remaining unchanged. Economic values were derived for the traits included in the breeding goal: thermal growth coefficient (TGC), thermal feed intake coefficient (TFC), mortality rate (M), and standard deviation of harvest weight ([Formula: see text]). For a simplified production system, improvement in TGC was assumed to affect harvest weight instead of growing period. Using the bio-economic model and a profit equation, economic values were derived for harvest weight, cumulative feed intake at harvest, and overall survival.

RESULTS

Changes in gross margin showed that the order of economic importance of the traits was: TGC, TFC, M, and [Formula: see text]. Economic values in € (kg production)^-1 (trait unit)^-1 were: 0.40 for TGC, -0.45 for TFC, -7.7 for M, and -0.0011 to -0.0010 for [Formula: see text]. For the simplified production system, similar economic values were obtained with the bio-economic model and the profit equation. The advantage of the profit equation is its simplicity, while that of the bio-economic model is that it can be applied to any aquaculture species, because it can include any limiting factor and/or environmental condition that affects production.

CONCLUSIONS

We confirmed the validity of the bio-economic model. TGC is the most important trait to improve, followed by TFC and M, and the effect of [Formula: see text] on gross margin is small.

Economic values for health and feed efficiency traits of dual-purpose cattle in marginal areas

Economic values of clinical mastitis, claw disease, and feed efficiency traits along with 16 additional production and functional traits were estimated for the dairy population of the Slovak Pinzgau breed using a bioeconomic approach. In the cow-calf population (suckler cow population) of the same breed, the economic values of feed efficiency traits along with 15 further production and functional traits were calculated. The marginal economic values of clinical mastitis and claw disease incidence in the dairy system were -€ 70.65 and -€ 26.73 per case per cow and year, respectively. The marginal economic values for residual feed intake were -€ 55.15 and -€ 54.64/kg of dry matter per day for cows and breeding heifers in the dairy system and -€ 20.45, -€ 11.30, and -€ 6.04/kg of dry matter per day for cows, breeding heifers, and fattened animals in the cow-calf system, respectively, all expressed per cow and year. The sums of the relative economic values for the 2 new health traits in the dairy system and for residual feed intake across all cattle categories in both systems were 1.4 and 8%, respectively. Within the dairy production system, the highest relative economic values were for milk yield (20%), daily gain of calves (20%), productive lifetime (10%), and cow conception rate (8%). In the cow-calf system, the most important traits were weight gain of calves from 120 to 210 d and from birth to 120 d (19 and 14%, respectively), productive lifetime (17%), and cow conception rate (13%). Based on the calculation of economic values for traits in the dual-purpose Pinzgau breed, milk production and growth traits remain highly important in the breeding goal, but their relative importance should be adapted to new production and economic conditions. The economic importance of functional traits (especially of cow productive lifetime and fertility) was sufficiently high to make the inclusion of these traits into the breeding goal necessary. An increased interest of consumers in animal welfare and quality of dairy farm products should probably lead to the incorporation of health traits (clinical mastitis incidence and somatic cells score) into the breeding goal. However, keeping carcass traits in the breeding goal of the Slovak Pinzgau breed does not seem to be relevant to the long-term market situation.

Using the choice experiment method in the design of breeding goals in dairy sheep

Market failures are the main cause of poor acknowledgement of the true impact of functional sheep traits on the management and economic performance of farms, which results in their omission from the breeding goal or the estimation of non-representative economic weights in the breeding goal. Consequently, stated-preference non-market valuation techniques, which recently emerged to mitigate these problems, are necessary to estimate economic weights for functional traits. The purpose of this paper is to present an example of the use of a choice experiment (CE) in the estimation of economic weights for sheep traits for the design of breeding goals. Through a questionnaire survey the preferences of sheep farmers are recorded and their marginal willingness to pay (MWTP) for 10 production and functional traits is estimated. Data are analysed using random parameter logit models. The results reveal unobserved preference heterogeneity for fertility, adaptability to grazing and resistance to disease, thus highlighting that these traits are appreciated differently by farmers, because their needs are diverse. Positive MWTP is found for Greek breeds, high milk production and lambs with low fat deposition, for which there is high demand in Greek markets. On the other hand, MWTP for the cheese-making ability of milk is negative, stemming from the fact that sheep milk prices in Greece are not formulated according to milk composition. In addition, farmers seem to understand differences between udder shapes and attribute different values to various types. This application of the CE method indicates that communication channels among farmers and breeders should be established in order to enhance market performance and to provide orientation to the design of breeding programmes. Non-market valuation can be used complementarily to market valuation techniques, in order to provide accurate estimates for production and functional traits.

Economic values for production and functional traits of Small East African goat using profit functions

Economic values for production traits (milk yield, MY, g; 12-month live weight, yLW, kg; consumable meat percentage, CM, %) and functional traits (mature doe live weight, DoLW, kg; mature buck live weight, LWb, kg; kidding frequency, KF; pre-weaning survival rate, PrSR, %; post-weaning survival rate, PoSR,%; doe survival rate, DoSR, %; and residual feed intake, RFI, kg) were estimated using profit functions for the Small East African goat. The scenario evaluated was a fixed flock size, and the resultant economic values (Kes per doe per year) were 34.46 (MY), 62.35 (yLW), 40.69 (CM), 0.15 (DoLW), 2.84 (LWb), 8.69 (KF), 17.38 (PrSR), 16.60 (PoSR), 16.69 (DoSR) and -3.00 (RFI). Similarly, the economic values decreased by -14.7 % (MY), -2.7 % (yLW), -23.9 % (CM), -6.6 % (DoLW), -98 % (LWb), -8.6 % (KF), -8.2 % (PrSR), -8.9 % (PoSR), -8.1 % (DoSR) and 0 % (RFI) when they were risk rated. The economic values for production and functional traits, except RFI, were positive, which implies that genetic improvement of these traits would have a positive effect on the profitability in the pastoral production systems. The application of an Arrow-Pratt coefficient of absolute risk aversion (λ) at the level of 0.02 resulted in a decrease on the estimated economic values, implying that livestock keepers who were risk averse were willing to accept lower expected returns. The results indicate that there would be improvement in traits of economic importance, and, therefore, easy-to-manage genetic improvement programmes should be established.