A specific breeding goal definition was developed for Creole goats in Guadeloupe. This local breed is used for meat production. To ensure a balanced selection outcome, the breeding objective included two production traits, live weight (BW11) and dressing percentage (DP) at 11 months (the mating or selling age), one reproduction trait, fertility (FER), and two traits to assess animal response to parasite infection: packed cell volume (PCV), a resilience trait, and faecal worm eggs count (FEC), a resistance trait. A deterministic bio-economic model was developed to calculate the economic values based on the description of the profit of a Guadeloupean goat farm. The farm income came from the sale of animals for meat or as reproducers. The main costs were feeding and treatments against gastro-intestinal parasites. The economic values were 7.69€ per kg for BW11, 1.38€ per % for FER, 3.53€ per % for DP and 3 × 10−4€ per % for PCV. The economic value for FEC was derived by comparing the expected profit and average FEC in a normal situation and in an extreme situation where parasites had developed resistance to anthelmintics. This method yielded a maximum weighting for FEC, which was −18.85€ per log(eggs per gram). Alternative scenarios were tested to assess the robustness of the economic values to variations in the economic and environmental context. The economic values of PCV and DP were the most stable. Issues involved in paving the way for selective breeding on resistance or resilience to parasites are discussed.

The objectives of this study were to quantify the errors in economic values (EVs) for traits affected by cost or price thresholds when skewed or kurtotic distributions of varying degree are assumed to be normal and when data with a normal distribution is subject to censoring. EVs were estimated for a continuous trait with dichotomous economic implications because of a price premium or penalty arising from a threshold ranging between −4 and 4 standard deviations from the mean. In order to evaluate the impacts of skewness, positive and negative excess kurtosis, standard skew normal, Pearson and the raised cosine distributions were used, respectively. For the various evaluable levels of skewness and kurtosis, the results showed that EVs can be underestimated or overestimated by more than 100% when price determining thresholds fall within a range from the mean that might be expected in practice. Estimates of EVs were very sensitive to censoring or missing data. In contrast to practical genetic evaluation, economic evaluation is very sensitive to lack of normality and missing data. Although in some special situations, the presence of multiple thresholds may attenuate the combined effect of errors at each threshold point, in practical situations there is a tendency for a few key thresholds to dominate the EV, and there are many situations where errors could be compounded across multiple thresholds. In the development of breeding objectives for non-normal continuous traits influenced by value thresholds, it is necessary to select a transformation that will resolve problems of non-normality or consider alternative methods that are less sensitive to non-normality.

Cattle production faces new challenges regarding sustainability with its three pillars – economic, societal and environmental. The following three main factors will drive dairy cattle selection in the future: (1) During a long period, intensive selection for enhanced productivity has deteriorated most functional traits, some reaching a critical point and needing to be restored. This is especially the case for the Holstein breed and for female fertility, mastitis resistance, longevity and metabolic diseases. (2) Genomic selection offers two new opportunities: as the potential genetic gain can be almost doubled, more traits can be efficiently selected; phenotype recording can be decoupled from selection and limited to several thousand animals. (3) Additional information from other traits can be used, either from existing traditional recording systems at the farm level or from the recent and rapid development of new technologies and precision farming. Milk composition (i.e. mainly fatty acids) should be adapted to better meet human nutritional requirements. Fatty acids can be measured through a new interpretation of the usual medium infrared spectra. Milk composition can also provide additional information about reproduction and health. Modern milk recorders also provide new information, that is, on milking speed or on the shape of milking curves. Electronic devices measuring physiological or activity parameters can predict physiological status like estrus or diseases, and can record behavioral traits. Slaughterhouse data may permit effective selection on carcass traits. Efficient observatories should be set up for early detection of new emerging genetic defects. In the near future, social acceptance of cattle production could depend on its capacity to decrease its ecological footprint. The first solution consists in increasing survival and longevity to reduce replacement needs and the number of nonproductive animals. At the individual level, selection on rumen activity may lead to decreased methane production and concomitantly to improved feed efficiency. A major effort should be dedicated to this new field of research and particularly to rumen flora metagenomics. Low input in cattle production is very important and tomorrow's cow will need to adapt to a less intensive production environment, particularly lower feed quality and limited care. Finally, global climate change will increase pathogen pressure, thus more accurate predictors for disease resistance will be required.

The aim of this study was to show how choice experiments can be used to derive economic weights in breeding objectives. In a choice experiment, respondents are asked to view various alternative descriptions of a good differentiated by their attributes and levels, and are asked to choose their most preferred alternative. Analysis of the data generated can be used to elicit a quantitative description of respondent preference for contrasting attributes and levels. We simulated a partial profile choice experiment with four different attributes (traits) each at three levels. In a partial profile design, the choices are simplified so that only a subset of traits is used for each comparison, making participation in the experimental process less onerous. Three different choice designs were compared. All three designs included four attributes each at three levels where respondents choose between two alternative genotypes. In the first design, respondents choose between two genotypes differing for all four traits simultaneously. In the second and third designs, respondents made choices based on three or two out of the four traits per choice set respectively. The effectiveness of different designs was evaluated based on comparisons between true and simulated preferences for varying numbers of respondents and choice sets per respondent. Choice design and the simulated respondent choice were analysed using a conditional logit model. Regression coefficients from the conditional logit model based on an average of 200 replicated choices across respondents were used to estimate the relative economic weights of traits. A need to account for discounted gene flow principles when formulating the survey questions was emphasised as a critical component of the method. When the relative importance’s of four traits were considered, practical designs involving, e.g., 20 choice sets based on a subset of two traits at each choice, and over 30 respondents provided relatively accurate estimates of relative respondent preferences. The method based on a practical choice experiment design can be used to define economic weights for use in animal breeding selection indexes where traditional approaches such as profit equations and bioeconomic models are not practical. The approach may also be of interest to commercial breeding programs wishing to formulate a quantitative understanding of market preferences for attributes of the genestocks that they sell.