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One joint breeding program (BP) for different dairy cattle environments can be advantageous for genetic gain depending on the genetic correlation between environments (r g ). The break-even correlation (r b ) refers to the specific r g where genetic gain with 1 joint BP is equal to the genetic gain of 2 environment-specific BP. One joint BP has the highest genetic gain if r g is higher than r b , whereas 2 environment-specific BP have higher genetic gain if r g is lower than r b . Genetic gain in this context is evaluated from a breeding company's perspective that aims to improve genetic gain in both environments. With the implementation of genomic selection, 2 types of collaboration can be identified: exchanging breeding animals and exchanging genomic information. The aim of this study was to study genetic gain in multiple environments with different breeding strategies with genomic selection. The specific aims were (1) to find r b when applying genomic selection; (2) to assess how much genetic gain is lost when applying a suboptimal breeding strategy; (3) to study the effect of the reliability of direct genomic values, number of genotyped animals, and environments of different size on r b and genetic gain; and (4) to find r b from each environment's point of view. Three breeding strategies were simulated: 1 joint BP for both environments, 2 environment-specific BP with selection of bulls across environments, and 2 environment-specific BP with selection of bulls within environments. The r b was 0.65 and not different from r b with progeny-testing breeding programs when compared at the same selection intensity. The maximum loss in genetic gain in a suboptimal breeding strategy was 24%. A higher direct genomic value reliability and an increased number of genotyped selection candidates increased genetic gain, and the effect on r b was not large. A different size in 2 envi-ronments decreased r b by, at most, 0.10 points. From a large environment's point of view, 1 joint BP was the optimal breeding strategy in most scenarios. From a small environment's point of view, 1 joint BP was only the optimal breeding strategy at high r g . When the exchange of breeding animals between environments was restricted, genetic gain could still increase in each environment. This was due to the exchange of genomic information between environments, even when r g between environments were as low as 0.4. Thus, genomic selection improves the possibility of applying environment-specific BP.

The aim of this study was to characterize preferences of farmers for breeding goal traits with Danish Red (DR) or Danish Jersey (DJ) cows. A breed-specific survey was established to characterize farmers' preferences for improvements in 10 traits, by means of pairwise rankings using the online software 1000Minds. These pairwise rankings were based on equal economic worth of trait improvements. The DR survey was filled in by 87 farmers and the DJ survey by 76 farmers. Both DR and DJ farmers gave the highest preference to improvements in mastitis, and the lowest to calving difficulty. By means of a cluster analysis, three distinct clusters of farmers were identified per breed. Comparisons of herd characteristics between clusters suggest that farmers choose to improve traits that are problematic in their herds. This study shows that heterogeneity exists in farmers' preferences for trait improvements and that herd characteristics influence these preferences in DR and DJ.ARTICLE HISTORY

In Denmark, Finland, and Sweden, the Nordic Total Merit index is used as the breeding selection tool for both organic and conventional dairy farmers based on common economic models for conventional dairy farming. Organic farming is based on the principles of organic agriculture (POA) defined by the International Federation of Organic Agriculture Movements. These principles are not set up with an economic point of view, and therefore it may be questionable to use a breeding goal (BG) for organic dairy production based on economic models. In addition to economics and the principles of organic agriculture, it is important to look at farmers' preferences for improving BG traits when setting up a BG for organic farming. The aim of this research was to set up, simulate, and compare long-term effects of different BG for organic and conventional dairy production systems based on economic models, farmers' preferences, and POA, with particular emphasis on disease resistance or on roughage consumption and feed efficiency. The BG based on economic models and on farmers' preferences were taken from previous studies. The other BG were desired gains indices, set up by means of a questionnaire about relatedness between the POA and BG traits. Each BG was simulated in the stochastic simulation program ADAM. The BG based on POA, with particular emphasis on disease resistance or on roughage consumption and feed efficiency, caused favorable genetic gain in all 12 traits included in this study compared with 6 traits for the other BG. The BG based on POA, with particular emphasis on disease resistance or on roughage consumption and feed efficiency, were very different from BG for organic and conventional production based on economic models and farmers' preferences in both simulated genetic change and correlations between BG. The BG that was created based on the principles of organic agriculture could be used as a specific index for organic dairy farming in Denmark, but this index was economically not very sustainable. Hence, an intermediate breeding goal could be developed by breeding companies to address both economics and the principles of organic agriculture.

Organic dairy production differs from conventional dairy production in many aspects. However, breeding programs for the 2 production systems are the same in most countries. Breeding goals (BG) might be different for the 2 production systems and genotype × environment interaction may exist between organic and conventional dairy production, both of which have an effect on genetic gain in different breeding strategies. Other aspects also need to be considered, such as the application of multiple ovulation and embryo transfer (MOET), which is not allowed in organic dairy production. The general aim of this research was to assess different environment-specific breeding strategies for organic dairy production. The specific aim was to study differences in BG weights and include the effect of genotype × environment interaction, MOET, and the selection of breeding bulls from the conventional environment. Different scenarios were simulated. In the current scenario, the present-day situation for dairy production in Denmark was emulated as much as possible. The BG was based on a conventional dairy production system, MOET was applied in both environments, and conventional bulls could be selected as breeding bulls in the organic environment. Four alternative scenarios were simulated, all with a specific organic BG in the organic breeding program but differences in the usage of MOET and the selection of conventional bulls as breeding bulls. Implementation of a specific BG in organic dairy production slightly increased genetic gain in the aggregate genotype compared with the breeding program that is currently implemented in organic dairy production. Not using embryo transfer or only selecting breeding bulls from the organic environment decreased genetic gain in the aggregate genotype by as much as 24%. However, the use of embryo transfer is debatable because this is not allowed according to current regulations for organic dairy production. Assessing genetic gain on trait levels showed that a significant increase for functional traits was possible compared with the current breeding program in the organic environment without a decrease in genetic gain in the aggregate genotype. This difference on trait level was even more present when selection of conventional bulls as breeding bulls in the organic environment was not possible. This finding is very relevant when breeding for the desired cow in organic dairy production.