In most breeding programs of plant and animal species, genetic data (such as data from field progeny tests) are used to rank parents and help choose candidates for selection. In general, all selection processes first rank the candidates using some function of the observed data and then choose as the selected portion those candidates with the largest (or smallest) values of that function. To make maximum progress from selection, it is necessary to use a function of the data that results in the candidates being ranked as closely as possible to the true (but always unknown) ranking. Very often the observed data on various candidates are messy and unbalanced and this complicates the process of developing precise and accurate rankings. For example, for any given candidate, there may be data on that candidate and its siblings growing in several field tests of different ages. Also, there may be performance data on siblings, ancestors or other relatives from greenhouse, laboratory or other field tests. In addition, data on different candidates may differ drastically in terms of quality and quantity available and may come from varied relatives. Genetic improvement programs which make most effective use of these varied, messy, unbalanced and ancestral data will maximize progress from all stages of selection. In this regard, there are two analytical techniques, best linear prediction (BLP) and best linear unbiased prediction (BLUP), which are quite well-suited to predicting genetic values from a wide variety of sources, ages, qualities and quantities of data.

Canadian historian Margaret Derry examines the evolution of modern animal breeding from the invention of improved breeding methods in 18th-century England to the application of molecular genetics in the 1980s and 1990s.

This volume presents selected issues in the complex and diverse science of animal husbandry. The use of computer programs provides an opportunity to improve breeding and optimize farm management. At the same time, the use of traditional breeding methods is also of decisive importance. Knowledge of animal welfare and animal wellness is of great help in controlling animal health issues and in economic production. In the biological processes of reproduction of dairy cows, the events of the 100 days after calving are of fundamental importance. Production systems influence the process of product production, in which the relationship between animal products and human health goes far beyond animal husbandry, and to which the issue of greenhouse gases is also connected. The quality of manufactured meat products is influenced by both on-farm and off-farm factors, but good meat cannot be produced from low-quality animals, even with excellent slaughterhouse work. Background knowledge of animal health ‒ including the microbiome in the digestive tract, which makes use of the feed ‒ makes this activity more effective, which is of particular importance in the case of broiler chickens. Knowing the behavioural characteristics of animals (rams) enables better management. Many horse breeds are capable of artificial gaits as a result of breeding and selection processes. Comparative knowledge of the movements of these horse breeds also helps to understand their differences. The quality of life of animals and the quality of manufactured products are also affected by polycyclic aromatic hydrocarbons from the environment, which, being stored and enriched in fat-containing tissues, can also have adverse effects on the human consumer. Each topic presented not only offers specialist knowledge but makes interesting reading in its own right.

Low-and-Middle-Income Countries (LMICs) are home to diverse populations of livestock species adapted to various agro-ecological zones, production systems, and harsh environmental conditions. However, the livestock in LMICs have not been systematically improved and current low levels of productivity do not meet the demand for livestock products by a growing population. Recent advances in next-generation sequencing and genotyping technologies have enabled the application of genomic selection in various livestock species in some western countries with great success. Despite the low adoption of genomic breeding in LMICs livestock industry, various studies and programs were initiated and some are still ongoing. Furthermore, community-based breeding programs (CBBP) have been initiated in many LMICs with great benefits for smallholder livestock farmers. CBBPs are based on the active participation of farmers from inception through to implementation and consider their needs, views, decisions, breeding objectives, and available infrastructure. In Africa for instance, small ruminants CBBPs have generated substantial genetic gains and socioeconomic benefits for rural poor farmers. However, the current challenges affecting the data recording and genetic evaluation of the CBBPs in LMICS are yet to be fully reported. Furthermore, the CBBPs are yet to integrate genomic selection in their breeding strategies. For sustainable livestock breeding in LMICs, there is a need to assess the current status of livestock genomics and community-based breeding strategies to identify the challenges and suggest mitigating strategies and future improvement strategy plans. In this Research Topic, we aim to collect findings from past and current livestock genomics and community-based breeding programs, the challenges, the lessons learned, the opportunities, and future perspectives.