Software

Managing multi-stage selection within and across cohorts of animals in multi-unit breeding programs

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Abstract

This study presents example applications of a 'Flow Control' method for coordinated selection across multiple units in a breeding program. Units can include nucleus farms, semen collection stations, test stations and multiplier units. Inventories of males and females at these units are typically managed with some periodic attrition of older stock and infusion of younger stock. The method targets desired genetic gains, trait profiles, logistical constraints, etc. There is possibility for custom targets for specified breeding units, such as emphasising particular traits for a specific multiplier unit. This is done while simultaneously managing genetic diversity/inbreeding across the whole operation. An example is described, involving controlled flow of animals from test stations to nucleus farms for three separate lines of pigs. The example uses a real scenario and real data, and the results are coordinated decisions on selection, culling and migration of individual animals across multiple breeding units. In practice, this involves fulfilling weekly requirements for topping up animal inventories, with constraints applied on a disease resistance marker, selection index and progeny inbreeding, while managing overall diversity. By integrating constraints at multiple stages, it provides a detailed understanding of selection outcomes for each phase, family representation, and potential bias in disease marker frequencies among families available for breeding in a given week. Outcomes from using this method and the overall system that drives it will be presented. Plans for increasing the scope of this Flow Control method to cover all parts of the breeding operations will be discussed. The "Flow Control" method provides a practical and flexible tool for managing coordinated selection across multiple breeding units and selection stages while controlling inbreeding and maintaining genetic diversity. It allows integration of genetic and logistical constraints into a unified decision-making framework, thereby supporting both genetic improvement and sustainable breeding management.

Keywords: 2026

How to Cite:

Bhatia, V., Borg, R., Cross, A., Kinghorn, A., Kinghorn, B., Rathje, T., Solar Diaz, I. & Walugembe, M., (2026) “Managing multi-stage selection within and across cohorts of animals in multi-unit breeding programs”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2286636. doi: https://doi.org/10.31274/wcgalp.24073

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