Presented at XIX Conference 2025, EUCARPIA: Biometrics Plant Breeding, 17-19 Sep, Edinburgh, UK.

Mate allocation is a critical component of plant breeding programs, which aims to generate superior progenies and improved populations over time. While numerous methodologies for mate allocation exist, few software tools offer a unified and scalable framework that integrates these keymethodologies in a user-friendly manner. CrossingTools addresses this gap by providing a flexible, efficient solution for optimizing mating decisions across a wide range of breeding schemes. The package supports genomic BLUP and selection indices for a wide range of variance structures and implements a variety of selection criteria to evaluate the potential of a cross, including the expected mean, optimal haploid value and the superior progeny value. For the latter, different methods to calculate the additive and dominance segregation variances for both inbred and heterozygote parents are implemented, which makes CrossingTools well-suited to any breeding scheme. After criteria calculation, the user can ran all potential crosses based on the selected criterion or apply CrossingTools’ optimal crossing selection routine, which balances genetic gain and genetic diversity to support long-term improvement. The package is implemented within the R statistical environment using C++ subroutines, allowing a user-friendly scripting language while ensuring high computational performance and scalability for large populations with dense marker data. The flexibility and utility of CrossingTools are demonstrated through simulation studies comparing different selection criteria in both classical line breeding programs and two-part breeding schemes.

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