Optimal contribution breeding and matching calculation method applied to endangered rare cattle and sheep

By optimizing breeding stock retention and selection using genetic algorithms and simulated annealing algorithms, and combining pedigree and genomic kinship matrices, the problems of maintaining genetic diversity and controlling inbreeding in endangered cattle and sheep populations have been solved, achieving efficient population management and protection.

CN122090925APending Publication Date: 2026-05-26SHANDONG AGRICULTURAL UNIVERSITY
0 Cites 0 Cited by

Patent Information

Application Number
CN202610293762.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-03-11
Publication Date
2026-05-26

AI Technical Summary

Technical Problem

Existing technologies lack efficient and intelligent population selection strategies, making it difficult to balance the maintenance of genetic diversity and inbreeding control in the context of big data. This leads to endangered cattle and sheep populations facing the risk of inbreeding, affecting their adaptability and survival probability.

Method used

By employing genetic algorithms and simulated annealing algorithms, combined with pedigree and genomic kinship matrices, we optimized the calculation methods for seed retention and selective mating. By minimizing the average kinship of the next generation population, we reduced the risk of inbreeding and ensured genetic diversity.

Benefits of technology

It effectively reduces the risk of inbreeding, improves the efficiency and quality of breeding, reduces human intervention, is suitable for the protection of genetic resources of livestock such as cattle and sheep, and has strong versatility and adaptability.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention discloses an optimal contribution breeding and matching calculation method applied to endangered rare cattle and sheep. The method comprises the following steps: acquiring pedigree data and genome information of the rare cattle and sheep; constructing a pedigree genetic relationship matrix according to the pedigree data; constructing a genome genetic relationship matrix according to the genome information; based on the pedigree genetic relationship matrix or the genome genetic relationship matrix, using a genetic algorithm to minimize a population average genetic relationship, and determining an eliminated individual set; for the reserved individual set, calculating an individual optimal contribution value by using a simulated annealing algorithm; and based on the optimal contribution values of all individuals, using a simulated annealing algorithm to minimize the average genetic relationship among all pairs, and obtaining a target matching scheme. According to the method, constraint conditions such as gender proportion and group scale and genetic relationship control are considered, the purpose of minimizing the average genetic relationship coefficient of the next-generation group is taken as a target, the inbreeding risk is greatly reduced, and the genetic diversity of the group is guaranteed.
Need to check novelty before this filing date? Find Prior Art