The application relates to the field of animal genetic breeding technology, and discloses a local pig
breed multi-node block chain collaborative breeding method. According to the method, key data abstracts, evaluation results, model versions and breeding decisions are chained and left marks in a
window period through a permissioned consortium chain and a
consensus verification mechanism, the source is clear, tamper-proof and auditable, the problem that data standards are different, difficult to trace and difficult to trust in traditional multi-subject
collaboration is solved, in addition, an AI multi-factor breeding
evaluation system can simultaneously process multiple traits such as meat quality, growth,
reproduction, health resistance and environmental management factors, can depict the
nonlinear correlation between complex traits, can improve the evaluation precision and stability of the comprehensive genetic value of local pig breeds, can reduce the risk of decision-making errors caused by single-
point data or single-
algorithm deviation, can realize cross-node alignment and joint use of dispersed data through a rolling window and a labeled archive, and can make up for the short board of insufficient samples of a single breeding unit.