Whole Process Tracing Model of Pigeon Quality in Block Chain Environment

In order to improve the whole process traceability of meat pigeon quality, a whole process traceability model of meat pigeon quality based on block chain data fusion is proposed. The method comprises the following steps of: constructing a statistical information distribution model for tracing the whole process of meat pigeon quality; reorganizing the structure of information sources for tracing the whole process of meat pigeon quality by adopting a data structure reorganization method; establishing an information source characteristic distribution model for tracing the whole process of meat pigeon quality; carrying out tracking identification and large data mining of meat pigeon quality information by adopting an association rule mining method under a block chain mode; constructing a meat pigeon quality whole process tracing model; and combining information extraction and optimal scheduling of meat pigeon quality. The quantitative feature distribution set of meat pigeon quality is extracted, and the statistical feature analysis of the whole process traceability of meat pigeon quality is realized by combining the information detection and feature positioning methods. The dynamic evaluation of meat pigeon quality information is realized by using the meat pigeon quality statistical large data analysis method. The optimization design of the whole process traceability model of meat pigeon quality is realized by combining the block chain data fusion and the knowledge map feature analysis method. The simulation results show that the method has good real-time performance, strong dynamic tracing ability and good information positioning ability for the quality of meat pigeons.