大米供应链中黄曲霉菌风险概率快速评估方法

A rapid risk probability assessment of Aspergillus flavus in rice supply chain

针对大米供应链中黄曲霉菌的定量风险评估分析时间过长等问题,提出了一种基于贝叶斯网络推理与微生物生长预测模型结合的快速风险评估的建模方法。该模型通过贝叶斯公式得到各节点的联合风险概率分布,并将黄曲霉菌的生长预测模型加入供应链节点中,进而得出各节点黄曲霉菌风险概率的解析解。最后通过对供应链中不同温度下黄曲霉菌的风险概率对比进行案例验证。结果表明,该方法能快速有效地反映供应链节点的风险概率,为企业在生产流通过程中预防和管理安全风险提供有力的工具,具有重要的理论和应用价值。

Considering the problem of long-term quantitative risk assessment of Aspergillus flavus in the rice supply chain,a rapid risk assessment modeling method based on Bayesian network inference and microbial growth prediction model is proposed.This model obtains the joint risk probability distribution of each node through the Bayesian formula,and adds the Aspergillus growth prediction model to the supply chain node,and then obtains the analytical solution of the risk probability of Aspergillus flavus at each node.Finally,a case study is performed by comparing the risk probabilities of Aspergillus flavus at different temperatures in the supply chain.The results show that this method can quickly and effectively reflect the risk probability of supply chain nodes,and provide a powerful tool for enterprises to prevent and manage security risks in the process of production and circulation,which has important theoretical and application values.