大米供应链中黄曲霉菌风险概率快速评估方法
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摘要
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.
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.
引文
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[19]杨浩雄,王丹,崔丽.供应链视角下的大米安全监管模式[J].江苏农业科学,2015,43(1):267﹣269.
[20]彭坚,韩北忠.小麦中黄曲霉生长的预测模型[J].河南工业大学学报(自然科学版),2005,26(2):51﹣54.
[2]杨浩雄,王丹,崔丽.供应链视角下的大米安全监管模式[J].江苏农业科学,2015,43(1):267﹣269.
[3]李培武,丁小霞,白艺珍,等.农产品黄曲霉毒素风险评估研究进展[J].中国农业科学,2013,46(12):2534﹣2542.
[4]刘丽梅,高永超,王玎.食品中微生物危害的风险评估建模方法改进与应用[J].农业工程学报,2014,30(6):279﹣286.
[5]Zhu J H.China’s food microbiological risk assessment progress and prospect[J].Chinese Journal of Food Hygiene,2016.
[6]张娜,郭庆启,韩春然,等.模糊数学法在餐饮食品微生物风险评估中的应用[J].中国食品学报,2017,17(8):210﹣216.
[7]王瑞,李婷,赵玉梅,等.多维灰聚类评估在山西老陈醋质量评价中的应用[J].食品工业,2014,(7):166﹣168.
[8]李亚楠,傅忠宁,张龙忠,等.基于物元分析的鲜活农产品供应链风险评价[J].物流技术,2015,(1):212﹣215.
[9]Abiyev R H,Uyar K,Ilhan U,et al.Assessment of Food Security Risk Level Using Type 2 Fuzzy System[J].Procedia Computer Science,2016,102:547﹣554.
[10]Brul S,Bassett J,Cook P,et al.‘Omics’technologies in quantitative microbial risk assessment[J].Trends in Food Science&Technology,2012,27(1):12﹣24
[11]Williams M S,Ebel E D,Hoeting J A,et al.Bayesian Analysis for Food﹣Safety Risk Assessment:Evaluation of Dose﹣Response Functions within WinBUGS[J].Journal of Statistical Software,2011,43(c02):1﹣14.
[12]Yuan Y,Chen C,Zheng C,et al.Residue of chlorpyrifos and cypermethrin in vegetables and probabilistic exposure assessment for consumers in Zhejiang Province,China[J].Food Control,2014,36(1):63﹣68.
[13]赵静娴.基于决策树的食品安全评估研究[J].安徽农业科学,2011,39(32):20259﹣20259.
[14]Liu L,Gao Y,Wang Y.Improvement and application of modular process risk modeling method for microbial risk assessment[J].Nongye Gongcheng Xuebao/transactions of the Chinese Society of Agricultural Engineering,2013,9(5):434﹣438.
[15]Romero﹣Barrios P,Hempen M,Messens W,et al.Quantitative microbiological risk assessment(QMRA)of food﹣borne zoonoses at the European level[J].Food Control,2013,29(2):343﹣349.
[16]李瑞芳,韩北忠,陈晶瑜,等.黄曲霉生长预测模型的建立及其在玉米储藏中的应用[J].中国粮油学报,2008,23(3):144﹣147.
[17]韩舒伊,刘珏,郑宁,等.玉米中黄曲霉菌生长特性[J].北京农业,2013,33.
[18]邱静,董庆利,程飞.气调包装冷却猪肉中假单胞菌生长概率模型的构建[J].农业工程学报,2012,28(13):257﹣262.
[19]杨浩雄,王丹,崔丽.供应链视角下的大米安全监管模式[J].江苏农业科学,2015,43(1):267﹣269.
[20]彭坚,韩北忠.小麦中黄曲霉生长的预测模型[J].河南工业大学学报(自然科学版),2005,26(2):51﹣54.