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预测赤霉病菌在小麦上的产脱氧雪腐镰刀菌烯醇的生长动力学参数和模型概率在模拟储存条件下。

Predictive growth kinetic parameters and modelled probabilities of deoxynivalenol production by Fusarium graminearum on wheat during simulated storing conditions.

机构信息

Beijing Engineering and Technology Research Center of Food Additives, Beijing Technology & Business University (BTBU), Beijing, China.

Beijing Innovation Centre of Food Nutrition and Human, Beijing Technology & Business University (BTBU), Beijing, China.

出版信息

J Appl Microbiol. 2022 Aug;133(2):349-361. doi: 10.1111/jam.15557. Epub 2022 Apr 13.

Abstract

AIMS

Mathematical models were employed to predict the growth kinetic parameters of Fusarium graminearum and the accumulation of deoxynivalenol (DON) during wheat storage as a function of different moisture contents (MCs) and temperatures.

METHODS AND RESULTS

The colony counting method was used to quantify F. graminearum growth under different environmental conditions, and kinetic and probability models were developed to describe the effect of different MCs and temperatures on fungal growth and DON production during wheat storage. Among the employed secondary models (Arrhenius-Davey, Gibson and Cardinal), the general polynomial best predicted the fungal growth rate under varying temperature and MC during wheat storage. According to the logistic model, DON contamination was correctly predicted in 96.5% of cases.

CONCLUSIONS

The maximum growth rate of fungi was 0.4889 ± 0.092 Log CFU g  day at 25°C and 30% moisture according to the polynomial model. At below 17°C and ≤15% moisture, no fungal growth was observed. The probability model of toxin production showed no toxin production at less than 15% moisture (a  ≤0.76) and below 15°C.

SIGNIFICANCE AND IMPACT OF THE STUDY

This is the first application of a probability model of DON production during wheat storage, providing a reference for preventing fungal growth and mycotoxin accumulation by F. graminearum during wheat storage and guaranteeing food product safety.

摘要

目的

采用数学模型预测了小麦贮藏过程中镰刀菌的生长动力学参数和脱氧雪腐镰刀菌烯醇(DON)的积累,这一过程与不同的水分含量(MCs)和温度有关。

方法和结果

采用平板计数法定量检测不同环境条件下的禾谷镰刀菌生长情况,并建立了动力学和概率模型,以描述不同 MCs 和温度对小麦贮藏过程中真菌生长和 DON 产生的影响。在所采用的二次模型(Arrhenius-Davey、Gibson 和 Cardinal)中,通用多项式模型最好地预测了小麦贮藏过程中温度和 MC 变化下真菌的生长速率。根据逻辑斯蒂模型,DON 污染的预测准确率为 96.5%。

结论

根据多项式模型,真菌的最大生长速率为 0.4889±0.092Log CFU g-1 day-1,温度为 25°C,水分含量为 30%。在 17°C 以下和水分含量≤15%的情况下,未观察到真菌生长。毒素产生的概率模型表明,在水分含量低于 15%(a≤0.76)和温度低于 15°C 的情况下,不会产生毒素。

意义和影响

这是首次在小麦贮藏过程中应用 DON 产生概率模型,为防止小麦贮藏过程中禾谷镰刀菌的生长和真菌毒素的积累提供了参考,保证了食品的安全。

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