Reliable prediction of the risk of mold development in a stored bulk of rapeseeds may help to maintain seed quality and ensure the highest quality and safety of cooking oil. Mathematical models based on predictive microbiology that are able to assess the risk of fungal growth and the mycotoxins formation in a stored seed ecosystems are promising prognostic tools, which may improve postharvest management systems. The aim of the study was to develop a predictive model of fungal growth in bulks of rapeseeds stored under conditions, in which seeds are at risk of quality deterioration. It was formulated on the basis of data reflecting actual seed ecosystems with a hazardous initial level of mold spores (characteristic of seeds that vegetate and are harvested under adverse weather conditions) stored at a wide range of temperature (12–30 °C) and humidity (seed water activity, a_w = 0.80–0.90). The predictive model was based on the modified Gompertz equation, whose coefficients are related with biological parameters of mold growth (i.e., lag phase duration, maximum growth rate and fungal population level at the stationary phase). The biological parameters of the model were described using the second‐degree polynomial functions of temperature and water activity. The criteria used to assess the model efficiency pointed to its good predictive quality (R² = 0.90; RMSE =0.547). Moreover, the model was characterized by high accuracy (bias factor B _f = 1.045 and accuracy factor A _f = 1.050). The formulated model of fungal growth can be used as a decision support tool to improve systems managing postharvest seed preservation processes.

中文翻译：

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用于评估作为收获后管理系统决策支持工具的散装油菜籽中霉菌生长风险的预测模型

可靠地预测储存的大量油菜籽中发霉的风险可能有助于维持种子质量并确保食用油的最高质量和安全性。基于预测微生物学的数学模型能够评估储存的种子生态系统中真菌生长和霉菌毒素形成的风险，是有希望的预后工具，可以改善收获后的管理系统。该研究的目的是建立在一定条件下储存的大量油菜籽中真菌生长的预测模型，在这种条件下种子存在质量下降的风险。_w = 0.80–0.90）。该预测模型基于改进的Gompertz方程，该方程的系数与霉菌生长的生物学参数（即，滞后期，持续时间，最大生长速率和静止期的真菌种群水平）有关。使用温度和水活度的二次多项式函数描述了模型的生物学参数。用于评估模型效率的标准指出其良好的预测质量（R ² = 0.90； RMSE = 0.547）。此外，该模型具有较高的精度（偏置因子B _f = 1.045和精度因子A _f = 1.050）。真菌生长的模型可以用作决策支持工具，以改善管理收获后种子保存过程的系统。