CAJ | 학술논문

为了模拟贮藏玉米中主要生态因子对黄曲霉生长的影响，利用Baranyi和Roberts函数拟合了玉米中黄曲霉的生长数据，得到了不同温度和水分活度下玉米中黄曲霉的生长动力学模型。应用一个二次多项式函数分别建立了描述水分活度（aw）和温度对菌落生长的组合影响的模型。对模型的有效性分别进行了验证，其偏离因子分别为0.896和0.963。精确因子都小于1.15。结果证明构建的二次多项式预测模型可以很好的预报aw和温度对黄曲霉生长的比生长速率和迟滞期的组合影响。得出的方程可以用于预测贮藏玉米中黄曲霉生长情况。
위료모의저장옥미중주요생태인자대황곡매생장적영향，이용Baranyi화Roberts함수의합료옥미중황곡매적생장수거，득도료불동온도화수분활도하옥미중황곡매적생장동역학모형。응용일개이차다항식함수분별건립료묘술수분활도（aw）화온도대균락생장적조합영향적모형。대모형적유효성분별진행료험증，기편리인자분별위0.896화0.963。정학인자도소우1.15。결과증명구건적이차다항식예측모형가이흔호적예보aw화온도대황곡매생장적비생장속솔화지체기적조합영향。득출적방정가이용우예측저장옥미중황곡매생장정황。
The safety of corn storage is related to food safety and human health. According to the predictive microbiology, the microorganism’s growth in stored corn can be quickly judged in advance by construction of a predictive microbiology model. It plays an important part in controlling the growth of pathogens and spoilage microorganisms in stored grain. It is of important theoretical and practical application value to realize the ecological storage of corn and ensure the security of corn storage. The radial growth of A. flavus on corn was studied in this article. The testing of four temperatures and four aw values was designed. A full factorial design of four temperatures (20, 25, 30, and 35℃) and four aw values (0.97, 0.91, 0.85, 0.81) was used to investigate the growth of A. flavus on corn. The colony growth curve of A. flavus on corn was determined. The objective of the present study was to develop validated models that describe the effect of the main ecological factors on the radial growth of Aspergillus flavus on corn. The growth data of A. flavus on corn under different temperatures and water activity were fitted by the Baranyi and Roberts functions. The corresponding growth kinetics models were built. The higher R2 (0.993-0.998) showed that these growth kinetics models can be a good fit of the experimental conditions on the growth curve of A. flavus on corn. Afterwards, a quadratic polynomial function relating colony growth rate or lag phase to aw and temperature were developed. The models described the combined effect of aw and temperature on the growth rate and th lag phase. The models were validated by using independently collected data, respectively. The obtained bias factors ranged from 0.896 to 0.963, and the accuracy factors were less than 1.15. The MSEs (0.008-0.334) were low, also. These observations were confirmed by the distribution of the validation data about the 3D surfaces of the models. Generally, the validation data was evenly distributed about the model surfaces developed from the quadratic polynomial function. Consequently, the results showed the quadratic polynomial functions built were good predictors for describing the combined effect of aw and temperature on the colony growth rate and the lag phase duration of A. flavus, respectively. The developed equations can be applied to forecast the colony growth of A. flavus in stored corn.