Simulation of effect of main ecological factors on radial growth of Aspergillus flavus during storage period of corn

Abstract: 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 con?rmed 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.