A mathematical model was developed to correlate the four heat penetration parameters of 57 Stumbo’s tables (18,513 datasets) in canned food: (the difference between the retort and the coldest point temperatures in the canned food at the end of the heating process), ℎ/ (the ratio of the heating rate index to the sterilizing value), (the temperature change required for the thermal destruction curve to traverse one log cycle), and , (the cooling lag factor). The quantities , , and , are input variables for predicting ℎ/, while , and ℎ/ are input variables for predicting the value of , which is necessary to calculate the heating process time , at constant retort temperature, using Ball’s formula. The process time calculated using the value obtained from themathematicalmodel closely followed the time calculated fromthe tabulated values (rootmean square of absolute errors RMS = 0.567 min, average absolute error = 0.421 min with a standard deviation SD = 0.380 min). Because the mathematical model can be used to predict the intermediate values of any combination of inputs, avoiding the storage requirements and the interpolation of 57 Stumbo’s tables, it allows a quick and easy automation of thermal process calculations and to perform these calculations using a spreadsheet.
A New Mathematical Model for Food Thermal Process Prediction
FRISO, DARIO
2013
Abstract
A mathematical model was developed to correlate the four heat penetration parameters of 57 Stumbo’s tables (18,513 datasets) in canned food: (the difference between the retort and the coldest point temperatures in the canned food at the end of the heating process), ℎ/ (the ratio of the heating rate index to the sterilizing value), (the temperature change required for the thermal destruction curve to traverse one log cycle), and , (the cooling lag factor). The quantities , , and , are input variables for predicting ℎ/, while , and ℎ/ are input variables for predicting the value of , which is necessary to calculate the heating process time , at constant retort temperature, using Ball’s formula. The process time calculated using the value obtained from themathematicalmodel closely followed the time calculated fromthe tabulated values (rootmean square of absolute errors RMS = 0.567 min, average absolute error = 0.421 min with a standard deviation SD = 0.380 min). Because the mathematical model can be used to predict the intermediate values of any combination of inputs, avoiding the storage requirements and the interpolation of 57 Stumbo’s tables, it allows a quick and easy automation of thermal process calculations and to perform these calculations using a spreadsheet.File | Dimensione | Formato | |
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