Development of optimum freezing process prediction model based on high-precision three-dimensional internal structure and component information

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Fundamental studies on the Cryogenic Micro Slicer Image Processing System (Cryo-MSIPS) designed and prototyped in this project revealed that the Cryo-MSIPS was sufficiently applicable to biological and food materials. At the same time, some problems in managing the Cryo-MSIPS were also solved : unstable control of the slicing section in the system, vibration of the observation section in a microscope, unstable control of the cooling surface temperature when the cooling section was cooled to -80℃, and heat transfer losses at the contact surface between the system and the observation samples. Calibration curves between absorbance and absorption wavelength were made on pure water as well as pure ice to observe internal structure and component information in frozen samples by a near infrared camera These results indicated that water and ice have different absorption wavelengths, and then different kinds of biological and food materials have also different absorption wavelengths for ice. Furthermore, the results also suggested that two indicators of freezing rate as well as absorbance were the governing factors for internal structural parameters of frozen materials and optimal freezing processes of biological and food materials.