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

本课题所设计和研制的低温微切片机图像处理系统（Cryo-MSIPS）的基础研究表明，低温微切片机图像处理系统在生物材料和食品材料上具有良好的应用前景。同时，还解决了Cryo-MSIPS管理中的一些问题：系统中切片切片的控制不稳定、显微镜下观察切片的振动、冷却切片冷却至-80℃时冷却表面温度的控制不稳定、系统与观察样品接触面的传热损失等。用近红外相机分别对纯水和纯冰进行了吸光度与吸收波长的标定曲线，观察了冷冻样品的内部结构和成分信息。结果表明，水和冰具有不同的吸收波长，而不同种类的生物和食品材料对冰也具有不同的吸收波长。结果还表明，冷冻速率和吸光度两个指标是冷冻材料内部结构参数以及生物和食品材料最佳冷冻工艺的控制因素。

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.