淀粉粒微结构数字图像表征及其分子构象变化的显微光谱解析

Starch is the major plant polysaccharide consumed by mankind. Knowledge of the structure of starch is important for understanding functionality. The current view of the Microstructure of starch granules has been largely derived from microscopy and scattering studies. The representative of the picture and the accuracy of interpretation are closely related with the experience of researchers, and most of the explanation can only be subjective and qualitative. Quantitative analysis of the microstructure and molecular conformation changes in starch granules remains to be explored for overcoming the drawbacks of traditional manual method..To address these issues, computer image processing technology is used to study the color images quantitative features of the starch granules microstructure based on optical microscope, the grayscale and the depth image quantitative features of the starch granules ultrastructure based on scanning electron microscopy and atomic force microscopy respectively. Meanwhile, microscopic spectrometer combined with digital image analysis method are used to study spectra quantitative characteristics of starch granules chemical structure based on infrared spectroscopy and starch granules molecular conformation changes based on Raman spectroscopy. The research aims to develop quantitative methods for automatic image representation of microstructure and microspectroscopy analysis of chemical conformation changes in starch granules. What’s more, the established effective feature extraction and quantitative methods are proposed to investigate the changes of maize starch induced in different mutants and structural variation of potato starch during heating processing. The microstructure of the starch granules affect the quality of the processed products. Digital image processing techniques are available to extract quantitative features related to microstructure, and quantitative analysis provides an objective and repeatable means for evaluating the structural changes. The research makes the mechanism of starch microstructure analysis method Improved clear..Based on the previous research of applicant, the image processing algorithms and the image features best correlating with the microstructure of starch granules or its structural variation during processing are investigated in this study using In situ mapping method combined with automatic platform and quantitative analysis. This work pay attention to innovation of basic theory and technology method, automatic analysis driven by computer vision and advanced nanoscale analytical instruments provide objective and accurate representation. The research is expected to form a key technical support to quantitative analysis of the microstructure in starch granules, and provide a reliable basis for further study of the micro mechanism of special varieties or processing on the microstructure, which is a key to the improved delivery of high quality starch products.

淀粉生物学结构与其品质和功能密切相关。基于各种显微镜和化学成像技术的淀粉粒微结构分析，其客观性和准确度受限于研究者人工解读。本项目结合显微图谱技术和数字图像分析，研究淀粉粒微结构光学显微镜彩色图像量化表征、超微结构扫描电镜灰度图像和原子力显微镜深度图像量化表征，分析淀粉粒化学结构和分子构象的显微红外、拉曼谱图特征变化，建立淀粉粒微结构有效特征提取和自动分析方法，并通过不同基因玉米淀粉表型特征识别、马铃薯淀粉加热凝胶过程的微结构变化分析进行实施验证，明确淀粉微结构解析方法的改进机理。本研究旨在克服传统人工分析的弊端，将精确、客观和可重复的计算机图像处理算法融入淀粉微纳尺度系统，在前期研究基础上采用原位表征机制结合自动平台和量化分析方法，揭示种源和加工过程对淀粉粒的微观影响规律。研究成果有望形成对淀粉粒微结构量化分析的关键支撑，为专用品种选育和加工过程中淀粉品质变化研究提供微结构自动解析基础。

农业物料结构信息的准确解读是揭示其品质与功能的基础。本项目研究了淀粉粒微结构数字图像表征及其分子构象变化的显微光谱解析方法，分别利用普通光学显微镜、扫描电镜和原子力显微镜获取淀粉粒微结构彩色图像、超微结构灰度图像和深度图像，在此基础上进行了原位分析和数字图像量化表征；利用近红外光谱仪、中红外显微镜和拉曼显微镜分别获取试样显微红外、拉曼谱图信息，进行了淀粉粒微结构谱图解析方法研究；进一步针对具体应用，研究了几种图像分割算法和分子构象的显微光谱解析方法，并通过不同基因玉米淀粉表型特征识别和品种分类、马铃薯淀粉加热凝胶过程的微结构变化分析进行了实施例研究。结果表明建立的淀粉粒微结构有效特征提取和自动分析方法，在分别用于5种不同链/支比玉米品种切片试样、10种玉米品种整粒试样、4种马铃薯品种全粉制样的分析研究中均取得了较好的效果，利用加热凝胶过程的微结构变化分析还可对马铃薯全粉与面粉混合物的混合比例进行鉴别。通过本项目研究明确了淀粉微结构解析方法的改进机理，揭示了种源和加工过程对淀粉粒的微观影响规律，并对淀粉纳米晶进行了拓展研究。在本项目的支持下，课题组已发表了标注资助论文17篇，其中SCI/EI收录论文16篇（影响因子大于5的3篇，大于3小于5的6篇）；申请国家发明专利5项，其中已获得授权3项，并取得软件著作权登记3项，培养5名以上研究生。项目研究成果形成了对淀粉粒微结构量化分析的关键支撑，为专用品种选育和加工过程中淀粉品质变化研究提供微结构自动解析基础。