不同颜色银杏叶总黄酮含量分布高光谱图像检测

Determination of Total Flavonoid Content Distribution on Different Color Ginkgo Biloba Leaves

利用近红外高光谱图像技术研究了总黄酮含量在不同颜色（绿色、黄绿色、黄色）银杏叶片上的二维分布规律。采集120片银杏叶在近红外波段（900—1700nm）下的高光谱图像信息，并利用分光光度计法测定银杏叶片的总黄酮含量；计算高光谱图像中不同波段下的平均灰度作为银杏叶对应的光谱信息，利用逐步线性回归方法建立黄酮含量校正模型（R=0．9307）；逐一提取待测银杏叶高光谱图像中每个像素点在不同波段的光谱信息，并将其代入黄酮含量校正模型以计算出各个像素点处对应的黄酮含量，从而绘制总黄酮含量在整个银杏叶片上的二维分布图。研究结果表明，银杏叶总黄酮含量随着绿色、黄绿色、黄色而呈现出递增趋势，且总黄酮含量高的区域主要位于叶片的边缘，总黄酮含量低的区域主要位于叶柄附近。研究为揭示有机组分在农产品、食品中的分布规律提供了枯术手段．

Hyperspectral imaging technology was used to determine total flavonoid content distribution map on different color ginkgo biloba leaves （green, green-yellowish, yellow）. Firstly, 120 Ginkgo biloba leaves were used to collect hyperspectral image data cube and determine total flavonoids concentrations. Secondly, the average gray value of each band in hyperspectral image data cube was calculated as spectal data of Ginkgo biloba leaf. The speetal data and total flavonoids concentrations were used to bulid calibration model （R = 0. 930 7） by using multiple stepwise regression method. Finaly, the calibration model was used to predict the total flavonoid content of each pixel in the hyperspectral image. This enables construction of a distribution map of total flavonoid content on the ginkgo leave. Distribution maps of total flavonoid content in three color groups （green, green-yellowish, yellow） were calculated. Results indicate that the level of total flavonoid for green, green-yellowish, and yellow were in an increasing order. Higher level of total flavonoids could be noticed at the margin area of the leaves, while lower levels occured at the area near the leafstalk of the ginkgo leaves. This research provided a method to determine major constituent of food and agricultural products.