摘要
利用高光谱图像技术研究了枇杷叶总黄酮含量在不同生长阶段（新叶、成熟叶、老叶）可视化分布。采集120片枇杷叶高光谱（431～962 nm）图像信息,利用分光光度计法测定枇杷叶片的总黄酮含量,并建立7种定量预测模型,其中最小二乘支持向量机（LS-SVM）模型最佳,校正集和预测集相关系数r分别为0.8705和0.8996,最小均方根误差RMSE分别为1.92 mg/g和1.72 mg/g。逐一提取待测枇杷叶高光谱图像中每个像素点在不同波段的光谱信息,并将其带入最佳模型计算各个像素点处的黄酮含量,从而绘制总黄酮含量在整个枇杷叶上的二维分布图。研究表明,枇杷叶总黄酮含量随新叶、成熟叶、老叶而呈递增趋势,且黄酮含量高的区域集中在叶脉和靠近叶脉的叶肉区域,低的区域集中在叶片边缘和远离叶脉的叶肉区域。研究对枇杷叶的分类采集有一定的参考价值,为揭示化学活性成分在农产品中的分布规律提供了技术手段。
Ityperspectral imaging technology was used to detect total flavonoid content distribution map in loquat （Erio- botrya japonica） leaves at different growth stages （Young leaf, Mature leaf, Old leaf）. Firstly, 120 loquat leaves were used to collect hyperspectral image data cube and determine total flavonoid concentrations. Secondly, the optimal model （r =0. 8996,tOISE = 1.72 rag/g） for predication of total flavonoid was built using Least-Squares Support Vector Ms- elaine method. Finally,the calibration model was used to predict the total flavonoid content of each pixel in the hyper- spectral image. Distribution maps of total flavonoid content in three leaves （Young leaf,Mature leaf,Old leaf） were cal- culated. Our results indicated that the level of total flavonoid for Young leaf, Mature leaf and Old leaf were in an inereas- ing order. Higher level of total flavonold can be noticed in the leaf mesophyll regions near the primary and secondary veins ,while the lower levels occurred at the margin area of the leaves. This research provided a method to determine ma- jor constituent of food and agricultural products.
出处
《天然产物研究与开发》
CAS
CSCD
北大核心
2016年第3期354-358,共5页
Natural Product Research and Development
基金
国家高新技术研究发展计划(863计划)(2011AA100807)
全国优秀博士基金(200968)
国家自然科学基金(61301239)
新世纪优秀人才项目(NCET-11-00986)
江苏省杰出青年基金(BK20130010)
江苏省研究生创新基金(KYLX_1070)
关键词
高光谱图像技术
枇杷叶
总黄酮
支持向量机
叶面分布
hyperspeetral imaging technology
loquat leaf
total flavonoid content
support vector machine
distribution
