您好，欢迎访问新疆农垦科学院 机构知识库！
新疆农垦科学院机构知识库

全部

  • 全部
  • 标题
  • 学者
  • 机构
  • 关键词

Estimation Models for Jujube Leaf Pigment Concentration with Hyperspectrum Data at Canopy Scale

文献类型： 外文期刊

作者： Liu Wei-yang 1 ; Peng Jie 1 ; Dou Zhong-jiang 2 ; Chen Bing 2 ; Wang Jia-qiang 1 ; Xiang Hong-ying 1 ; Dai Xi-jun 3 ; Wan 1 ;

作者机构： 1.Tarim Univ, Coll Plant Sci, Alar 843300, Peoples R China

2.Xinjiang Acad Agr & Reclamat Sci, Shihezi 832000, Peoples R China

3.Tarim Univ, Coll Mech & Elect Engn, Alar 843300, Peoples R China

关键词： Jujube;Pigment;Canopy scale;Visible and near infrared spectrum;Quantitative inversion model

期刊名称：SPECTROSCOPY AND SPECTRAL ANALYSIS （ 影响因子：0.589； 五年影响因子：0.504 ）

ISSN： 1000-0593

年卷期： 2017 年 37 卷 1 期

页码：

收录情况： SCI

摘要： Plant canopy pigment concentration is a critical variable for agricultural remote sensing due to its close relationship to leaf nitrogen content. The aims of this study were to: (1) compare the prediction performances on chlorophyll, chlorophyll-a and b, and carotenoid concentration in jujube leaf at canopy scale between partial least squares regression (PLSR) and support vector machine (SVM), (2) develop quantitative models to estimate pigment concentration in jujube canopy using hyperspectral data and provide theoretical and technical support for rapidly, non-destructive, less expensive and eco-friendly measuring the concentration. Results from correlation analysis showed that jujube canopy pigment concentration correlated strongly with hyperspectral data. What's more, the hyperspectral data was better correlated by chlorophyll and chlorophyll-a than chlorophyll-b and carotenoid. Results of independent samples tested in predicting performance indicated that both of the PLSR and SVM models could effectively estimate pigment concentration, however, with different prediction precisions. Additionally, the precision of SVM outperformed PLSR for predicting chlorophyll and carotenoid. Whereas chlorophyll-a and chlorophyll-b were better predicted using PLSR than SVM. Compared among all the pigments' prediction precisions with corresponding optimal inversion models showed that prediction precisions on chlorophyll, chlorophyll-a and carotenoid were superior to chlorophyll-b. The determination coefficients and residual prediction deviation from predicting chlorophyll, chlorophyll-a and carotenoid were higher than 0.8 and 2.0, respectively, while the mean relative error values were lower than 13%. And the corresponding values from predicting chlorophyll-b were 0.60%, 20.79% and 1.79% respectively.

  • 相关文献
作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：新疆农垦科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台