光谱学与光谱分析, 2016, 36 (11): 3657, 网络出版: 2016-12-30   

油菜光谱的多重分形分析及叶绿素诊断建模

Multifractal Analysis of Rapeseed Spectrum for Chlorophyll Diagnosis Modeling
王晓乔 1,2,3,*王访 1,2廖桂平 1,2官春云 1,4
作者单位
1 湖南农业大学/南方粮油作物协同创新中心, 湖南 长沙 410128
2 湖南农业大学理学院, 湖南 长沙 410128
3 湖南科技大学管理学院, 湖南 湘潭 411201
4 湖南农业大学农学院, 湖南 长沙 410128
摘要
作物信息科学的重要内容是如何利用作物的信息对其进行无损营养诊断, 光谱分析是一种有效可行的途径。 对于油菜而言, 冠层光谱的特征是描述其营养状况的重要指标。 但由于原始光谱总是受到一些如环境、 气候等外在因素的影响, 其巨大的波动导致难以直接用于油菜生物量的诊断。 然而, 光谱的多重分形特征将保持相对稳定。 为研究油菜冠层光谱与叶绿素含量的关系, 基于多重分形理论, 提出了基于油菜冠层光谱特征的叶绿素定量预测模型和定性识别模型。 以24个移栽种植小区和24个直播种植小区的高油酸油菜苗期样本为试验对象。 首先, 利用流行的多重分形去趋势波动分析提取了6个不同波段范围内光谱的广义Hurst指数和质量指数及其他相关的特征参数, 发现它们都呈现典型的多重分形特性。 但两种不同种植方式下的光谱特征也存在差异。 接着, 通过多重分形特征参数与SPAD值的相关分析发现不同波段的光谱所含的有效信息不同。 以多重分形特征参数建立单变量油菜叶片SPAD值预测模型, 移栽方式、 直播方式及混合样本的预测模型相对均方根误差均小于5%。 最后, 以多重分形特征组合建立识别模型, 以Fisher线性判别法识别移栽和直播两种种植方式的最大约登指数为0.902 5, 对应最敏感波段为350~1 350 nm。 这项有意义的工作为预测油菜叶绿素提供了理论基础和实践方法, 也为寻找敏感波段进行识别诊断提供了有效的途径。
Abstract
One of the most important topics in crop information science is how to make use of the crop’s information for non-destructive nutrient diagnosiswhich can be solved with spectrum analysis. The canopy’s spectrum feature is a key indicator to describe the nutritional status for the rapeseeds. The original spectrum is to be disturbed with external factors such as environment and climate; however, it is difficult to be directly used for rapeseed biomass diagnosis due to its huge fluctuation. However, the multifractal feature of the spectra remains stable relatively. In order to study the relationship between the canopy’s spectrum of the rapeseed and its chlorophyll, based on the multifractal theory, a quantitative model of chlorophyll prediction and a qualitative model of planting pattern identification were proposed in this paper to study the high oleic acid rapeseed samples in 24 transplanting regions and 24 direct planting regions. At first, the generalized Hurst exponent and mass exponents together with other relevant multifractal parameters of the spectra were extracted with popular multifractal detrended fluctuation analysis (MF-DFA) in different six considered wavelength ranges. It shows that all of them possess representative multifractal nature. However, there are some differences of the multifractal characteristics between the two kinds of regions with different planting pattern in some bands. In addition, by correlation analysis and detection between the multifractal parameters of the spectra and the SPAD values in six considered ranges of bands, it demonstrates that there is some difference of the effective information content in the different ranges of bands. In the quantitative model of chlorophyll prediction, for each groups of samples in transplanting regions and direct planting regions and mixed together in each significant bands, a selected multifractal parameter was used to establish the univariate model for predicting the rapeseed leaf’s SPAD values, respectively. The results of all the relative root mean square errors are small than 5%. Finally, the qualitative model was proposed to distinguish the samples by the two planting pattern. Youden index, as the identification accuracy was calculated for the six considered ranges of bands by the Fisher’s linear discriminant analysis. The best Youden index is 0.902 5 and the corresponding band range is 350~1 350 nm. The significant work provides a theoretical and practical method for predicting rapeseed leaf’s SPAD and also provides effective way to find the sensitive bands of the spectra for identification diagnosis.

王晓乔, 王访, 廖桂平, 官春云. 油菜光谱的多重分形分析及叶绿素诊断建模[J]. 光谱学与光谱分析, 2016, 36(11): 3657. WANG Xiao-qiao, WANG Fang, LIAO Gui-ping, GUAN Chun-yun. Multifractal Analysis of Rapeseed Spectrum for Chlorophyll Diagnosis Modeling[J]. Spectroscopy and Spectral Analysis, 2016, 36(11): 3657.

本文已被 1 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!