基于EFAST和PLS的苹果叶片等效水厚度高光谱估算
叶片等效水厚度(EWT)是评估果树生长状况及产量的一个重要参数。为了快速、准确地估算此参数,该文建立苹果叶片EWT归一化近红外水分指数(NDIWI)和扩展傅里叶幅度灵敏度检测方法和偏最小二乘回归(EFAST-PLS)估算模型并验证。使用2012年和2013年在中国山东省肥城县潮泉镇获取的整个生育期苹果叶片EWT和配套的光谱数据,比较NDIWI和EFAST-PLS联合模型。在EFAST-PLS联合模型中,EFAST用来选择光谱敏感波段,PLS用来回归分析。NDIWI与EFAST-PLS模型的决定系数(R^2)分别为0.2831和0.5628,标准均方根误差(NRMSE)分别为8.00%和6.25...
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| Published in | 农业工程学报 Vol. 32; no. 12; pp. 165 - 171 |
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| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
国家农业信息化工程技术研究中心,北京 100097
2016
北京市农业物联网工程技术研究中心,北京 100097 农业部农业信息技术重点实验室,北京 100097 北京农业信息技术研究中心,北京 100097 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1002-6819 |
| DOI | 10.11975/j.issn.1002-6819.2016.12.024 |
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| Summary: | 叶片等效水厚度(EWT)是评估果树生长状况及产量的一个重要参数。为了快速、准确地估算此参数,该文建立苹果叶片EWT归一化近红外水分指数(NDIWI)和扩展傅里叶幅度灵敏度检测方法和偏最小二乘回归(EFAST-PLS)估算模型并验证。使用2012年和2013年在中国山东省肥城县潮泉镇获取的整个生育期苹果叶片EWT和配套的光谱数据,比较NDIWI和EFAST-PLS联合模型。在EFAST-PLS联合模型中,EFAST用来选择光谱敏感波段,PLS用来回归分析。NDIWI与EFAST-PLS模型的决定系数(R^2)分别为0.2831和0.5628,标准均方根误差(NRMSE)分别为8.00%和6.25%。研究结果表明:EFAST-PLS模型估算苹果叶片EWT潜力巨大,考虑到应用简单,NDIWI也有可取之处。 |
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| Bibliography: | spectrum analysis; models; moisture content; apple leaves; equivalent water thickness; extended fourier amplitude sensitivity test; partial least squares; normalized difference infrared water index 11-2047/S Equivalent water thickness(EWT) is an important parameter for evaluating the growth status and yield of fruit tree. The objectives of this study were(i) to establish and verify a model for the EWT of the apple leaves, in which the regression models, the extended Fourier amplitude sensitivity test- partial least squares(EFAST-PLS), and the normalized difference infrared water index(NDIWI) model were tested, and(ii) to compare the performances of the proposed models respectively using the EFAST-PLS and the NDIWI model. Spectral reflectance of leaves and concurrently the apple leaves' EWT parameters were acquired in Tai'an area, Shandong, China during apple growth seasons of 2012-2013. Firstly, the apple leaves' EWT sensitivity was analyzed through the EFAST and the PROSPECT model; the results showed that the |
| ISSN: | 1002-6819 |
| DOI: | 10.11975/j.issn.1002-6819.2016.12.024 |