Fassnacht Fabian E, Stenzel Stefanie, Gitelson Anatoly A
Karlsruhe Institute of Technology, Institute of Geography and Geoecology, Kaiserstraße 12, 76131 Karlsruhe, Germany.
Israel Institute of Technology (Technion), Civil and Environmental Engineering, Rabin Building, 32000 Haifa, Israel; School of Natural Resources, University of Nebraska, Lincoln, USA.
J Plant Physiol. 2015 Mar 15;176:210-7. doi: 10.1016/j.jplph.2014.11.003. Epub 2014 Nov 27.
Leaf pigment content is an important indicator of plant status and can serve to assess the vigor and photosynthetic activity of plants. The application of spectral information gathered from laboratory, field and remote sensing-based spectrometers to non-destructively assess total chlorophyll (Chl) content of higher plants has been demonstrated in earlier studies. However, the precise estimation of carotenoid (Car) content with non-destructive spectral measurements has so far not reached accuracies comparable to the results obtained for Chl content. Here, we examined the potential of a recently developed angular vegetation index (AVI) to estimate total foliar Car content of three tree species. Based on an iterative search of all possible band combinations, we identified a best candidate AVIcar. The identified index showed quite close but essentially not linear relation with Car contents of the examined species with increasing sensitivity to high Car content and a lack of sensitivity to low Car content for which earlier proposed vegetation indices (VI) performed better. To make use of the advantages of both VI types, we developed a simple merging procedure, which combined the AVIcar with two earlier proposed carotenoid indices. The merged indices had close linear relationship with total Car content and outperformed all other examined indices. The merged indices were able to accurately estimate total Car content with a percental root mean square error (%RMSE) of 8.12% and a coefficient of determination of 0.88. Our findings were confirmed by simulations using the radiative transfer model PROSPECT-5. For simulated data, the merged indices again showed a quasi linear relationship with Car content. This strengthens the assumption that the proposed merged indices have a general ability to accurately estimate foliar Car content. Further examination of the proposed merged indices to estimate foliar Car content of other plant species is desirable to prove the general applicability of the index for non-destructive estimation of Car from leaf reflectance data.
叶片色素含量是植物状态的重要指标，可用于评估植物的活力和光合活性。早期研究已证明，利用从实验室、野外和基于遥感的光谱仪收集的光谱信息，可无损评估高等植物的总叶绿素（Chl）含量。然而，通过无损光谱测量精确估算类胡萝卜素（Car）含量，目前尚未达到与Chl含量估算结果相当的准确度。在此，我们研究了一种最近开发的角度植被指数（AVI）估算三种树种叶片总Car含量的潜力。通过对所有可能波段组合的迭代搜索，我们确定了最佳候选指数AVIcar。所确定的指数与被测树种的Car含量呈现出相当紧密但本质上并非线性的关系，对高Car含量的敏感性增加，而对低Car含量缺乏敏感性，早期提出的植被指数（VI）在低Car含量时表现更好。为利用两种VI类型的优势，我们开发了一种简单的合并程序，将AVIcar与两个早期提出的类胡萝卜素指数相结合。合并后的指数与总Car含量具有紧密的线性关系，且优于所有其他被测指数。合并后的指数能够准确估算总Car含量，百分比均方根误差（%RMSE）为8.12%，决定系数为0.88。我们的研究结果通过使用辐射传输模型PROSPECT - 5的模拟得到了证实。对于模拟数据，合并后的指数再次与Car含量呈现出准线性关系。这强化了这样一种假设，即所提出的合并指数具有准确估算叶片Car含量的一般能力。进一步检验所提出的合并指数以估算其他植物物种的叶片Car含量，对于证明该指数从叶片反射率数据无损估算Car的普遍适用性是很有必要的。
