Lu Shan, Lu Fan, You Wenqiang, Wang Zheyi, Liu Yu, Omasa Kenji
1School of Geographical Sciences, Northeast Normal University, 5268 Renmin Street, Changchun, 130024 China.
2Graduate School of Agricultural and Life Sciences, The University of Tokyo, Yayoi 1-1-1, Bunkyo-ku, Tokyo, 113-8657 Japan.
Plant Methods. 2018 Feb 14;14:15. doi: 10.1186/s13007-018-0281-z. eCollection 2018.
Leaf chlorophyll content (LCC) provides valuable information about plant physiology. Most of the published chlorophyll vegetation indices at the leaf level have been based on the spectral characteristics of the adaxial leaf surface, thus, they are not appropriate for estimating LCC when both the adaxial and abaxial leaf surfaces influence the spectral reflectance. We attempted to address this challenge by measuring the spectral reflectance of the adaxial and abaxial leaf surfaces of several plant species at different growth stages using a portable field spectroradiometer. The relationships between more than 30 published reflectance indices with LCC were analyzed to determine which index estimated LCC most effectively. Additionally, since the relationships determined on one set of samples might have poor predictive performances when applied to other samples, a robust wavelength region is required to render the spectral index generally applicable, regardless of the leaf surface or plant species.
The Modified Datt (MDATT) index, which is the ratio of reflectance difference defined as (R - R)/(R - R), exhibited the strongest correlation (R = 0.856, RMSE = 6.872 μg/cm), with LCC of all the indices tested when all the leaf samples from the adaxial and abaxial surfaces were combined. The optimal wavelength regions, which were derived from the contour maps of R between the MDATT index and LCC for the datasets of one side or both leaf surfaces of each plant species and their intersection, indicated that the red-edge to near-infrared wavelength (723-885 nm) was optimal for λ, while the red-edge region (697-771 nm) was optimal for λ and λ. In these optimal wavelength regions, when the MDATT index was used to estimate LCC, an R higher than 0.8 could be obtained. The correlation of the MDATT index with LCC was the same when the positions of λ and λ were exchanged in the index.
MDATT is proposed as an optimal index for the remote estimation of vegetation chlorophyll content across several plant species in different growth stages when reflectance from both leaf surfaces is considered. The red-edge to near-infrared wavelength (723-885 nm) for λ, as well as the red-edge region (697-771 nm) for λ or λ, are considered to be the most robust for constructing the MDATT index for estimating LCC, regardless of the leaf surface or plant species.
叶片叶绿素含量（LCC）提供了有关植物生理的有价值信息。大多数已发表的叶片水平的叶绿素植被指数都是基于叶片正面的光谱特征，因此，当叶片正面和背面都影响光谱反射率时，它们不适用于估算LCC。我们试图通过使用便携式野外光谱辐射计测量几种植物在不同生长阶段的叶片正面和背面的光谱反射率来应对这一挑战。分析了30多个已发表的反射率指数与LCC之间的关系，以确定哪个指数能最有效地估算LCC。此外，由于在一组样本上确定的关系应用于其他样本时可能具有较差的预测性能，因此需要一个稳健的波长区域以使光谱指数普遍适用，而不受叶片表面或植物种类的影响。
修正的达特（MDATT）指数，即定义为（R - R）/（R - R）的反射率差值之比，在将来自叶片正面和背面的所有叶片样本合并时，与所有测试指数的LCC表现出最强的相关性（R = 0.856，RMSE = 6.872μg/cm）。从每个植物物种叶片一侧或两侧数据集的MDATT指数与LCC之间的R等值线图及其交集得出的最佳波长区域表明，红边到近红外波长（723 - 885nm）对λ是最佳的，而红边区域（697 - 771nm）对λ和λ是最佳的。在这些最佳波长区域中，当使用MDATT指数估算LCC时，可以获得高于0.8的R值。当指数中λ和λ的位置互换时，MDATT指数与LCC的相关性相同。
当考虑叶片两面的反射率时，建议将MDATT作为估算不同生长阶段多种植物植被叶绿素含量的最佳指数。对于构建用于估算LCC的MDATT指数，λ的红边到近红外波长（723 - 885nm）以及λ或λ的红边区域（697 - 771nm）被认为是最稳健的，而不受叶片表面或植物种类的影响。
