The knowledge of leaf biochemical traits is significant to understand the plant growth and physiological status. Spectral indices have been widely used to assess leaf biochemical traits, while the estimation accuracies at canopy level are frequently lower compared to those at leaf level in part due to the complexity of canopy structures and the variations in optical properties between leaf adaxial and abaxial surfaces. This study thus improved spectral indices with minimizing the effect of the difference between leaf adaxial and abaxial surfaces to assess leaf biochemical traits from leaf to canopy level. The datasets including leaf reflectance and canopy reflectance with corresponding leaf chlorophyll content (C_ab), water content (C_w), and dry matter content (C_m) from a wide range of plant species were used. Results showed that there existed a significant difference between leaf abaxial and abaxial reflectance, causing the variation in the relationship between leaf biochemical traits and spectral indices. The published spectral indices exhibited the strong relationships with C_ab, C_w, and C_m for either leaf adaxial or abaxial data, while the relationships of spectral indices with C_ab, C_w, and C_m from leaf adaxial reflectance were inconsistent with those from leaf abaxial reflectance. The proposed adjusted ratio of difference spectral index (ARDSI) minimized the difference between leaf adaxial and abaxial reflectance for assessing C_ab, C_w, and C_m at leaf level with the root mean square error of 9.32 μg cm^-2, 0.0050 g cm^-2, and 0.0053 g cm^-2, respectively. The application of the proposed ARDSI to the canopy level alleviated the effect of the variations of leaf adaxial and abaxial reflectance difference and canopy structures on the estimation of leaf biochemical traits, which thus improved the assessment of C_ab, C_w, and C_m at canopy level in the simulated and measured datasets. The proposed approach would advance the applicability of spectral indices to monitor the physiological and functional traits of field crops at different scales.

叶片生化性状的知识对于了解植物的生长和生理状态具有重要意义。光谱指数已被广泛用于评估叶片生化性状，而冠层水平的估计精度通常低于叶片水平，部分原因是冠层结构的复杂性以及叶片正反面之间光学特性的变化。因此，这项研究改进了光谱指数，同时最大限度地减少了叶片正面和背面之间差异的影响，以评估从叶片到冠层水平的叶片生化性状。数据集包括叶子反射率和冠层反射率以及相应的叶子叶绿素含量 ( C _ab )、水分含量 ( C _w) 和来自广泛植物物种的干物质含量 ( C _m )。结果表明，叶片背面和背面反射率存在显着差异，导致叶片生化性状与光谱指标的关系发生变化。公布的光谱指数表现出与牢固的关系Ç _AB，Ç_瓦特，和Ç_米为任一叶正面或背面数据，而谱指数与关系Ç _AB，Ç_瓦特，和Ç_米叶片正面反射率与叶片背面反射率不一致。建议的调整后的差异光谱指数比 (ARDSI) 将叶片正面和背面反射率之间的差异最小化，以评估叶片水平的C _ab、C _w和C _m，均方根误差为 9.32 μg cm ^-2、0.0050 g cm ^-2和 0.0053 g cm ^-2，分别。所提出的ARDSI到罩盖的水平中的应用减轻关于叶生化性状的推定，这从而提高了的评估叶近轴和远轴反射率差和冠层结构的变化的影响Ç _AB、C _w和C _m在模拟和测量数据集中的冠层水平。所提出的方法将提高光谱指数在不同尺度上监测大田作物生理和功能性状的适用性。