Leaf mass per area (LMA) is an important indicator of plant functioning and photosynthetic capacity and is critical for understanding plant physiology and ecosystem function. Despite detailed and continuous spectral information offered in hyperspectral reflectance, LMA remains a difficult leaf characteristic to be retrieved due to its complex constituents and overlapping absorptions with leaf water. Traditional derivative analysis is commonly used to extract the absorption band positions and to resolve overlapping spectral features, but most cases are only limited to an integral derivative that ignores the asymptotic information between spectral curves. Recent advances in fractional-order derivative (FOD) based analyses, however, have shown their advantages in eliminating background noise as well as in extracting effective information from spectral information. We have thus investigated the potentials of using the fractional derivative indices to retrieve LMA based on a composite dataset consisting of 842 leaf samples from various species. The results demonstrated that the 0.3-order FOD indices provided the highest accuracies to trace LMA and, meanwhile, had the least sensitivity to random noise. Among the ten different index types examined in this study, the SR(1320, 1715) calculated from the 0.3-order derivative spectra had the best performance with an R² of 0.79. Furthermore, the band around 1715 nm was confirmed to be the wavelength with the highest relative absorption of LMA, while the band around 1320 nm was the non-absorbing wavelength for LMA, which could be applied as a base to describe the effects of other leaf constituents. The results of this study revealed the potential of low-order FOD indices to capture LMA and we foresee their wide applications in the future.

单位面积叶质量 (LMA) 是植物功能和光合能力的重要指标，对于了解植物生理学和生态系统功能至关重要。尽管高光谱反射提供了详细和连续的光谱信息，但由于其复杂的成分和与叶水的重叠吸收，LMA 仍然是难以检索的叶特征。传统的导数分析通常用于提取吸收带位置并解决重叠的光谱特征，但大多数情况仅限于忽略光谱曲线之间的渐近信息的积分导数。然而，基于分数阶导数 (FOD) 的分析的最新进展，已经显示出它们在消除背景噪声以及从光谱信息中提取有效信息方面的优势。因此，我们基于由来自不同物种的 842 个叶子样本组成的复合数据集研究了使用分数导数指数检索 LMA 的潜力。结果表明，0.3 阶 FOD 指数为追踪 LMA 提供了最高的准确度，同时对随机噪声的敏感性最低。在本研究检查的十种不同指数类型中，从 0.3 阶导数光谱计算的 SR(1320, 1715) 具有最佳性能，R 结果表明，0.3 阶 FOD 指数为追踪 LMA 提供了最高的准确度，同时对随机噪声的敏感性最低。在本研究检查的十种不同指数类型中，从 0.3 阶导数光谱计算的 SR(1320, 1715) 具有最佳性能，R 结果表明，0.3 阶 FOD 指数为追踪 LMA 提供了最高的准确度，同时对随机噪声的敏感性最低。在本研究检查的十种不同指数类型中，从 0.3 阶导数光谱计算的 SR(1320, 1715) 具有最佳性能，R0.79 中的^2个。此外，1715 nm 附近的波段被证实是 LMA 相对吸收最高的波长，而 1320 nm 附近的波段是 LMA 的非吸收波长，可以作为描述其他叶片效应的基础。成分。这项研究的结果揭示了低阶 FOD 指数捕获 LMA 的潜力，我们预计它们在未来的广泛应用。