All fresh-leaf spectral data are available through the CABO data portal (https://data.caboscience.org/leaf).
Open resource ↗CABO data portal · pdf-page:24 lines:1-32Unverified paper record
Reflectance spectroscopy allows rapid, accurate, and non-destructive estimates of functional traits from pressed leaves
bioRxiv · 20 Apr 2022 · 10.1101/2021.04.21.440856
Abstract
O_LIMore than ever, ecologists seek to employ herbarium collections to estimate plant functional traits from the past and across biomes. However, many trait measurements are destructive, which may preclude their use on valuable specimens. Researchers increasingly use reflectance spectroscopy to estimate traits from fresh or ground leaves, and to delimit or identify taxa. Here, we extend this body of work to non-destructive measurements on pressed, intact leaves, like those in herbarium collections. C_LIO_LIUsing 618 samples from 68 species, we used partial least-squares regression to build models linking pressed-leaf reflectance spectra to a broad suite of traits, including leaf mass per area (LMA), leaf dry matter content (LDMC), equivalent water thickness, carbon fractions, pigments, and twelve elements. We compared these models to those trained on fresh- or ground-leaf spectra of the same samples. C_LIO_LIOur pressed-leaf models were best at estimating LMA (R2 = 0.932; %RMSE = 6.56), C (R2 = 0.855; %RMSE = 9.03), and cellulose (R2 = 0.803; %RMSE = 12.2), followed by water-related traits, certain nutrients (Ca, Mg, N, and P), other carbon fractions, and pigments (all R2 = 0.514-0.790; %RMSE = 12.8-19.6). Remaining elements were predicted poorly (R2 20). For most chemical traits, pressed-leaf models performed better than fresh-leaf models, but worse than ground-leaf models. Pressed-leaf models were worse than fresh-leaf models for estimating LMA and LDMC, but better than ground-leaf models for LMA. Finally, in a subset of samples, we used partial least-squares discriminant analysis to classify specimens among 10 species with near-perfect accuracy (>97%) from pressed- and ground-leaf spectra, and slightly lower accuracy (>93%) from fresh-leaf spectra. C_LIO_LIThese results show that applying spectroscopy to pressed leaves is a promising way to estimate leaf functional traits and identify species without destructive analysis. Pressed-leaf spectra might combine advantages of fresh and ground leaves: like fresh leaves, they retain some of the spectral expression of leaf structure; but like ground leaves, they circumvent the masking effect of water absorption. Our study has far-reaching implications for capturing the wide range of functional and taxonomic information in the worlds preserved plant collections. C_LI
Plant phenotyping relevance
押葉の反射分光から葉の機能形質を非破壊推定する手法を開発・比較検証しており、植物形質取得が研究の中心である。
abstractwe used partial least-squares regression to build models linking pressed-leaf reflectance spectra to a broad suite of traits
abstractThese results show that applying spectroscopy to pressed leaves is a promising way to estimate leaf functional traits
Code and data availability
The paper's fresh-leaf spectral dataset is publicly available via the CABO data portal. Pressed/ground spectra, trait data, and PLSR/PLS-DA models are only promised 'upon publication' to EcoSIS and EcoSML, so those require contacting the authors; no author analysis code with a public URL is stated.
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