Summary The allocation of non‐structural carbohydrates (NSCs) to reserves constitutes an important physiological mechanism associated with tree growth and survival. However, procedures for measuringNSCin plant tissue are expensive and time‐consuming. Near‐infrared spectroscopy (NIRS) is a high‐throughput technology that has the potential to infer the concentration of organic constituents for a large number of samples in a rapid and inexpensive way based on empirical calibrations with chemical analysis. The main objectives of this study were (i) to develop a generalNSCconcentration calibration that integrates various forms of variation such as tree species and tissue types and (ii) to identify characteristic spectral regions associated withNSCmolecules. In total, 180 samples from different tree organs (root, stem, branch, leaf) belonging to 73 tree species from tropical and temperate biomes were analysed. Statistical relationships betweenNSCconcentration andNIRSspectra were assessed using partial least squares regression (PLSR) and a variable selection procedure (competitive adaptive reweighted sampling,CARS), in order to identify key wavelengths. Parsimonious and accurate calibration models were obtained for totalNSC(r2of 0·91,RMSEof 1·34% in external validation), followed by starch (r2 = 0·85 andRMSE = 1·20%) and sugars (r2 = 0·82 andRMSE = 1·10%). Key wavelengths coincided among these models and were mainly located in the 1740–1800, 2100–2300 and 2410–2490 nm spectral regions. This study demonstrates the ability of general calibration model to inferNSCconcentrations across species and tissue types in a rapid and cost‐effective way. The estimation ofNSCin plants usingNIRStherefore serves as a tool for functional biodiversity research, in particular for the study of the growth–survival trade‐off and its implications in response to changing environmental conditions, including growth limitation and mortality.
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Ramírez et al. (2015) studied this question.
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