Near-infrared reflectance spectroscopy as a fast and non-destructive tool to predict foliar organic constituents of several woody species

Abstract

Near-infrared reflectance spectroscopy (NIRS) was used to estimate N, neutral detergent fibre (NDF), acid detergent fibre (ADF), lignin and cellulose contents in leaves of a heterogeneous group of 17 woody species from the Central Western region of the Iberian Peninsula. The sample set consisted of 182 samples of leaves of deciduous and evergreen species, showing a wide range of concentrations determined by reference methods: 6.60-35.2 g kg-1 (N), 15.5-66.0% (NDF), 10.2-57.3% (ADF), 3.45-27.4% (lignin) and 5.79-31.3% (cellulose). Reflectance spectra, obtained for samples of dried and ground leaves, were recorded as log1/R (R=reflectance) from 1,100 to 2,500 nm. NIRS calibrations were developed using multiple linear (MLR) and partial least-squares (PLSR) regressions, and tested by external validation. Spectral data were transformed to the first and second derivative (1D, 2D). The PLSR method and derivative transformations provided the best statistics and showed lower standard errors of calibration (SEC) and higher coefficients of multiple determination (R2). In the external validation the standard errors of prediction (SEP) were 0.76 g kg-1 (N), 2.11% (NDF), 1.47% (ADF), 0.85% (lignin) and 0.86% (cellulose). The results obtained show that NIRS is very effective for the estimation of these organic constituents in leaf tissue of woody species. This technique can be used in ecological or ecophysiological studies as an alternative to the more time-consuming standard methods.

Leaf optical properties reflect variation in photosynthetic metabolism and its sensitivity to temperature

“…Recently, spectroscopic data combined with PLSR modelling has been used to estimate levels of various other leaf biochemical and nutritional constituents (Gillon et al , 1999; Richardson and Reeves, 2005; Petisco et al , 2006). For example, Asner and Martin (2008) found that spectroscopy could be used to estimate leaf concentrations of chlorophylls (i.e.…”

“…Thus far, target foliar traits have included concentrations of nitrogen ( N mass , Bolster et al , 1996; Gillon et al , 1999), lignin, cellulose (Wessman et al , 1988 a ; Martin and Aber, 1997; Kokaly and Clark, 1999; Petisco et al , 2006), and photosynthetic pigments (Richardson et al , 2002; Gitelson et al , 2003; Moorthy et al , 2008) as well as water content (Sims and Gamon, 2003; Stimson et al , 2005; Cheng et al , 2008). In addition, leaf isotopic ratios (δ 13 C and δ 15 N; Richardson and Reeves, 2005; Wang et al , 2007; Kleinebecker et al , 2009), specific leaf area (SLA; Asner and Martin, 2008), and leaf mass per area (LMA; Asner et al , 2011; Doughty et al , 2011) have been successfully estimated using leaf optical properties.…”

On the challenges of using field spectroscopy to measure the impact of soil type on leaf traits

“…The spectral reflectance values of each sample were transformed into pseudo-absorption values; that is, log [1/R]) where R is reflectance (see Bolster et al, 1996;Gillon et al, 1999;Richardson and Reeves III, 2005;Petisco et al, 2006;Kleinebecker et al, 2009). There is strong autocorrelation in pseudo-absorption values, so PLSR involves dimensionality reduction, producing orthogonal uncorrelated latent vectors containing the maximum explanatory power in relation to the trait data (Wold et al, 2001).…”

Use of near-infrared reflectance spectroscopy to predict species composition in tree fine-root mixtures

“…To test and select a truly robust NIRS model, a large and diverse external independent validation sample set is necessary (Martens and Dardenne 1998;Petisco et al 2006;Richardson and Reeves 2005). In this study, 132 sample spectra were set aside as external, independent validation set, which was not included in either of the calibration and test validation, but contained, at least in part, some of the original pure root material.…”