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Application of near-infrared spectroscopy for estimation of non-structural carbohydrates in foliar samples of Eucalyptus globulus Labilladière

Citation

Quentin, AG and Rodemann, T and Doutreleau, M-F and Moreau, M and Davies, NW, Application of near-infrared spectroscopy for estimation of non-structural carbohydrates in foliar samples of Eucalyptus globulus Labilladiere, Tree Physiology: An International Botanical Journal, 37, (1) pp. 131-141. ISSN 0829-318X (2017) [Refereed Article]

DOI: doi:10.1093/treephys/tpw083

Abstract

Near-infrared reflectance spectroscopy (NIRS) is frequently used for the assessment of key nutrients of forage or crops but remains underused in ecological and physiological studies, especially to quantify non-structural carbohydrates. The aim of this study was to develop calibration models to assess the content in soluble sugars (fructose, glucose, sucrose) and starch in foliar material of Eucalyptus globulus. A partial least squares (PLS) regression was used on the sample spectral data and was compared to the contents measured using standard wet chemistry methods. The calibration models were validated using a completely independent set of samples. We used key indicators such as the ratio of prediction to deviation (RPD) and the range error ratio to give an assessment of the performance of the calibration models. Accurate calibration models were obtained for fructose and sucrose content (R2 > 0.85, root mean square error of prediction (RMSEP) of 0.95%–1.26% in the validation models), followed by sucrose and total soluble sugar content (R2 ~ 0.70 and RMSEP > 2.3%). In comparison to the others, calibration of the starch model performed very poorly with RPD = 1.70. This study establishes the ability of the NIRS calibration model to infer soluble sugar content in foliar samples of E. globulus in a rapid and cost-effective way. We suggest a complete redevelopment of the starch analysis using more specific quantification such as an HPLC-based technique to reach higher performance in the starch model. Overall, NIRS could serve as a high-throughput phenotyping tool to study plant response to stress factors.

Item Details

Item Type:Refereed Article
Keywords:calibration model performance, high-throughput phenotyping tool, partial least squares regression, rapid and cost-effective, soluble sugars, starch
Research Division:Biological Sciences
Research Group:Plant Biology
Research Field:Plant Physiology
Objective Division:Plant Production and Plant Primary Products
Objective Group:Forestry
Objective Field:Native Forests
Author:Rodemann, T (Dr Thomas Rodemann)
Author:Davies, NW (Associate Professor Noel Davies)
ID Code:119055
Year Published:2017
Deposited By:Central Science Laboratory
Deposited On:2017-07-25
Last Modified:2017-07-25
Downloads:0

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