Non-structural carbohydrates in woody plants compared among laboratories

Audrey G. Quentin*, Elizabeth A. Pinkard, Michael G. Ryan, David T. Tissue, L. Scott Baggett, Henry D. Adams, Pascale Maillard, Jacqueline Marchand, Simon M. Landhäusser, André Lacointe, Yves Gibon, William R.L. Anderegg, Shinichi Asao, Owen K. Atkin, Marc Bonhomme, Caroline Claye, Pak S. Chow, Anne Clément-Vidal, Noel W. Davies, L. Turin DickmanRita Dumbur, David S. Ellsworth, Kristen Falk, Lucía Galiano, José M. Grünzweig, Henrik Hartmann, Günter Hoch, Sharon Hood, Joanna E. Jones, Takayoshi Koike, Iris Kuhlmann, Francisco Lloret, Melchor Maestro, Shawn D. Mansfield, Jordi Martínez-Vilalta, Mickael Maucourt, Nathan G. McDowell, Annick Moing, Bertrand Muller, Sergio G. Nebauer, Ülo Niinemets, Sara Palacio, Frida Piper, Eran Raveh, Andreas Richter, Gaëlle Rolland, Teresa Rosas, Brigitte Saint Joanis, Anna Sala, Renee A. Smith, Frank Sterck, Joseph R. Stinziano, Mari Tobias, Faride Unda, Makoto Watanabe, Danielle A. Way, Lasantha K. Weerasinghe, Birgit Wild, Erin Wiley, David R. Woodruff

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

194 Scopus citations


Non-structural carbohydrates (NSC) in plant tissue are frequently quantified to make inferences about plant responses to environmental conditions. Laboratories publishing estimates of NSC of woody plants use many different methods to evaluate NSC. We asked whether NSC estimates in the recent literature could be quantitatively compared among studies. We also asked whether any differences among laboratories were related to the extraction and quantification methods used to determine starch and sugar concentrations. These questions were addressed by sending sub-samples collected from five woody plant tissues, which varied in NSC content and chemical composition, to 29 laboratories. Each laboratory analyzed the samples with their laboratory-specific protocols, based on recent publications, to determine concentrations of soluble sugars, starch and their sum, total NSC. Laboratory estimates differed substantially for all samples. For example, estimates for Eucalyptus globulus leaves (EGL) varied from 23 to 116 (mean = 56) mg g-1 for soluble sugars, 6-533 (mean = 94) mg g-1 for starch and 53-649 (mean = 153) mg g-1 for total NSC. Mixed model analysis of variance showed that much of the variability among laboratories was unrelated to the categories we used for extraction and quantification methods (method category R2 = 0.05-0.12 for soluble sugars, 0.10-0.33 for starch and 0.01-0.09 for total NSC). For EGL, the difference between the highest and lowest least squares means for categories in the mixed model analysis was 33 mg g-1 for total NSC, compared with the range of laboratory estimates of 596 mg g-1. Laboratories were reasonably consistent in their ranks of estimates among tissues for starch (r = 0.41-0.91), but less so for total NSC (r = 0.45-0.84) and soluble sugars (r = 0.11-0.83). Our results show that NSC estimates for woody plant tissues cannot be compared among laboratories. The relative changes in NSC between treatments measured within a laboratory may be comparable within and between laboratories, especially for starch. To obtain comparable NSC estimates, we suggest that users can either adopt the reference method given in this publication, or report estimates for a portion of samples using the reference method, and report estimates for a standard reference material. Researchers interested in NSC estimates should work to identify and adopt standard methods.

Original languageAmerican English
Pages (from-to)1146-1165
Number of pages20
JournalTree Physiology
Issue number11
StatePublished - 2015

Bibliographical note

Publisher Copyright:
© The Author 2015.


  • Extraction and quantification consistency
  • Non-structural carbohydrate chemical analysis
  • Particle size
  • Reference method
  • Soluble sugars
  • Standardization
  • Starch


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