Non-structural carbohydrates in woody plants compared among laboratories

被引:221
作者
Quentin, Audrey G. [1 ,2 ]
Pinkard, Elizabeth A. [1 ]
Ryan, Michael G. [3 ,4 ,5 ]
Tissue, David T. [2 ]
Baggett, L. Scott [5 ]
Adams, Henry D. [6 ]
Maillard, Pascale [7 ]
Marchand, Jacqueline [8 ]
Landhaeusser, Simon M. [9 ]
Lacointe, Andre [10 ,11 ]
Gibon, Yves [12 ,13 ]
Anderegg, William R. L. [14 ]
Asao, Shinichi [3 ,4 ]
Atkin, Owen K. [15 ,16 ]
Bonhomme, Marc [10 ,11 ]
Claye, Caroline [17 ]
Chow, Pak S. [9 ]
Clement-Vidal, Anne [18 ]
Davies, Noel W. [19 ]
Dickman, L. Turin [6 ]
Dumbur, Rita [20 ]
Ellsworth, David S. [2 ]
Falk, Kristen [21 ]
Galiano, Lucia [22 ,23 ]
Grunzweig, Jose M. [20 ]
Hartmann, Henrik [24 ]
Hoch, Guenter [25 ]
Hood, Sharon [26 ]
Jones, Joanna E. [17 ]
Koike, Takayoshi [27 ]
Kuhlmann, Iris [24 ]
Lloret, Francisco [28 ,29 ]
Maestro, Melchor [30 ]
Mansfield, Shawn D. [31 ]
Martinez-Vilalta, Jordi [28 ,29 ]
Maucourt, Mickael [13 ,32 ]
McDowell, Nathan G. [6 ]
Moing, Annick [12 ,13 ]
Muller, Bertrand [33 ]
Nebauer, Sergio G. [34 ]
Niinemets, Ulo [35 ]
Palacio, Sara [30 ]
Piper, Frida [36 ]
Raveh, Eran [37 ]
Richter, Andreas [38 ]
Rolland, Gaelle [33 ]
Rosas, Teresa [28 ]
St Joanis, Brigitte [10 ,11 ]
Sala, Anna [26 ]
Smith, Renee A. [2 ]
机构
[1] CSIRO, Land & Water, Private Bag 12, Hobart, Tas 7001, Australia
[2] Univ Western Sydney, Hawkesbury Inst Environm, Richmond, NSW 2753, Australia
[3] Colorado State Univ, Nat Resources Ecol Lab, Ft Collins, CO 80523 USA
[4] Colorado State Univ, Grad Degree Program Ecol, Ft Collins, CO 80523 USA
[5] USDA Forest Serv, Rocky Mt Res Stn, Ft Collins, CO 80521 USA
[6] Los Alamos Natl Lab, Earth & Environm Sci Div, Los Alamos, NM 87545 USA
[7] Ctr Nancy, INRA, UMR 1137, Ecol & Ecophysiol Forestieres, F-54280 Champenoux, France
[8] Ctr Nancy, INRA, UMR 1137,Plateforme Tech Ecol Fonct OC 081, Ecol & Ecophysi Forest, F-54280 Champenoux, France
[9] Univ Alberta, Dept Renewable Resources, Edmonton, AB T6G 2E3, Canada
[10] INRA, UMR PIAF 0547, F-63100 Clermont Ferrand, France
[11] Univ Blaise Pascal, Univ Clermont Ferrand 2, UMR PIAF 0547, F-6310 Clermont Ferrand, France
[12] Bordeaux Univ, UMR1332, Biol Fruit & Pathol, INRA, F-33140 Villenave Dornon, France
[13] Ctr INRA, Plateforme Metabolome Ctr Genom Fonct Bordeaux, Ctr INRA, MetaboHUB,IBVM, F-33140 Villenave Dornon, France
[14] Princeton Univ, Princeton Environm Inst, Princeton, NJ 08540 USA
[15] Australian Natl Univ, Res Sch Biol, Div Plant Biol, Canberra, ACT 2601, Australia
[16] Australian Natl Univ, ARC Ctr Excellence Plant Energy Biol, Canberra, ACT 2601, Australia
[17] Univ Tasmania, Tasmanian Inst Agr, Sch Land & Food, Hobart, Tas 7001, Australia
[18] CIRAD, UMR AGAP, F-34398 Montpellier, France
[19] Univ Tasmania, Cent Sci Lab, Hobart, Tas 7001, Australia
[20] Hebrew Univ Jerusalem, Robert H Smith Fac Agr Food & Environm, IL-7610001 Rehovot, Israel
[21] Oregon State Univ, Dept Forest Ecosyst & Soc, Corvallis, OR 97331 USA
[22] Swiss Fed Res Inst WSL, CH-8903 Birmensdorf, Switzerland
[23] Univ Freiburg, Inst Hydrol, D-79098 Freiburg, Germany
[24] Max Planck Inst Biogeochem, D-07745 Jena, Germany
[25] Univ Basel, Dept Environm Sci Bot, CH-4056 Basel, Switzerland
[26] Univ Montana, Div Biol Sci, Missoula, MT 59812 USA
[27] Hokkaido Univ, Silviculture & Forest Ecol Studies, Sapporo, Hokkaido 0608589, Japan
[28] CREAF, E-08193 Barcelona, Spain
[29] Univ Autonoma Barcelona, E-08193 Barcelona, Spain
[30] CSIC, IPE, Jaca 22700, Huesca, Spain
[31] Univ British Columbia, Dept Wood Sci, Vancouver, BC V6T 1Z4, Canada
[32] Univ Bordeaux, UMR 1332, Biol Fruit & Pathol, F-33140 Villenave Dornon, France
[33] INRA, UMR LEPSE 759, F-34060 Montpellier, France
[34] Univ Politecn Valencia, Plant Prod Dept, Valencia 46022, Spain
[35] Estonian Univ Life Sci, Dept Plant Physiol, EE-51014 Tartu, Estonia
[36] CIEP, Coyhaique, Chile
[37] Gilat Res Ctr, Inst Plant Sci, Dept Fruit Trees Sci, ARO, IL-85289 Dn Negev, Israel
[38] Univ Vienna, Dept Microbiol & Ecosyst Sci, A-1090 Vienna, Austria
[39] Wageningen Univ, Forest Ecol & Forest Management Grp, NL-6700 AA Wageningen, Netherlands
[40] Univ Western Ontario, Dept Biol, London, ON N6A 5B7, Canada
[41] Tokyo Univ Agr & Technol, Inst Agr, Fuchu, Tokyo 1838509, Japan
[42] Duke Univ, Nicholas Sch Environm, Durham, NC 27708 USA
[43] Univ Peradeniya, Fac Agr, Peradeniya 20400, Sri Lanka
[44] Univ Gothenburg, Dept Earth Sci, S-40530 Gothenburg, Sweden
[45] USDA Forest Serv, Forestry Sci Lab, Corvallis, OR 97331 USA
关键词
extraction and quantification consistency; non-structural carbohydrate chemical analysis; particle size; reference method; soluble sugars; standardization; starch; INDUCED TREE MORTALITY; CARBON LIMITATION; QUANTITATIVE-DETERMINATION; PHOTOSYNTHETIC RESPONSES; STOMATAL CONDUCTANCE; RESOURCE LIMITATION; SEASONAL-CHANGES; WATER-DEFICIT; GAS-EXCHANGE; END-PRODUCTS;
D O I
10.1093/treephys/tpv073
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
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 R-2 = 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.
引用
收藏
页码:1146 / 1165
页数:20
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