Standardized protocols and procedures can precisely and accurately quantify non-structural carbohydrates
- Department of Renewable Resources, University of Alberta, Edmonton, Alberta, Canada
- Los Alamos National Laboratory, Earth and Environmental Sciences, Los Alamos, NM, USA
- Harvard University, Department of Organismic and Evolutionary Biology, 26 Oxford Street, Cambridge, MA, USA
- Max Planck Institute for Biogeochemistry, Hans-Knöll Str. 10, Jena, Germany
- Department of Environmental Sciences - Botany, University of Basel, Schönbeinstrasse 6, Basel, Switzerland
- University of Vienna, Department of Microbiology and Ecosystem Science, Althanstraße 14, Vienna, Austria
- Stockholm University, Department of Environmental Science and Analytical Chemistry, Stockholm, Sweden; University of Gothenburg, Department of Earth Sciences, Guldhedsgatan 5 A, Gothenburg, Sweden
- Pacific Northwest National Lab, Richland, WA, USA
- Harvard University, Department of Organismic and Evolutionary Biology, 26 Oxford Street, Cambridge, MA, USA; Northern Arizona University, Center for Ecosystem Science and Society and School of Informatics, Computing and Cyber Systems, Flagstaff, AZ, USA
- Oklahoma State University, Department of Plant Biology, Ecology, and Evolution, 301 Physical Sciences, Stillwater, OK, USA
Non-structural carbohydrates (NSCs), the stored products of photosynthesis, building blocks for growth, and fuel for respiration, are central to plant metabolism, but their measurement is challenging. Differences in methods and procedures among laboratories can cause results to vary widely, limiting our ability to integrate and generalize patterns in plant C balance among studies. A recent assessment found that NSC concentrations measured for a common set of samples can vary by an order of magnitude, but sources for this variability were unclear. We measured a common set of nine plant material types, and two synthetic samples with known NSC concentrations, using a common protocol for sugar extraction and starch digestion, and three different sugar quantification methods (ion chromatography, enzyme, acid) in six laboratories. We also tested how sample handling, extraction solvent, and centralizing parts of the procedure in one laboratory affected results. NSC concentrations measured for synthetic samples were within about 11.5% of known values for all three methods. However, differences among quantification methods were the largest source of variation in NSC measurements for natural plant samples because the three methods quantify different NSCs. The enzyme method quantified only glucose, fructose, and sucrose, with ion chromatography we additionally quantified galactose, while the acid method quantified a large range of mono- and oligosaccharides. For some natural samples, acid method quantification doubled sugar relative to the other methods, demonstrating that trees allocate C to a range of sugar molecules. Sample handling had little effect on measurements, while ethanol sugar extraction improved accuracy over water extraction. Our results demonstrate that reasonable accuracy of NSC measurements can be achieved when different methods are used, as long as protocols are robust and standardized. Thus, we provide detailed protocols for the extraction, digestion and quantification of NSCs in plant samples, which should improve the comparability of NSC measurements among laboratories.
- Research Organization:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-76RL01830
- OSTI ID:
- 1497013
- Report Number(s):
- PNNL-SA-134735
- Journal Information:
- Tree Physiology (Online), Vol. 38, Issue 12; ISSN 1758-4469
- Publisher:
- Oxford University Press
- Country of Publication:
- United States
- Language:
- English
Similar Records
Carbohydrate signatures of aquatic macrophytes and their dissolved degradation products as determined by a sensitive high-performance ion chromatography method
Automated “Cells-To-Peptides” Sample Preparation Workflow for High-Throughput, Quantitative Proteomic Assays of Microbes