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Chromatographic analysis of major non-structural carbohydrates in several wood species - an analytical approach for higher accuracy of data

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Raessler,  M.
Service Facility Spectrometry, Dr. M. Raessler, Max Planck Institute for Biogeochemistry, Max Planck Society;

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引用

Raessler, M., Wissuwa, B., Breul, A., Unger, W., & Grimm, T. (2010). Chromatographic analysis of major non-structural carbohydrates in several wood species - an analytical approach for higher accuracy of data. Analytical Methods, 2(5), 532-538. doi:10.1039/b9ay00193j.


引用: https://hdl.handle.net/11858/00-001M-0000-000E-DA91-A
要旨
The exact and reliable determination of non-structural carbohydrates (NSC) in wood samples of different origin allows to gain further insight into the biogeochemical carbon cycle, Le. processes that determine how carbon - and carbon dioxide - migrate between the land, the sea and the atmosphere. Plants are an essential part of this cycle using carbon dioxide in photosynthesis and locking up carbon within proteins and carbohydrates. Analytical determination of NSC is complicated by the complexity of the carbohydrate mixtures. However, most of them are present at the trace level only, and do not substantially contribute to the global NSC. Most important are glucose, sucrose, fructose and starch. Traditionally, these carbohydrates are analyzed spectrophotometrically. The spectrophotometric method does not provide any information on concentrations of sugar alcohols and raffinose. They can make up to a quarter of total NSC in deciduous tree samples. Consequently, ignoring them will severely impair the accuracy of NSC data in these samples. We will therefore present a method that allows the reliable determination of the following sugar alcohols and carbohydrates: inositol, sorbitol, mannitol, glucose, fructose, sucrose, raffinose and starch. These were the major contributors to the pool of nonstructural carbohydrates in the samples we examined. It is important to note, that the portion of sugar alcohols and raffinose in the samples ranged from <2-25% of total NSC, irrespective of the plant species, with strongest impact (>= 15% of NSC) for the conifer species "Pine" and the deciduous species "Ash Tree" and "Wild Cherry". Application of our method substantially improved the accuracy of NSC data in these samples if compared to those of the spectrophotometrical analysis.