植物落葉の化学組成の分子および抽出ベースの測定における体系的な違い(Systematic Differences in Molecular and Extraction-Based Measures of Plant Litter Chemical Composition)

2024-12-19 パシフィック・ノースウェスト国立研究所(PNNL)

<関連情報>

• https://www.pnnl.gov/publications/systematic-differences-molecular-and-extraction-based-measures-plant-litter-chemical
• https://www.sciencedirect.com/science/article/pii/S0038071724002062?via%3Dihub

近似分析と13C NMR分光法から評価した植物落葉分子多様性の比較 Comparing plant litter molecular diversity assessed from proximate analysis and 13C NMR spectroscopy

Arjun Chakrawal, Björn D. Lindahl, Odeta Qafoku, Stefano Manzoni
Soil Biology and Biochemistry  Available online: 8 July 2024
DOI:https://doi.org/10.1016/j.soilbio.2024.109517

Highlights

• Plant litter molecular diversity is assessed using proximate analysis and ¹³C NMR.
• Use of molecular mixing model to convert NMR spectra to litter macromolecules.
• Proximate fractions correlate with NMR data, but significant uncertainties remain.
• Emphasis on using molecular data to constrain future decomposition models.

Abstract

Accurate representation of the chemical diversity of litter in ecosystem-scale models is critical for improving predictions of decomposition rates and stabilization of plant material into soil organic matter. In this contribution, we conducted a systematic review to evaluate how conventional characterization of plant litter quality using proximate analysis compares with molecular-scale characterization using ¹³C NMR spectroscopy. Using a molecular mixing model, we converted chemical shift regions from NMR into fractions of carbon (C) in five organic compound classes that are major constituents of plant material: carbohydrates, proteins, lignins, lipids, and carbonylic compounds. We found positive correlations between the acid soluble fraction and carbohydrates, and between the acid insoluble fraction and lignins. However, the acid-soluble fraction underestimated carbohydrates, and the acid insoluble fraction overestimated lignins by 243%. We identified two sources of uncertainties: i) disparities between litter chemical composition based on hydrolysability and actual chemical composition obtained from NMR and ii) conversion factors to translate proximate fractions into organic constituents. Both uncertainties are critical, potentially leading to misinterpretations of decay rates in litter decomposition models. Consequently, we recommend including explicit substrate chemistry data in the next generation of litter decomposition models.