Stemflow Fluorescence Predicts Lignin Composition and Phenolic Monomer Yield for Trees

茎流荧光预测树木木质素组成和酚类单体产量

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Abstract

Lignin is a promising renewable feedstock to produce chemicals, fuels, and materials, yet a major challenge for lignocellulosic biorefineries is the significant variation in lignin content and structure. Traditional lignin characterization approaches require time-intensive, wet laboratory procedures, highlighting the need for rapid and reliable characterization methods to quantify lignin content and deconstruction products. This study presents a noninvasive, preharvest approach to determine lignin content, total phenolic monomer yield, and syringyl/guaiacyl (S/G) unit ratios in tree biomass from reductive catalytic fractionation (RCF) utilizing the optical properties of stemflow dissolved organic matter (DOM) as a proxy. A significant relationship between fluorescent signatures in stemflow DOM and constituent-specific composition (bark, twigs/branchlets, foliage) is identified, and stepwise multiple linear regression models showcase stemflow DOM component utilization to estimate lignin content, total phenolic monomer yield, and S/G ratio. Unlike traditional approaches, stemflow fluorescence can be quantified preharvest and pretransportation, enabling early lignin screening and prediction of deconstruction performance and product distribution. This stemflow fluorescence approach, harnessing the characterization of DOM in natural processes, is a higher-throughput, lower-cost screening method that could be a critical solution for biorefineries to overcome challenges due to biomass variability and facilitate feedstock screening, process optimization, and output product prediction.

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