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Main Authors: Li, Anbang, Liu, Chang, Xing, Ronge, Liu, Song, Li, Kecheng
Format: Artículo científico
Language:en
Published: Carbohydrate research 2026
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Online Access:https://pubmed.ncbi.nlm.nih.gov/41604754/
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author Li, Anbang
Liu, Chang
Xing, Ronge
Liu, Song
Li, Kecheng
author_facet Li, Anbang
Liu, Chang
Xing, Ronge
Liu, Song
Li, Kecheng
Li, Anbang
Liu, Chang
Xing, Ronge
Liu, Song
Li, Kecheng
collection PubMed - marine biology
contents Investigation of monosaccharide colorimetric efficiency by phenol-sulfuric acid method and optimization of quantitative models for polysaccharides. Li, Anbang Liu, Chang Xing, Ronge Liu, Song Li, Kecheng Colorimetry Polysaccharides Monosaccharides Sulfuric Acids Phenol Phenols Phenol-sulfuric acid method, a classical approach for total sugar quantification, suffers from substantial variation in the colorimetric efficiency among different monosaccharides, which may result in significant measurement bias. In this study, we investigated the colorimetric efficiency of 14 monosaccharides across three different systems and found that the colorimetric efficiency followed the pattern: neutral > acidic > amino monosaccharides. Notably, the colorimetric efficiency of mannose was over 800-fold higher than that of glucosamine. Principal coordinate analysis (PCoA) revealed that functional groups (carboxyl, amino) were the major determinants of colorimetric efficiency. Based on these findings, we assessed three quantitative models for five polysaccharides. The traditional model was suitable for homogeneous glucans (e.g., starch, recovery ∼101.0 %). The dominant monosaccharide model was effective for neutral polysaccharides with a single monosaccharide composition (e.g., mannan, recovery ∼100.5 % in the optimized system). In contrast, the weighted model, which integrates molar ratios and individual efficiencies, failed to improve accuracy for complex heterogeneous acidic polysaccharides (e.g., fucoidans, recovery
format Artículo científico
id pubmed_41604754
institution PubMed
language en
publishDate 2026
publisher Carbohydrate research
record_format pubmed
spellingShingle Investigation of monosaccharide colorimetric efficiency by phenol-sulfuric acid method and optimization of quantitative models for polysaccharides.
Li, Anbang
Liu, Chang
Xing, Ronge
Liu, Song
Li, Kecheng
Colorimetry
Polysaccharides
Monosaccharides
Sulfuric Acids
Phenol
Phenols
Investigation of monosaccharide colorimetric efficiency by phenol-sulfuric acid method and optimization of quantitative models for polysaccharides. Li, Anbang Liu, Chang Xing, Ronge Liu, Song Li, Kecheng Colorimetry Polysaccharides Monosaccharides Sulfuric Acids Phenol Phenols Phenol-sulfuric acid method, a classical approach for total sugar quantification, suffers from substantial variation in the colorimetric efficiency among different monosaccharides, which may result in significant measurement bias. In this study, we investigated the colorimetric efficiency of 14 monosaccharides across three different systems and found that the colorimetric efficiency followed the pattern: neutral > acidic > amino monosaccharides. Notably, the colorimetric efficiency of mannose was over 800-fold higher than that of glucosamine. Principal coordinate analysis (PCoA) revealed that functional groups (carboxyl, amino) were the major determinants of colorimetric efficiency. Based on these findings, we assessed three quantitative models for five polysaccharides. The traditional model was suitable for homogeneous glucans (e.g., starch, recovery ∼101.0 %). The dominant monosaccharide model was effective for neutral polysaccharides with a single monosaccharide composition (e.g., mannan, recovery ∼100.5 % in the optimized system). In contrast, the weighted model, which integrates molar ratios and individual efficiencies, failed to improve accuracy for complex heterogeneous acidic polysaccharides (e.g., fucoidans, recovery
title Investigation of monosaccharide colorimetric efficiency by phenol-sulfuric acid method and optimization of quantitative models for polysaccharides.
topic Colorimetry
Polysaccharides
Monosaccharides
Sulfuric Acids
Phenol
Phenols
url https://pubmed.ncbi.nlm.nih.gov/41604754/