Literature DB >> 32289426

Pitfalls in the 3, 5-dinitrosalicylic acid (DNS) assay for the reducing sugars: Interference of furfural and 5-hydroxymethylfurfural.

Narendra Naik Deshavath1, Gourab Mukherjee2, Vaibhav V Goud3, Venkata Dasu Veeranki4, Chivukula V Sastri5.   

Abstract

Transformation of renewable biomass into value-added chemicals and biofuels has evolved to be a vital field of research in recent years. Accurate estimation of reducing sugars post pretreatment of lignocellulosic biomass has been very inconsistent. For a few decades, 3,5-dinitrosalicylic acid (DNS) assay has been widely employed for the estimation of reducing sugars derived from pretreatment of lignocellulosic biomass. This assay tests for the presence of free carbonyl group (C=O), the so-called reducing sugars. This involves the oxidation of the aldehyde functional group present to the corresponding acid while DNS is simultaneously reduced to 3-amino-5-nitrosalicylic acid under alkaline conditions. However, the presence of other active carbonyl groups can potentially also react with DNS leading to incorrect yields of reducing sugars. Therefore, a detailed study has been carried out to evaluate the influence of active carbonyl compounds like furfural and 5-hydroxymethylfurfural (5-HMF) in the overall estimation of reducing sugars (glucose, xylose and arabinose) by DNS assay. In addition to this, reducing sugars estimation in the presence of furans were also investigated, it reveals that reducing sugars estimation was found to be 68% higher than actual sugars. Therefore, current findings strongly indicate that the employment of DNS assay for quantifying the reducing sugars in the presence of furans is not appropriate.
Copyright © 2020. Published by Elsevier B.V.

Entities:  

Keywords:  DNS assay; Furans; HPLC; Lignocellulosic biomass; Pretreatment; Reducing sugars

Mesh:

Substances:

Year:  2020        PMID: 32289426     DOI: 10.1016/j.ijbiomac.2020.04.045

Source DB:  PubMed          Journal:  Int J Biol Macromol        ISSN: 0141-8130            Impact factor:   6.953


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