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Estimation of Plant Biomass Lignin Content using Thioglycolic Acid (TGA)
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Mathematical tool from corn stover TGA to determine its composition.

Cesare Freda1, Francesco Zimbardi, Francesco Nanna

  • 1ENEA, UTTRI-BIOM, S.S. Jonica 106 km 419 + 500, 75026 Rotondella, Matera, Italy. cesare.freda@enea.it

Applied Biochemistry and Biotechnology
|June 19, 2012
PubMed
Summary

A new mathematical tool accurately predicts corn stover composition (cellulose, hemicellulose, lignin) using thermogravimetric analysis (TGA) data after steam explosion treatment.

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Area of Science:

  • Biomass valorization and chemical analysis
  • Thermochemical conversion of lignocellulosic materials
  • Agricultural residue utilization

Background:

  • Corn stover is a promising lignocellulosic biomass resource.
  • Understanding its composition (cellulose, hemicellulose, lignin) is crucial for efficient conversion.
  • Traditional analysis methods can be time-consuming.

Purpose of the Study:

  • To develop a mathematical tool for predicting corn stover composition.
  • To utilize thermogravimetric analysis (TGA) data for compositional analysis.
  • To assess the accuracy of the developed tool against wet chemical methods.

Main Methods:

  • Corn stover was treated using steam explosion at various temperatures.
  • Samples were analyzed using wet chemistry for cellulose, hemicellulose, and lignin content.
  • Thermogravimetric analysis (TGA) was performed on treated and extracted samples.
  • A mathematical model was developed using TGA data and biomass degradation temperatures.

Main Results:

  • The developed mathematical tool accurately predicted cellulose, hemicellulose, and lignin content.
  • Average absolute errors were 1.69% for cellulose, 5.59% for hemicellulose, and 0.74% for lignin.
  • The tool demonstrated high accuracy compared to the established wet chemical method.

Conclusions:

  • Thermogravimetric analysis combined with a novel mathematical tool offers a rapid and accurate method for determining corn stover composition.
  • This approach can streamline the analysis of biomass feedstock for thermochemical conversion processes.
  • Steam explosion treatment influences biomass composition, which can be effectively quantified by the developed method.