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Rapid determination of chemical composition and classification of bamboo fractions using visible–near infrared spectroscopy coupled with multivariate data analysis

Overview of attention for article published in Biotechnology for Biofuels, February 2016
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Title
Rapid determination of chemical composition and classification of bamboo fractions using visible–near infrared spectroscopy coupled with multivariate data analysis
Published in
Biotechnology for Biofuels, February 2016
DOI 10.1186/s13068-016-0443-z
Pubmed ID
Authors

Zhong Yang, Zhong Yang, Kang Li, Maomao Zhang, Donglin Xin, Junhua Zhang

Abstract

During conversion of bamboo into biofuels and chemicals, it is necessary to efficiently predict the chemical composition and digestibility of biomass. However, traditional methods for determination of lignocellulosic biomass composition are expensive and time consuming. In this work, a novel and fast method for quantitative and qualitative analysis of chemical composition and enzymatic digestibilities of juvenile bamboo and mature bamboo fractions (bamboo green, bamboo timber, bamboo yellow, bamboo node, and bamboo branch) using visible-near infrared spectra was evaluated. The developed partial least squares models yielded coefficients of determination in calibration of 0.88, 0.94, and 0.96, for cellulose, xylan, and lignin of bamboo fractions in raw spectra, respectively. After visible-near infrared spectra being pretreated, the corresponding coefficients of determination in calibration yielded by the developed partial least squares models are 0.994, 0.990, and 0.996, respectively. The score plots of principal component analysis of mature bamboo, juvenile bamboo, and different fractions of mature bamboo were obviously distinguished in raw spectra. Based on partial least squares discriminant analysis, the classification accuracies of mature bamboo, juvenile bamboo, and different fractions of bamboo (bamboo green, bamboo timber, bamboo yellow, and bamboo branch) all reached 100 %. In addition, high accuracies of evaluation of the enzymatic digestibilities of bamboo fractions after pretreatment with aqueous ammonia were also observed. The results showed the potential of visible-near infrared spectroscopy in combination with multivariate analysis in efficiently analyzing the chemical composition and hydrolysabilities of lignocellulosic biomass, such as bamboo fractions.

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Brazil 1 2%
Unknown 43 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 27%
Student > Master 7 16%
Student > Bachelor 5 11%
Researcher 5 11%
Professor > Associate Professor 2 4%
Other 5 11%
Unknown 9 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 20%
Chemical Engineering 7 16%
Biochemistry, Genetics and Molecular Biology 3 7%
Environmental Science 2 4%
Energy 2 4%
Other 7 16%
Unknown 15 33%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 February 2016.
All research outputs
#6,189,754
of 7,182,236 outputs
Outputs from Biotechnology for Biofuels
#486
of 570 outputs
Outputs of similar age
#236,367
of 282,785 outputs
Outputs of similar age from Biotechnology for Biofuels
#19
of 19 outputs
Altmetric has tracked 7,182,236 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 570 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.