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Determination of amylose content in starch using Raman spectroscopy and multivariate calibration analysis

Almeida, Mariana R. ; Alves, Rafael S. ; Nascimbem, Laura B. L. R. ; Stephani, Rodrigo ; Poppi, Ronei J. ; de Oliveira, Luiz Fernando C.

Analytical and bioanalytical chemistry, 2010-08, Vol.397 (7), p.2693-2701 [Periódico revisado por pares]

Berlin/Heidelberg: Springer-Verlag

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Título:
Determination of amylose content in starch using Raman spectroscopy and multivariate calibration analysis
Autor: Almeida, Mariana R. ; Alves, Rafael S. ; Nascimbem, Laura B. L. R. ; Stephani, Rodrigo ; Poppi, Ronei J. ; de Oliveira, Luiz Fernando C.
Assuntos: Amylose - analysis ; Analysis ; Analytical Chemistry ; Biochemistry ; Calibration ; Characterization and Evaluation of Materials ; Chemistry ; Chemistry and Materials Science ; Food Industry - standards ; Food Science ; Laboratory Medicine ; Manihot - chemistry ; Mathematical analysis ; Monitoring/Environmental Analysis ; Multivariate Analysis ; Original Paper ; Principal Component Analysis ; Quality Control ; Raman spectroscopy ; Spectrum Analysis, Raman - methods ; Starch - analysis ; Starches ; Zea mays - chemistry
É parte de: Analytical and bioanalytical chemistry, 2010-08, Vol.397 (7), p.2693-2701
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
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Descrição: Fourier transform Raman spectroscopy and chemometric tools have been used for exploratory analysis of pure corn and cassava starch samples and mixtures of both starches, as well as for the quantification of amylose content in corn and cassava starch samples. The exploratory analysis using principal component analysis shows that two natural groups of similar samples can be obtained, according to the amylose content, and consequently the botanical origins. The Raman band at 480 cm −1 , assigned to the ring vibration of starches, has the major contribution to the separation of the corn and cassava starch samples. This region was used as a marker to identify the presence of starch in different samples, as well as to characterize amylose and amylopectin. Two calibration models were developed based on partial least squares regression involving pure corn and cassava, and a third model with both starch samples was also built; the results were compared with the results of the standard colorimetric method. The samples were separated into two groups of calibration and validation by employing the Kennard-Stone algorithm and the optimum number of latent variables was chosen by the root mean square error of cross-validation obtained from the calibration set by internal validation (leave one out). The performance of each model was evaluated by the root mean square errors of calibration and prediction, and the results obtained indicate that Fourier transform Raman spectroscopy can be used for rapid determination of apparent amylose in starch samples with prediction errors similar to those of the standard method. Figure Raman spectroscopy has been successfully applied to the determination of the amylose content in cassava and corn starches by means of multivariate calibration analysis.
Editor: Berlin/Heidelberg: Springer-Verlag
Idioma: Inglês

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Determination of amylose content in starch using Raman spectroscopy and multivariate calibration analysis

Almeida, Mariana R. ; Alves, Rafael S. ; Nascimbem, Laura B. L. R. ; Stephani, Rodrigo ; Poppi, Ronei J. ; de Oliveira, Luiz Fernando C.

Berlin/Heidelberg: Springer-Verlag

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