Literature DB >> 17904472

Infrared spectroscopy and outer product analysis for quantification of fat, nitrogen, and moisture of cocoa powder.

Anezka Veselá1, António S Barros, Andriy Synytsya, Ivonne Delgadillo, Jana Copíková, Manuel A Coimbra.   

Abstract

The combination of the near infrared (NIR) and Fourier-transform infrared (FTIR) absorbance spectra (1100-2500nm and 4000-600cm(-1)) of 100 cocoa powder samples was used to build calibration models for the determination of the content of fat, nitrogen, and moisture. The samples that comprised the dataset had an average composition of 13.51% of fat, 3.77% nitrogen, and 3.98% moisture. The fat content ranged from 2.42 to 22.00%, the nitrogen from 0.88 to 4.48%, and moisture from 1.60 to 7.80%. For NIR, the relative root mean square error of cross-validation (RMSECV) was 7.0% (R(2)=0.96) for fat, 1.7% (R(2)=0.98) for nitrogen, and 5.2% (R(2)=0.94) for moisture. For FTIR, the relative RMSECV was 10.4% (R(2)=0.94) for fat and 3.9% (R(2)=0.95) for nitrogen. However, for moisture, it was not possible to build a calibration model with suitable predictability. The combination of the NIR and FTIR domains (data fusion) by outer product analysis PLS1 allowed to predict these parameters and to characterise frequencies in one domain based on the information of the other domain. This work allows to conclude that the second derivative of NIR is the recommended procedure to quantify fat, nitrogen, and moisture content in cocoa powders by infrared spectroscopy.

Entities:  

Year:  2007        PMID: 17904472     DOI: 10.1016/j.aca.2007.08.039

Source DB:  PubMed          Journal:  Anal Chim Acta        ISSN: 0003-2670            Impact factor:   6.558


  7 in total

1.  Determination of fat, protein and moisture in ricotta cheese by near infrared spectroscopy and multivariate calibration.

Authors:  Elisângela Serenato Madalozzo; Elenise Sauer; Noemi Nagata
Journal:  J Food Sci Technol       Date:  2013-08-16       Impact factor: 2.701

2.  Classification and compositional characterization of different varieties of cocoa beans by near infrared spectroscopy and multivariate statistical analyses.

Authors:  Douglas Fernandes Barbin; Leonardo Fonseca Maciel; Carlos Henrique Vidigal Bazoni; Margareth da Silva Ribeiro; Rosemary Duarte Sales Carvalho; Eliete da Silva Bispo; Maria da Pureza Spínola Miranda; Elisa Yoko Hirooka
Journal:  J Food Sci Technol       Date:  2018-04-16       Impact factor: 2.701

3.  In situ dynamics of microbial communities during decomposition of wheat, rape, and alfalfa residues.

Authors:  Noémie Pascault; Lauric Cécillon; Olivier Mathieu; Catherine Hénault; Amadou Sarr; Jean Lévêque; Pascal Farcy; Lionel Ranjard; Pierre-Alain Maron
Journal:  Microb Ecol       Date:  2010-07-01       Impact factor: 4.552

4.  Hyperspectral imaging for non-destructive prediction of fermentation index, polyphenol content and antioxidant activity in single cocoa beans.

Authors:  Nicola Caporaso; Martin B Whitworth; Mark S Fowler; Ian D Fisk
Journal:  Food Chem       Date:  2018-03-11       Impact factor: 7.514

5.  Total lipid prediction in single intact cocoa beans by hyperspectral chemical imaging.

Authors:  Nicola Caporaso; Martin B Whitworth; Ian D Fisk
Journal:  Food Chem       Date:  2020-11-19       Impact factor: 7.514

6.  Robust prediction performance of inner quality attributes in intact cocoa beans using near infrared spectroscopy and multivariate analysis.

Authors:  Rita Hayati; Zulfahrizal Zulfahrizal; Agus Arip Munawar
Journal:  Heliyon       Date:  2021-02-24

7.  Data analysis on near infrared spectroscopy as a part of technology adoption for cocoa farmer in Aceh Province, Indonesia.

Authors:  Purwana Satriyo; Agus Arip Munawar
Journal:  Data Brief       Date:  2020-02-06
  7 in total

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