Quality Control of Commercial Cocoa Beans (Theobroma cacao L.) by Near-infrared Spectroscopy
This work presents the use of near-infrared (NIR) spectroscopy as a fast and eco-friendly alternative to the conventional methods currently used for the quality control of cocoa beans. A key feature of this study was that the multivariate calibration models were built from the spectra of 81 samples of commercial cocoa beans from different producing regions and sampled over the period of 1 year. This aspect is crucial to demonstrate the feasibility of NIR for predicting chemical parameters of cocoa beans, since it provides a realistic variability in the calibration models. PLS regression models were constructed from the near-infrared diffuse reflectance spectra, allowing the prediction of moisture, pH, acidity, fat, shell content, protein, total phenolic compounds, caffeine, and theobromine through direct analysis of samples milled and sieved without any additional preparation. All of these parameters were predicted with adequate coefficient of determination values (R2), which ranged from 0.67 to 0.89 and relative errors smaller than 10.2%, which is quite suitable when compared to the coefficients of variation of the reference methods. Thus, the results demonstrated that the use of NIR combined with chemometrics is effective and recommended for the quality control of commercial cocoa beans.
KeywordsChemometrics Cocoa beans Cocoa quality Near-infrared (NIR) spectroscopy Partial least squares (PLS) regression
The authors thank FAPESP (São Paulo Research Foundation) and CNPq (Brazilian National Counsel of Technological and Scientific Development) for the financial support.
Compliance with Ethical Standards
Conflict of Interest
Juliana C. Hashimoto declares that she has no conflict of interest. Jéssica C. lima declares that she has no conflict of interest. Renata M. S. Celeghini declares that she has no conflict of interest. Alessandra B. Nogueira declares that she has no conflict of interest. Priscilla Efraim declares that she has no conflict of interest. Ronei J. Poppi declares that he has no conflict of interest. Juliana A. L. Pallone declares that she has no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
- Aculey PC, Snitkjaer P, Owusu M, Bassompiere M, Takrama J, Nørgaard L, Petersen MA, Nielsen DS (2010) Ghanaian cocoa bean fermentation characterized by spectroscopic and chromatographic methods and chemometrics. J Food Sci 75(6):300–307. https://doi.org/10.1111/j.1750-3841.2010.01710.x CrossRefGoogle Scholar
- AOAC (2006) Official methods of analysis of AOAC international, 18th edn. MarylandGoogle Scholar
- Efraim P, Tucci ML, Pezoa-García NH (2006) Phenolic compound content in cocoa seeds from different genotypes. Braz J Food Technol 9:229–236Google Scholar
- Eigenvector Research Inc. (2010) PLS toolbox 5.8. MansonGoogle Scholar
- Fowler MS (2009) Cocoa beans: from tree to factory. In: Beckett ST (ed) Industrial chocolate manufacture and use, 4th edn. Blackwell Publishing, United Kingdom, pp 10–47Google Scholar
- Martens H, Naes T (1989) Multivariate calibration. Spectrochim Acta Mol Biomol Spectrosc 44:287–321Google Scholar
- Sun D-W, Subramanian A, Rodriguez-Saona L (2009) Infrared spectroscopy for food quality analysis and Control. Elsevier /Academic, AmsterdamGoogle Scholar
- The Math Works Inc. (2009) Matlab 7.8. NatickGoogle Scholar
- Wise BM, Gallagher NB, Bro R, et al (2006) PLS_Toolbox version 4.0 for use with MATLAB ™Google Scholar