Prediction of oil content in the mesocarp of fruit from the macauba palm using spectrometry

Sofrimento Fenias Savanto Matsimbe, Sergio Yoshimitsui Motoike, Francisco Assis de Carvalho Pinto, Helio Garcia Leite, Gustavo Eduardo Marchatti


In the present work a model was developed for the prediction of the oil content of the mesocarp of fruit from the macauba palm, using visible and near infrared spectrometry. Reference values were determined the by Soxhlet method. The model was calibrated using spectral data from the mesocarp of macauba fruit by partial least squares regression, considering nine latent variables. The results of the calibration series were consistent with those of the validation series, registering an The coefficient of determination between the reference method and the developed model, systematic error between the predicted values and the measured values and root mean square error, for calibration and validation with independent data, respectively, equal to 0.8223, -9.2-14 and 5.917 and 0.7760, 7.081 and -0.064. VIS-NIR spectroscopy is a viable tool in the evaluation of genotypes in breeding programs for the macauba palm.


Acrocomia aculeata; Quantification of the oil; VIS-NIR model calibration

Texto completo:



AMERICAN OIL CHEMIST’ SOCIETY. Official methods and recommended practices of the American Oil Chemist’s Society. Fourth edition. Washington: American Oil Chemist’s Society Press, 1994. Cd 3d-63.

ANALYTICAL SPECTRAL DEVICES Inc. FieldSpec®HandHeld 2™ Spectroradiometer user manual. ASD Document 600860 Rev. D, 92 p. 2011. Disponível em: . Acesso em: 10 set. 2011.

BALBIN, R. M.; SMIRNOV, S. V. Variable selection in near infrared spectroscopy: Benchmarking of feature selection methods on biodiesel data. Analytica Chimica Acta, v. 692, n. 1/2, p. 63-72, 2011.

BAYE, T.; BECKER, H. C. Analyzing seed weight, fatty acid composition, oil, and protein contents in Vernonia galamensis germoplasma by near infrared reflectance spectroscopy. Journal of the American Oil Chemist’s Society, v. 81, n. 7, p. 641-645, 2004.

BLANCO, M. et al. Orthogonal signal correction in near infrared calibration. Analytica Chimica Acta, v. 434, n. 1, p. 125-132, 2001.

BORA, P. S.; ROCHA, R. V. M. Macaíba palm: fatty and amino acids composition of fruits. Ciência Tecnologia & Alimentos, v. 4, n. 3, p. 158-162, 2004.

COCININI, G. Caracterização de frutos e óleo da polpa de macaúba dos biomas do cerrado e pantanal do estado de Mato Grosso do Sul, Brasil. 2012. 128 f. Dissertação (Mestrado em Biotecnologia) - Universidade Católica Dom Bosco, Campo Grande, 2012.

COIMBRA, M. C.; JORGE, N. Characterization of the pulp and kernel oils from Syagrusoleracea, Syagrusromanzoffiana, and Acrocomia aculeata. Journal of Food Science, v. 76, n. 8, p. 1151-1161, 2011.

ELFADL, E. et al. Development of near infrared reflectance spectroscopy (NIRS) calibration model for estimation of oil content in a worldwide Safflower germoplasm collection. International Journal of Plant Production, v. 4, n. 4, p. 259-270, 2010.

FEUDALE, R. N. et al. Transfer of multivariate calibration models: a review. Chemometrics and Intelligent Laboratory Systems, v. 62, n. 2, p. 181-192, 2002.

JIANG, H. Y. et al. Analysis of protein, starch and oil content of single intact kernels by near infrared reflectance spectroscopy (NIRS) in Maize (Zea mays L.). Plant Breeding, v. 126, n. 5, p. 492-497, 2007.

LI, B. et al. Model selection for partial least squares regression. Chemometrics and Intelligent Laboratory Systems, v. 64, n. 1, p. 79-89, 2002.

LIU, F. et al. Variable selection in visible/near infrared spectra for linear and nonlinear calibrations: A case study to determine soluble solids content of beer. Analytica Chimica Acta, v. 634, n. 1, p. 45-52, 2009.

MEVIK, BJORN-HELGE; CEDERKVIST, H.R. Mean Squared Error of Prediction (MSEP) Estimates for Principal Component Regression (PCR) and Partial Least Squares Regression (PLSR). Journal of Chemometrics, v. 18, n. 09, p. 422-429, 2004.

MEVIK, BJORN-HELGE et al. Ensemble methods and partial least squares regression. Journal of Chemometrics, v. 18 n. 11, p. 498-507, 2004.

MOGHIMI, A. et al. Vis/NIR spectroscopy and chemometrics for the prediction of soluble solids content and acidity (pH) of kiwifruit. Biosystems Engineering, v. 106, n. 3, p. 295-302, 2010.

PÉREZ-VICH, B. et al. Determination of seed oil content and fatty acid composition in Sunflower through the analysis of intact seeds, husked seeds, meal and oil by near infrared reflectance spectroscopy. Journal of the American Oil Chemist’s Society, v. 75, n. 5, p. 547-555, 1998.

QUAMPAH, A. et al. Estimation of oil content and fatty acid composition in Cotton seed kernel powder using near infrared reflectance spectroscopy. Journal of the American Oil Chemist’s Society, v. 89, n. 4, p. 567-575, 2012.

R DEVELOPMENT CORE TEAM. R: A language and environment for statistical computing. R Foundation for Statistical Computing, 2012. Disponível em: Acesso em: 10 set. 2012.

ROGGO, Y. et al. Statistical tests for comparison of quantitative and qualitative models developed with near infrared spectral data. Journal of Molecular Structure, v. 654, n. 1/3, p. 253-262, 2003.

ROSSEL, R. A. V. et al. Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soils proprieties. Geoderma, v. 131, n. 1/2, p. 59-75, 2005.

RUDOLPHI, S. et al. Improved estimation of oil linoleic and oleic acid and seed hull fractions in Safflower by NIRS. Journal of the American Oil Chemist’s Society, v. 89, n. 3, p. 363-369, 2012.

SIVAKESAVA, S.; IRUDAYARAJ, J. Rapid determination of tetracycline in milk by FT-MIR and FT-NIR spectroscopy. Journal Dairy Science, v. 85, n. 3, p. 487-493, 2002.

ANDERSON, S. Soxtec: Its principles and applications. AOCS Press, 2004. Chapter 2, 14 p.

SWIERENGA, H. et al. Strategy for constructing robust multivariate calibration models. Chemometrics and Intelligent Laboratory Systems, v. 49, n. 1, p. 1-17, 1999.

VAKNIN, Y. et al. Predicting Jatropha curcas seed-oil content, oil composition and protein content using near infrared spectroscopy - a quick and nondestructive method. Industrial Crops and Products, v. 34, n. 1, p. 1029-1034, 2011.

VELASCO, L. et al. Estimation of seed weight, oil content and fatty acid composition in intact single seeds of rapeseed (Brassica napus L.) by near infrared reflectance spectroscopy. Euphytica, v. 106, n. 1, p. 79-85, 1999a.

VELASCO, L. et al. Development of calibration equations to predict oil content and fatty acid composition in Brassicaceae germoplasm by near infrared reflectance spectroscopy. Journal of the American Oil Chemist’s Society, v. 76, n. 1, p. 25-30, 1999b.

YENIAY, Ö.; GÖKTAS, A. A comparison of partial least squares regression with other prediction methods. Hacettepe Journal of Mathematics and Statistics, v. 31, p. 99-111, 2002.

Revista Ciência Agronômica ISSN 1806-6690 (online) 0045-6888 (impresso), Site:, e-mail: - Fone: (85) 3366.9702 - Expediente: 2ª a 6ª feira - de 7 às 17h.