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Rapid Prediction of Extractives and Polyphenolic Contents in Pinus caribaea Bark Using Near Infrared Reflectance Spectroscopy
Benjamin Adu-Amankwa, Nicholas Albert Darkwa, Daniel Sekyere
Pages - 1 - 11     |    Revised - 31-03-2011     |    Published - 04-04-2011
Volume - 2   Issue - 1    |    Publication Date - March / April 2011  Table of Contents
Folin-Ciocalteu Assay, Chemometric Modeling, Soxhlet Extraction, First Derivative Spectra, Spectroscopy
The potential of near infrared reflectance spectroscopy (NIRS) for rapidly and accurately determining the extractives and polyphenol contents in Pinus caribaea bark extracts was assessed. Pinus caribaea bark samples were obtained from 110 trees in plantation stands at different locations of Ghana and were then scanned by NIRS. Their extractives and polyphenol contents reference values were obtained by TAPPI T204 om-88 and Folin-Ciocalteu methods respectively. These reference values were regressed against different spectral transformations using partial least square (PLS) regression. First derivative transformation equation of the raw spectral data, resulted in a coefficient of determination r2 in the external validation of 0.91 and 0.97 respectively for extractives content and polyphenol content. The calibration samples covered a wide range of extractives content from 34 – 45% and polyphenolic content from 16 – 23.5%. The standard deviation to root mean square error of cross validation ratio (SD/RMSECV), root mean square error of calibration to standard deviation ratio (RMSEC/SD), RMSECV/RMSEC and r2 for both extractives and polyphenol models were indicative of good prediction equations. The predicted values were thus highly correlated with time-consuming wet chemical measured values of extractives content and polyphenol content. The use of NIRS for the determination of the extractives and polyphenol contents in Pinus caribaea bark thus provides an advantage of time saving and cost of analysis.
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Dr. Benjamin Adu-Amankwa
Kwame Nkrumah University of Science and Technology - Ghana
Associate Professor Nicholas Albert Darkwa
Kwame Nkrumah University of Science and Technology - Ghana
Dr. Daniel Sekyere
CSIR-Forestry Research Institute of Ghana - Ghana

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