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Predictive Analysis of Cocoa Procyanidins Using Near‐Infrared Spectroscopy Techniques
Author(s) -
WHITACRE E.,
LIVER J. O,
BROEK R.,
ENGELEN P.,
REMERS B. K,
HORST B.,
TEWART M. S,
JANSENBEUVINK A.
Publication year - 2003
Publication title -
journal of food science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.772
H-Index - 150
eISSN - 1750-3841
pISSN - 0022-1147
DOI - 10.1111/j.1365-2621.2003.tb05779.x
Subject(s) - theobroma , partial least squares regression , proanthocyanidin , calibration , chemistry , cocoa bean , near infrared spectroscopy , chromatography , chemometrics , analytical chemistry (journal) , fermentation , polyphenol , food science , mathematics , botany , statistics , organic chemistry , biology , neuroscience , antioxidant
A near‐infrared reflectance (NIR) spectroscopy technique for the prediction of procyanidins in cocoa beans ( Theobroma cacao ) has been developed. A select group of cocoa liquors from different origins used for the manufacture of chocolate were analyzed to determine quantitative levels of procyanidin oligomers (monomer to decamer) using normal‐phase high‐performance liquid chromatography. The calibration set included seasonal, environmental, and fermentation variations to cover the concentration range of procyanidins found at naturally occurring levels. The sample set was analyzed on FOSS NIR System II 6500 spectrophotometers and partial least‐squares algorithms developed. Very good calibration statistics were obtained for the prediction of the total procyanidin oligomers ( r 2 = 0.983) with standard deviation/standard error of cross validation ratio (SD/SECV) of 5.68. A global version of this calibration, involving 20 Foss instruments produced a calibration r 2 = 0.98 with a SD/ SECV = 6.20. Procyanidins have attracted increasing attention because of the rapidly growing body of evidence associating these compounds with a wide range of potential health benefits. A rapid method for the analysis of procyanidins in cocoa liquors would be beneficial in quality‐control environments and would provide cost benefits to manufacturing operations.