Journal
FOOD CHEMISTRY
Volume 153, Issue -, Pages 15-19Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.foodchem.2013.12.032
Keywords
Sweet almonds; Bitter almonds; Prunus amygdalus; NIR; Raman; PLS-DA; Classification
Funding
- Spanish Ministry of Science and Technology ['iSens' AGL2011-26456]
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In this study, near-infrared spectroscopy (NIR) coupled to chemometrics is used to develop a fast, simple, non-destructive and robust method for discriminating sweet and bitter almonds (Prunus amygdalus) by the in situ measurement of the kernel surface without any sample pre-treatment. Principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) models were built to discriminate both types of almonds, obtaining high levels of sensitivity and specificity for both classes, with more than 95% of the samples correctly classified and discriminated. Moreover, the almonds were also analysed by Raman spectroscopy, the reference technique for this type of analysis, to validate and confirm the results obtained by NIR. (C) 2013 Elsevier Ltd. All rights reserved.
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