6533b85efe1ef96bd12c068d

RESEARCH PRODUCT

Classification of persimmon fruit origin by near infrared spectrometry and least squares-support vector machines

Alba Mir-marquésSalvador GarriguesM. De La GuardiaMohammadreza KhanmohammadiA. Bagheri GarmarudiFarshad Karami

subject

business.industryAnalytical chemistryPattern recognitionNear-Infrared SpectrometryMass spectrometryLeast squaresChemometricsSupport vector machinesymbols.namesakeFourier transformTest setPrincipal component analysissymbolsArtificial intelligencebusinessFood ScienceMathematics

description

Abstract The main objective of this work has been the authentication by Fourier transform near infrared (FT-NIR) spectrometry of the origin of persimmon fruits cultivated in different regions of Spain. In order to achieve this goal, 166 persimmon samples from 7 different regions of Spain were analyzed by FT-NIR spectrometry. By splitting the spectral data in training and independent test sets, a classification model was built using least squares support vector machines chemometric technique. Orthogonal signal correction and principal component analysis were performed prior to conduct the classification strategy. The verified model was applied for the prediction of the origin of 50 samples from the independent test set being the prediction error 2%.

yearjournalcountryeditionlanguage
2014-12-01Journal of Food Engineering
https://doi.org/10.1016/j.jfoodeng.2014.06.003