2023-04-102023-04-102014-09-20Şahin, S. ve Demir, C. (2016). Determination of antioxidant properties of fruit juice by partial least squares and principal component regression". International Journal of Food Properties, 19(7), 1455-1464.1094-29121532-2386https://doi.org/10.1080/10942912.2014.968791https://www.tandfonline.com/doi/full/10.1080/10942912.2014.968791http://hdl.handle.net/11452/32281The multivariate calibration methods-principal component regression and partial least squares-were employed for the prediction of antioxidant capacities of fruit juices. High-performance liquid chromatography and spectrophotometric approaches were used to determine the antioxidant capacities of fruit juices. The importance of calibration design was investigated by calculating the prediction and validation errors. The influences of using independent validation sets were emphasized. Calibration design is shown to have major effect on principal component regression and partial least squares errors. The models developed on the basis of the mean-centered data were able to predict the total antioxidant activity with a precision comparable to that of the reference [2,2-azino-di-(3-ethylbenzothialozine-sulfonic acid)] method. The partial least squares model seems preferable because of its predictive and describing abilities and good interpretability of the contribution of compounds to the antioxidant capacity. The contribution of individual phenolic compounds to the antioxidant capacity was identified by high-performance liquid chromatography.eninfo:eu-repo/semantics/openAccessFood science & technologyHPLCFruit juiceUV-VIS spectroscopyPCRPLSAntioxidant compoundsCapacityChromatogramsPredictionSpectroscopyCalibrationExtractsAgentsAntioxidantsCalibrationChromatographyForecastingFruit juicesFruitsHigh performance liquid chromatographyLiquid chromatographyPrincipal component analysisRegression analysisUltraviolet visible spectroscopyAnti-oxidant activitiesAntioxidant compoundsMultivariate calibration methodsPartial least square (PLS)Partial least squares modelsPrincipal component regressionUV-vis spectroscopyLeast squares approximationsArticle0003716553000042-s2.0-8496375973614551464197Food science & technologyFragaria; Ribes; Antioxidant