2018
DOI: 10.1016/j.chemolab.2018.02.004
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Classification of 1-methylcyclopropene treated apples by fluorescence fingerprint using partial least squares discriminant analysis with stepwise selectivity ratio variable selection method

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Cited by 12 publications
(2 citation statements)
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“…Two analyses were done, the first one with markers at baseline and the second one with the variations of the markers after treatment (Δ: POST minus PRE values). PLS-DA can handle both, multicollinearity problem and datasets with the number of variables higher than that of samples [24]. To choose the optimal number of variables for each PLS-DA, we use the estimation of the misclassification error rate using leave-one-out or stratified cross-validation [23].…”
Section: Discussionmentioning
confidence: 99%
“…Two analyses were done, the first one with markers at baseline and the second one with the variations of the markers after treatment (Δ: POST minus PRE values). PLS-DA can handle both, multicollinearity problem and datasets with the number of variables higher than that of samples [24]. To choose the optimal number of variables for each PLS-DA, we use the estimation of the misclassification error rate using leave-one-out or stratified cross-validation [23].…”
Section: Discussionmentioning
confidence: 99%
“…The advantage of the FF technique over conventional fluorescence spectroscopy is that it includes the signals of many fluorescent constituents existing in the sample. Many studies using the FF technique to evaluate various food stuffs, such as olive oil (Guimet et al 2006), beer (Sikorska et al 2008), cheese (M. Kokawa et al 2015), soymilk (Mito Kokawa et al 2017, and apples (Trivittayasil et al 2018), have been reported. Trivittayasil et al (2017) reported that a model for estimating the active oxygen-scavenging ability of peach extract was constructed from the fluorescence patterns of epicatechin and procyanidin (Trivittayasil et al 2017).…”
Section: Introductionmentioning
confidence: 99%