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Principal components analysis (PCA) biplot for EIS raw data from the analyzed orange samples: green triangles represent natural (i.e., unfrozen) samples, and red triangles represent those having experienced a freeze phenomenon.
Partial least squares discriminant analysis (PLS-DA) biplot for EIS raw data from the analyzed orange samples: green crosses represent natural (i.e., unfrozen) samples, and red triangles represent those having experienced a freeze phenomenon.
This study proposes the use of the EIS technique by means of specific equipment and a double-needle sensor to generate electrical signals in the analyzed samples and then classify them using an ANN model. The results of this study show that it is possible to classify oranges depending on whether they have suffered a freeze phenomenon or not by using the described device and the analysis of the data via ANN. The designed model was robust, and it was reliable enough to classify all the samples tested correctly (CCR% = 100%). 2b1af7f3a8