## 3 Results
### Multi-Block Analysis
The variables identified as relevant for the SO-PLS-LDA model based on the VIP analysis and those selected by the SO-CovSel-LDA algorithm are graphically compared in Figure 3. In these plots, the relevant predictors in the two blocks are highlighted in red over the corresponding mean spectrum, which is plotted in black. SO-CovSel-LDA has an embedded variable selection step through an algorithm that is specifically designed to provide an extremely parsimonious solution: indeed, only five predictors (two from the MIR and three from the NIR blocks) are selected. On the other hand, the definition of the VIP scores, which are the basis for the identification of the relevant predictors in SO-PLS-LDA, is such that usually, a rather high number of variables is selected. In particular, by adopting the \"greater-than-one\" criterion to establish whether a predictor was significantly contributing to the model or not, VIP analysis identified 920 variables (over 3601) and 730 variables (over 3112) for the MIR and the NIR blocks, respectively. Despite the differences between the two approaches, it is evident from the Figure that they are consistent in terms of the spectral bands identified as relevant for the discrimination between pure and adulterated Senise samples. In fact, as far as the MIR block is concerned, VIP analysis identifies as relevant the intervals of 955-1223 cm\({}^{-1}\) and 2844-2960 cm\({}^{-1}\), while, in the same spectral ranges, SO-CovSel-LDA selects two variables, the peak at 1024 cm\({}^{-1}\) and the one at 2924 cm\({}^{-1}\)  
Figure 3: SO-PLS-LDA: MIR (**a**) and NIR (**b**) variables identified as relevantly contributing to the model based on the value of their variable importance in projection (VIP) score (highlighted in red). Sequential and orthogonalized covariance selection linear discriminant analysis (SO-CovSel-LDA): MIR (**c**) and NIR (**d**) variables selected by the model. In all cases, the mean spectroscopic profiles are displayed as black continuous line. attributable to the C-O-C, C-C and C-O stretching in organic acids and carbohydrates and to the (a) symmetric stretching of CH\({}_{2}\) and CH\({}_{3}\)[33], respectively. The other relevant spectral intervals selected based on the values of the VIP scores are those between 3171 cm\({}^{-1}\) and 3429 cm\({}^{-1}\) ascribable to the O-H stretching, and between 1691 cm\({}^{-1}\) and 1757 cm\({}^{-1}\), probably related to the absorption of the C=O, C=C and the O-H vibrations in phenolic compounds, carotenes and organic acids [33]. For the NIR block, the bands identified as relevant by the VIP analysis of the SO-PLS-LDA model and by SO-CovSel-LDA are highly consistent. In fact, VIP selects the range of 4923-5294 cm\({}^{-1}\) while SO-CovSel-LDA the peak at 4337 cm\({}^{-1}\), probably indicating that moisture could be a suitable parameter to differentiate pure and adulterated Senise samples. Moreover, SO-CovSel-LDA selected the spectral variable at 4007 cm\({}^{-1}\), whereas VIP analysis highlighted as relevant the region between 4000 cm\({}^{-1}\) and 4800 cm\({}^{-1}\), which can be ascribed to sugars in bell peppers [6], suggesting that those compounds could also represent a marker for the identification of the adulteration of Senise bell peppers with paprika.