## 3 Results and Discussion
### Multivariate Analysis
All samples with the plant extracts were stacked in one cluster, whereas control sample with high TBARS, hexanal and L* values was stacked in a separate cluster. Moreover, clove-, black seed-, and allspice-treated samples with low lipid/protein oxidation heaped in one cluster different from the rest of treated samples. Allspice and black seed, both with low values of b* coordinates, were stacked in another cluster than cloves showing high b* value. Also bay leaf (with low a* value) was heaped in clusters other than cardamom, caraway, and nutmeg. The lowest Euclidean distance was measured between nutmeg- and caraway-treated samples. These samples were the mostsimilar according to the tested parameters, which disrupted to discriminate them well. The small distance was also noticed between caraway and cardamom samples. GDA is supervised pattern recognition technique enabling obtainment of discriminant functions, which maximize the ratio of between-class variance and minimize the ratio of within-class variance [31]. The first 5 discriminant functions were statistically significant and explained 99.9% of total variance. The first discriminant function accounted for 49.7% of total variance, and the second one for 33.6%. Based on standardized canonical discriminant function coefficients the importance of the independent variables in the canonical function was discussed (Table 6). The higher the absolute value of standardized coefficient the higher the discrimination power of the related variable is. Figure 6: Multivariate analyses: (**a**) Projections of the variables (TBARS—thiobarbituric acid reagent substances, CD—conjugated diene content, SH—thiol group content, hexanal content, L*a*b* color coordinates) onto the factor plane defined by principal components (PC1 and PC2), (**b**) Projections of the scores (samples of raw ground chicken) onto the factor plane (PC1 vs PC2), samples: C—control sample, samples with treatments: A—allspice, BL—bay leaf, BS—black seed, CD—cardamom, CL—cloves, CR—caraway, N—nutmeg, (**c**) Dendrogram of raw ground chicken samples according to CA of similarity, (**d**) GDA classification of raw ground chicken samples. SH content contributed the most to the first canonical function, CD content to the second one, whereas a* parameter to the third one. The discrimination of meat samples with spice extracts was noticeable (Figure 6d). Based on the results it could be concluded that meat samples showing very high oxidative stability of proteins, namely: Clove-, allspice-, and black seed-treated samples, were excellent discriminated with 100% of the classification's propriety. The propriety of classification was also 100% for the samples treated with bay leaf and caraway. Only 2 control samples, 3 samples with nutmeg, and 2 samples with cardamom extracts were incorrectly classified. Summarizing, according to the classification matrix 95.1% of the samples were classified correctly which proved very strong classification ability of the constructed discrimination models. Discriminant functions were successfully used previously to classified samples of raw ground pork with garlic and marjoram according to the fatty acid composition [10].