## 3 Results
### Volatile Compounds of Citrus and Other Nectar Honeys
#### 3.2.5 LDA: Discrimination of Citrus and other Nectar Honeys (Part II)  
For validation of the aforementioned results, and to test the initial model efficacy, MANOVA analysis was applied to the semi-quantitative data of volatile compounds of the 44 citrus and other nectar honeys again, to determine which volatile compounds were now significant concerning discrimination of their geographical origin. In this case, dependent variables included the 42 volatile compounds, since the other nectar honey samples used in the multivariate analysis had some additional characteristic volatile compounds, and the origin of honey samples (citrus honey from Egypt, citrus honey from Morocco, citrus honey from Greece, citrus honey from Spain, and other nectar honeys from Greece) was taken as the independent variable. [PERSON]'s trace = 3.888 (F = 6.773, df = 144, \(p<0.001\)) (with observed power equal to 1.000), and [PERSON] lambda = 0.000 (F = 23.073, df = 144, \(p<0001\)) (with observed power equal to 1.000) index values showed the existence of a significant multivariable effect of citrus and other nectar honeys geographical origin on their volatile composition. Thirty-one of the forty-two volatile compounds (Table 1) were significant (\(p<0.05\)) for geographical origin discrimination of citrus and other nectar honeys. Afterwards, these 31 volatile compounds were subjected to LDA. LDA showed that four statistically significant discriminant functions were formed: Wilks' lambda = 0.000, \(X^{2}=312.976\), df = 100, \(p<0.001\) for the first function; Wilks' Lambda = 0.003, \(X^{2}=165.143\), df = 72, \(p<0.001\) for the second; Wilks' Lambda = 0.027, \(X^{2}=100.793\), df = 46, \(p<0.001\) for the third; and Wilks' Lambda = 0.228, \(X^{2}=41.441\), df = 22, \(p<0.01\) for the fourth. The first discriminant function accounted for 90.8% of the total variance and had the highest eigenvalue (195.319) and canonical correlation (0.997). The second discriminant function had a significantly lower eigenvalue (8.956) and canonical correlation (0.948), while accounting for 4.2% of the total variance. The third discriminant function had a lower eigenvalue (7.329) and canonical correlation (0.938) accounting for 3.4% of the total variance. Finally, the fourth discriminant function had the lowest eigenvalue (3.393) and canonical correlation (0.879) accounting for 1.6% of the total variance. All discriminant functions accounted for 100% of the total variance. During LDA, another important parameter is the tolerance level of the variables (volatile compounds) used for the classification of honey samples according to geographical origin. SPSS software uses a default value of 0.001 as the minimum tolerance level in LDA. The volatile compounds that had a tolerance level value of 0.000 did not pass the tolerance test, and were not included \"a priori\" in the discriminant functions. These volatile compounds were: ethyl malonate, 1-octanol, undecane, benzeneethanol, and benzeneacetonitrile. The group centroid values were: (5.213, \(-\)2.730), (3.774, \(-\)5.606), (6.118, 1.799), (4.390, 2.577), and (\(-\)33.044, 0.258) for honey samples from the specific geographical origin (Figure 4). The total correct classification rate was 97.7% using the original and 77.3% using the cross-validation method, both considered satisfactory classification results. The respective classification rates using the cross-validation method were: 71.4, 66.7%, 70.6%, 87.5%, and 100%, for citrus honey form Egypt, citrus honey from Morocco, citrus honey from Greece, citrus honey from Spain, and other nectar honeys from Greece, respectively. The overall error in each case was 28.6%, 33.3%, 29.4%, 12.5%, and 0%. Regarding the precision of the expanded LDA classification model, from the initial seven citrus honey samples from Egypt five were allocated correctly to Egypt, one to Morocco and one to Greece. In case of citrus honey samples from Morocco, four samples were allocated correctly to Morocco, one to Egypt and one to Greece.