## 2 Results and Discussion
### Multivariate Analysis
The major metabolites influenced in the volatile metabolic profile of leaf, in decreasing order of contribution, were unknowns (65, 40, 28), 1-pentanol (27), unknown (95), 1-penten-3-ol (19), unknown (81), (Z)-3-hexenyl acetate (57), octanal (58), (Z)-2-penten-1-ol (29), unknown (71), (\(E\))-2-butenal (17), benzeneacetaldehyde (72), unknown (114), 2-ethylfuran (23), ionene (99), hexanoic acid (47), unknown (67), 1-penten-3-one (20), sulfur dioxide (1), 4-oxoisphorone (87), unknown (101), (\(E\))-2-octen-1-ol (76), 1-octanol (77), unknowns (80, 34), (\(E\))-2-pentenal (26), heptanal (41), (\(E\))-2-4-heptadieneal (61), (\(E\))-2-heptenal (44), 5-ethyl-2-(5\(H\))-furanone (45), and 2-ethylthiophene (39). These metabolites can potentially be used as volatile fingerprints to characterize each tissue. For example, butyl acetate which critically contributes to 'Gala' apple aroma, was present in only trichome tissue [43], while \(\alpha\)-terpinol which refers to fragment, floral, and lilac-like in apricot, had a greater concentration in stem tissue [44]. (\(Z\))-3-Hexenyl acetate and 2-ethylfuran were unique metabolites in leaf tissue. (\(Z\))-3-Hexenyl acetate plays an important ecological role in airborne wound signaling in plants [45] and 2-ethylfuran is an indicator for the extent of lipid oxidation [46]. There are also greater concentration of C5 metabolites [1-pentanol, 1-penten-3-ol, (\(Z\))-2-penten-1-ol, (\(E\))-2-pentenal and 1-penten-3-one] in leaf. These are known to be released by wounded leaves of various plants [47]. Alfalfa volatiles have been analyzed before using a number of different techniques to study responses of the plant to pathogens, but these have not used SPME, to the best of our knowledge. Using a vacuum steam distillation method, 16 volatiles, mainly straight chain alcohols, aldehydes, and esters, were identified from leaves of the glandular-haired _M. sativa_ G98A and the nongranular-haired _M. sativa_ Ranger [15]. A push-pull head-space volatile collection system was also used but identified even fewer volatiles from the intact whole _M. sativa_ G98A and Ranger plants [15]. The significantly lower number of volatiles identified using vacuum steam distillation and push-pull methods were probably due to the lack of the volatile enrichment mechanism typically seen SPME methods. This could result if volatiles of low abundances were not detected. For example, all the terpenoids detected in this manuscript were not found in their report [15]. In a different study  
Figure 5: PCA biplot of volatile metabolites originating from glandular trichomes isolated from stems, trichome-free stems, and leaves of alfalfa plants on the basis of 133 volatile metabolites (\(n=4\)); (**A**) score plot showing separation of glandular trichomes, stems, and leaves tissue; (**B**) loading plot showing distribution of 133 volatile metabolites. The score plot illustrates clear differentiation between the volatile metabolic profiles of glandular trichomes, stems, and leaves and the loading plot indicates the contributions of independent volatile metabolites on the separations in the PCA score plot. of _M. sativa_ volatiles, 96 volatile compounds were detected from four alfalfa cultivars and three wild _M. sativa_ species using a supercritical fluid extraction (SFE) with CO\({}_{2}\) as supercritical fluid [48]. This number is close to what we detected from _M. sativa_ leaves using the optimized SPME method (i.e., 99 volatiles detected). However, SFE is more costly and requires specialized equipment. It is also not considered as an optimal method to study volatile profiles as it does not sample volatiles in the head space emitted by samples. Instead, it extracts compounds, including both volatile and nonvolatile compounds, from the samples using supercritical CO\({}_{2}\) fluid as extraction solvents. It is not surprising that different metabolite profiles were obtained using SPME and SFE methods.