**5. Conclusions**

potato, carrot and mango. The β‐carotene distribution was probed using the C=C vibrational peaks at 1520 cm−1, characteristic for β‐carotene. Heterogeneous rod‐shaped bodies with high carotenoid density were identified in sweet potato and carrot, while in mango carotenoid‐filled lipid droplets were identified as homogeneous aggregates. Raman imaging would also be suitable for other types of carotenoids such as lutein and lycopene, since they all have similar vibrational Raman bands at 1500–1535 cm−1 (C=C stretching), at 1145–1165 cm−1 (C–C stretch‐ ing) and at 1000–1010 cm−1 (C–CH3 deformation) [62, 63]. The Raman bands are similar to all carotenoids, but shifted in position according to the number of conjugated bonds, the side groups and to the interaction of carotenoids to other plant constituents. Raman mapping was proved to be useful in evaluating the individual distribution of 7‐, 8‐ and 9‐double bond conjugated carotenoids in the intact tissues of *Calendula officinalis* [63]*.* The Raman images were generated based on the peak at round C=C stretching vibration at 1520 cm−1. This band was shifted at 1536, 1530 and 1524 cm−1 for the 7‐, 8‐ and 9‐conjugated double bond carotenoids,

Roots of different carrot cultivars were screened for their individual carotenoid distribution. The β‐carotene signal at 1520 cm−1 was used for integration. The level of β‐carotene was heterogeneous across root sections of orange, yellow, red and purple carrots. In the secondary phloem, the level of β‐carotene increased gradually from periderm toward the core, but declined fast in cells close to the vascular cambium. Lutein and α‐carotene were deposited in younger cells, while lycopene in red carrots accumulated throughout the whole secondary phloem at the same level [64]. Raman mapping was also applied for studies of *Pelargonium hortorum* to illustrate the heterogeneous distribution of the individual carotenoids in the

Plant polyacetylenes are another class of compounds that can be identified based on their C=C stretching vibration in the 2100–2300 cm−1 range. Using the Raman peaks at 2258 and 2252 cm −1 characteristic to the most common polyacetylenes falcarinol and falcarindiol, Baranska et al*.* [66] showed that polyacetylenes are mainly located in the outer section of the carrot roots. Algae species are important candidates for industrial lipid and biofuel production. Sharma et al*.* [67] used Raman mapping for lipid analysis of microalgae. Characterization of lipid contents in cells obtained by mutagenesis showed that they managed to obtain mutants with increased lipid content. They have generated Raman images of the lipid‐rich, carotenoid‐rich and protein‐rich areas on the *Chlamydomonas reinhardtii* microalgae based on the characteristic

Apart from mutations, the growth media can also induce generation of different metabolites. *Chlorella sorokiniana* and *Neochloris oleoabundans* represent two good candidates for biofuel production. The species were Raman mapped at 532 nm for identification of carotenoid and triglyceride production, and in consequence, the maps were generated based on the signal intensity in the 1505–1535 cm−1 for carotenoids and 2800–3000 cm−1 for triglycerides (CH2 stretching) [68]. Both healthy algae and nitrogen‐starved algae were examined. Only carote‐ noids could be mapped in the healthy cells. The maps showed distinct locations where the carotenoids are concentrated as they are normally located in the chloroplasts. Triglyceride production was observed under nitrogen‐starvation conditions, and it was possible to image

peaks at 1003 cm−1 (proteins), 1445 cm−1 (lipids) and 1520 cm−1 (carotenoids).

respectively.

72 Raman Spectroscopy and Applications

leaves [65].

Raman mapping is a powerful technique for label‐free, noninvasive investigations of tissues, cells and microorganisms. The resulted Raman maps contain not only spatial information but also valuable structural and chemical information on the analyzed samples. Raman imaging has been successfully used for investigations at cellular and subcellular level, including identification of nucleus, nucleoli, mitochondria and lipid‐rich structures. Cell responses to drugs and different stages of the cell cycle from the stem cell to the completely differentiated cell were as well distinguished. In addition, Raman mapping has a great potential for becoming a leading method in a wide range of biomedical applications, owing to its high chemical specificity, good resolution and to the fact that it is a noninvasive to tissues and cells. It is possible to achieve accurate detection of healthy and cancer tissues. At the moment, for the purpose of medical diagnosis, the results of Raman imaging need most often to be compared with currently used diagnosis tools (PCR, histopathology and immunohistopathology). But since it has already been proved that Raman images are sensitive indicators for cancer detection, there is strong indication of the possibility to replace the conventional tools with Raman detection in the future.
