**4. Conclusions**

characteristic MS spectrum of carotenoids and the search in databases on the Internet is helpful for interpretation, but they should be applied with caution considering the instrumental configuration and conditions for acquisition of the MS that were used in the references, to avoid confusing or incorrect identification. The use of experimental data from authentic standards analyzed with the same MS acquisition settings used for the sample, as well as any

The implementation of software tools to assist in the production of a positive list of identified compounds in sample is one of the significant advances that has been introduced in the capabilities of MS. The analysis of MS spectra for the identification of the molecular/protonated molecular ions, the application of filtering rules based on the mass accuracy error and isotopic pattern, and the study of product ions in tandem MS means an intensive manual labor that could be released with the aid of suitable software. These tools may be embedded as a module or option in the main software distributed with the MS instrument, or may be available to download from the Internet. Different software utilities are designed to resolve each of the steps that lead to

complementary source of data should be considered a golden rule for identification.

obtain the correct elemental composition and to establish the main structural features.

To achieve that aim, the application of filtering rules to the measured mass, regarding the mass error and isotopic pattern distribution, is the main approach to constrain the number of possible candidate structures. Thus, for a given molecular/protonated molecular ion with an experimentally measured *m/z* value, a set of elemental compositions is possible (see Section 3.1.3 and **Figure 2**). Increasing the mass accuracy, the number of potential candidates is reduced. The software tools to perform this first screening automatically, the operator should only establish the mass error value to allow an elemental composition to enter in the positive list or to be excluded. The second filtering rule involves isotopic pattern. The software tools compare the isotopic distribution of the experimental *m/z* value with the theoretical ones of the potential candidates that fulfilled the first filter (mass error) yielding a correlation value for each candidate. The operator should only establish the threshold for that correlation value that makes an elemental composition to pass this second screening. Free software to complete both screening steps is available on the Internet (http://tarc.chemistry.dal.ca/soft\_down.htm; https://omics.pnl. gov/software/molecular-weight-calculator). Regarding the evaluation of data from tandem MS spectra, the same programs may apply to each of the characteristic product ions. The filtering rules process should be reliably accomplished, both in the parent compound and in its product ions. Thus, the consistency of the elemental composition and isotopic pattern of the product ions with the structural features of their parent compound is assured [91, 92]. To perform this step and the subsequent study of the contribution of each characteristic product ion to the structure of the molecular/protonated molecular ion, we should be able to predict product ions from the candidate structures ascertained in the first screening process. As it was noted in Section 3.2.1, the product ions generated in a tandem MS spectrum could be modeled by the application of the general fragmentation rules. Predictive software tools (Mass Frontier, HighChem, Mass Fragmenter, Advanced Chemistry Development, and EPIC) evaluate the starting structure of the parent compound and generate a set of hypothetical product ions that may arise from fragmentation. This list of candidate product ions could be matched with the list of experimental

*3.2.2. Software tools*

34 Progress in Carotenoid Research

The advance in knowledge of carotenoids occurrence in nature has required the application of different analytical techniques to characterize the structure of this family of pigments, how they accumulate in different tissues and the available metabolic conversions they experiment either in their natural cellular surrounding or in the tissues they are incorporated. Classical procedures for the extraction of carotenoids from raw sources and different biological materials have evolved with the inclusion of *green* technologies and environmentally friendly practices, which are summarized in this chapter. Indeed, the development of HPLC methods has introduced the new generation of stationary phases that shortens the run time and solvent expenditure. With the application of UPLC and two-dimensional liquid chromatography, the challenge of the characterization of intricate carotenoid profiles has been accomplished, and it is possible to select almost tailored chromatographic conditions to the target sample matrix containing the carotenoids. Thus, a relevant improvement has been the analysis of xanthophyll esters, which was a difficult approach few years ago. The current accessibility to mass spectrometry detectors has overcome several of the drawbacks that the traditional detection/ identification of carotenoids by the UV-visible spectrum. This has been possible due to the improvements in the ionization strategies and equipment applied to yield ions mass, as well as the use of mass spectrometers with high capabilities in terms of mass resolving power, mass accuracy, linear dynamic range, and sensitivity. Thus, the acquisition of full detailed MS data in conjunction with the information obtained from the chromatographic behavior and UV-visible features produce the accurate evidences for the correct identification and provide the appropriate biological meaning to the research issue. Finally, the practice in software tools implemented in the workflow of MS data analysis alleviates the manual labor of data processing and allows the systematic high-throughput screening of carotenoids and their metabolites.
