Calculating derivatives of spectral data by the Savitzky–Golay (SG) numerical algorithm is often used as a preliminary preprocessing step to resolve overlapping signals, enhance signal properties, and suppress unwanted spectral features that arise due to nonideal instrument and sample properties. Addressing these issues, a study of the simulated and measured infrared data by partial least-squares regression has been conducted. The simulated data sets were modeled by considering a range of undesired chemical and physical spectral anomalies and variations that can occur in a measured spectrum, such as baseline variations, noise, and scattering effects. The study has demonstrated the importance of the optimization of the SG parameters during the conversion of spectra into derivative form, specifically window size and polynomial order of the fitting curve. A specific optimal window size is associated with an exact component of the system being estimated, and this window size does not necessarily apply for some other component present in the system. Since the optimization procedure can be time-consuming, as a rough guideline spectral noise level can be used for assessment of window size. Moreover, it has been demonstrated that, when the extended multiplicative signal correction (EMSC) is used alongside the SG procedure, the derivative treatment of data by the SG algorithm must precede the EMSC normalization.

To assess whether Fourier Transform Infrared (FTIR) spectroscopy could be used to evaluate and monitor lipid extraction processes, the extraction methods of Folch, Bligh and Lewis were used. Biomass of the oleaginous fungi Mucor circinelloides and Mortierella alpina were employed as lipid-rich material for the lipid extraction. The presence of lipids was determined by recording infrared spectra of all components in the lipid extraction procedure, such as the biomass before and after extraction, the water and extract phases. Infrared spectra revealed the incomplete extraction after all three extraction methods applied to M.circinelloides and it was shown that mechanical disruption using bead beating and HCl treatment were necessary to complete the extraction in this species. FTIR spectroscopy was used to identify components, such as polyphosphates, that may have negatively affected the extraction process and resulted in differences in extraction efficiency between M.circinelloides and M.alpina. Residual lipids could not be detected in the infrared spectra of M.alpina biomass after extraction using the Folch and Lewis methods, indicating their complete lipid extraction in this species. Bligh extraction underestimated the fatty acid content of both M.circinelloides and M.alpina biomass and an increase in the initial solvent-to-sample ratio (from 3:1 to 20:1) was needed to achieve complete extraction and a lipid-free IR spectrum. In accordance with previous studies, the gravimetric lipid yield was shown to overestimate the potential of the SCO producers and FAME quantification in GC-FID was found to be the best-suited method for lipid quantification. We conclude that FTIR spectroscopy can serve as a tool for evaluating the lipid extraction efficiency, in addition to identifying components that may affect lipid extraction processes.

Pollen studies are important for the assessment of present and past environment, including biodiversity, sexual reproduction of plants and plant-pollinator interactions, monitoring of aeroallergens, and impact of climate and pollution on wild communities and cultivated crops. Although information on chemical composition of pollen is of importance in all of those research areas, pollen chemistry has been rarely measured due to complex and time-consuming analyses. Vibrational spectroscopies, coupled with multivariate data analysis, have shown great potential for rapid chemical characterization, identification and classification of pollen. This study, comprising 219 species from all principal taxa of seed plants, has demonstrated that high-quality Raman spectra of pollen can be obtained by Fourier transform (FT) Raman spectroscopy. In combination with Fourier transform infrared spectroscopy (FTIR), FT-Raman spectroscopy is obtaining comprehensive information on pollen chemistry. Presence of all the main biochemical constituents of pollen, such as proteins, lipids, carbohydrates, carotenoids and sporopollenins, have been identified and detected in the spectra, and the study shows approaches to measure relative and absolute content of these constituents. The results show that FT-Raman spectroscopy has clear advantage over standard dispersive Raman measurements, in particular for measurement of pollen samples with high pigment content. FT-Raman spectra are strongly biased toward chemical composition of pollen wall constituents, namely sporopollenins and pigments. This makes Raman spectra complementary to FTIR spectra, which over-represent chemical constituents of the grain interior, such as lipids and carbohydrates. The results show a large variability in pollen chemistry for families, genera and even congeneric species, revealing wide range of reproductive strategies, from storage of nutrients to variation in carotenoids and phenylpropanoids. The information on pollen’s chemical patterns for major plant taxa should be of outstanding value for various studies in plant biology and ecology, including aerobiology, palaeoecology, forensics, community ecology, plant-pollinator interactions, and climate effects on plants.

Mucoromycota fungi are important producers of low- and high-value lipids. Mortierella alpina is used for arachidonic acid production at industrial scale. In addition, oleaginous Mucoromycota fungi are promising candidates for biodiesel production. A critical step in the development of such biotechnological applications is the selection of suitable strains for lipid production. The aim of the present study was to use the Duetz-microtiter plate system combined with Fourier transform infrared (FTIR) spectroscopy for high-throughput screening of the potential of 100 Mucoromycota strains to produce low- and high-value lipids. With this reproducible, high-throughput method, we found several promising strains for high-value omega-6 polyunsaturated fatty acid (PUFA) and biodiesel production purposes. Gamma-linolenic acid content was the highest in Mucor fragilis UBOCC-A-109196 (24.5% of total fatty acids), and Cunninghamella echinulata VKM F-470 (24.0%). For the first time, we observed concomitant gamma-linolenic acid and alpha-linolenic acid (up to 13.0%) production in psychrophilic Mucor flavus strains. Arachidonic acid was present the highest amount in M. alpina ATCC 32222 (41.1% of total fatty acids). Low cultivation temperature (15 °C) activated the temperature sensitive ∆17 desaturase enzyme in Mortierella spp., resulting in eicosapentaenoic acid production with up to 11.0% of total fatty acids in M. humilis VKM F-1494. Cunninghamella blakesleeana CCM-705, Umbelopsis vinacea CCM F-539 and UBOCC-A-101347 showed very good growth (23–26 g/L) and lipid production (7.0–8.3 g/L) with high palmitic and oleic acid, and low PUFA content, which makes them attractive candidates for biodiesel production. Absidia glauca CCM 451 had the highest total lipid content (47.2% of biomass) of all tested strains. We also demonstrated the potential of FTIR spectroscopy for high-throughput screening of total lipid content of oleaginous fungi. The use of Duetz-microtiter plate system combined with FTIR spectroscopy and multivariate analysis, is a feasible approach for high-throughput screening of lipid production in Mucoromycota fungi. Several promising strains have been identified by this method for the production of high-value PUFA and biodiesel.

It is imperative to have reliable and timely methodologies for analysis and monitoring of seed plants in order to determine climate-related plant processes. Moreover, impact of environment on plant fitness is predominantly based on studies of female functions, while the contribution of male gametophytes is mostly ignored due to missing data on pollen quality. We explored the use of infrared spectroscopy of pollen for an inexpensive and rapid characterization of plants. The study was based on measurement of pollen samples by two Fourier transform infrared techniques: single reflectance attenuated total reflectance and transmission measurement of sample pellets. The experimental set, with a total of 813 samples, included five pollination seasons and 300 different plant species belonging to all principal spermatophyte clades (conifers, monocotyledons, eudicots, and magnoliids). The spectroscopic-based methodology enables detection of phylogenetic variations, including the separation of confamiliar and congeneric species. Furthermore, the methodology enables measurement of phenotypic plasticity by the detection of inter-annual variations within the populations. The spectral differences related to environment and taxonomy are interpreted biochemically, specifically variations of pollen lipids, proteins, carbohydrates, and sporopollenins. The study shows large variations of absolute content of nutrients for congenital species pollinating in the same environmental conditions. Moreover, clear correlation between carbohydrate-to-protein ratio and pollination strategy has been detected. Infrared spectral database with respect to biochemical variation among the range of species, climate and biogeography will significantly improve comprehension of plant-environment interactions, including impact of global climate change on plant communities.