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Use of FTIR Spectroscopy and Chemometrics with Respect to Storage Conditions of Moldavian Dragonhead Oil

  • The University College of Applied Sciences in Chełm, Poland

Abstract and Figures

Oils often have similar properties and can be difficult to identify based on color, smell or taste alone. The present paper suggests the use of Fourier-transform infrared spectroscopy (FTIR) in combination with chemometric methods to explore similarities and differentiate between samples of Moldavian dragonhead oil subjected to different storage conditions. Dragonhead is a plant characterized by very good honey output and ease of cultivation. Principal component analysis (PCA) was applied to a standard, full range of FTIR spectra. Additionally, hierarchical cluster analysis (HCA) was employed to explore the organization of the samples in groups relative to their “proximity” (similarity), by way of Euclidean distance measurement. PC1 and PC2 accounted respectively for 85.4% and 10.1% of the total data variance. PC1 and PC2 were strongly, negatively correlated within the entire spectral range; the only exception was the region corresponding to νs(-C-Hvst, -CH2) vibrations (aliphatic groups in triglycerides), where PC2 was positively correlated. The use of FTIR spectral analysis revealed noticeable differences in the intensity of bands characteristic of the ageing processes (markers of oxidative processes, etc.) taking place in oleaginous samples and related to the processes of fatty acids oxidation.
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Sustainability 2019, 11, 6414; doi:10.3390/su11226414
Use of FTIR Spectroscopy and Chemometrics
with Respect to Storage Conditions of Moldavian
Dragonhead Oil
Arkadiusz Matwijczuk
*, Tomasz Oniszczuk
*, Alicja Matwijczuk
, Edyta Chruściel
Anna Kocira
, Agnieszka Niemczynowicz
, Agnieszka Wójtowicz
, Maciej Combrzyński
and Dariusz Wiącek
Department of Biophysics, University of Life Sciences in Lublin, 20-950 Lublin, Poland; (A.M.); (E.C.)
Department of Thermal Technology and Food Process Engineering, University of Life Sciences in Lublin,
20-612 Lublin, Poland; (A.W.); (M.C.)
Institute of Agricultural Sciences, State School of Higher Education in Chelm, 22-100 Chelm, Poland;
Department of Analysis and Differential Equations, University of Warmia and Mazury,
10-710 Olsztyn, Poland;
Department of Physical Properties of Plant Materials, Institute of Agrophysics, Polish Academy of Sciences,
20-290 Lublin, Poland;
Correspondence: (A.M.); (T.O.);
Tel.: +48-81-445-65-64 (A.M.); +48-81-445-61-18 (T.O.)
Received: 17 August 2019; Accepted: 10 November 2019; Published: 14 November 2019
Abstract: Oils often have similar properties and can be difficult to identify based on color, smell or
taste alone. The present paper suggests the use of Fourier-transform infrared spectroscopy (FTIR)
in combination with chemometric methods to explore similarities and differentiate between
samples of Moldavian dragonhead oil subjected to different storage conditions. Dragonhead is a
plant characterized by very good honey output and ease of cultivation. Principal component
analysis (PCA) was applied to a standard, full range of FTIR spectra. Additionally, hierarchical
cluster analysis (HCA) was employed to explore the organization of the samples in groups relative
to their “proximity” (similarity), by way of Euclidean distance measurement. PC1 and PC2
accounted respectively for 85.4% and 10.1% of the total data variance. PC1 and PC2 were strongly,
negatively correlated within the entire spectral range; the only exception was the region
corresponding to νs(-C-Hvst, -CH
) vibrations (aliphatic groups in triglycerides), where PC2 was
positively correlated. The use of FTIR spectral analysis revealed noticeable differences in the
intensity of bands characteristic of the ageing processes (markers of oxidative processes, etc.)
taking place in oleaginous samples and related to the processes of fatty acids oxidation.
Keywords: chemometric analysis; Dracocephalum moldavica; FTIR spectroscopy; functional food
1. Introduction
One of the aspects of sustainable food production is the widest possible use of raw materials
with health-promoting properties. Currently, the bioeconomy is becoming increasingly globalized.
As a result of globalization processes, many previously new products now appear on European
markets, including plant products such as fruit or seeds, which have valuable antioxidative
properties and can potentially offer considerable health benefits to consumers. At the same time,
growing health awareness and the general problem of ageing societies dictate the direction of
research related to functional food intended for particular age groups. Maintaining a well-balanced
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diet largely based on plant products, often those advocated by traditional medicine, is fast becoming
one of the key concerns in our everyday lives. Apart from fruit, the production of functional food
largely depends on oils cold-pressed from seeds. Such oils provide considerable food energy as well
as essential unsaturated fatty acids (UFA), phytosterols, and liposoluble vitamins. Cold-pressed oils
are considered more nutritious due to their antioxidant and provitamins content, e.g., carotenoids,
tocopherols, polyphenols. Oils obtained exclusively from pressing are characterized by a lower
content of oxyphitosterols, carcinogenic and mutagenic compounds, as well as the absence of fatty
acid trans isomers [1,2]. The sensory quality of oil depends on a number of factors such as exposure
to light and oxygen, and time and temperature of storage. Auto- and photo- oxidative processes lead
to the oxidation of unsaturated fatty acids, and consequently, to the formation of fatty acid
hydroperoxides. It is important that the oil is pressed under appropriate conditions, and stored and
packed in an appropriate way.
Moldavian dragonhead (Dracocephalum moldavica L.) is a plant endemic to the Himalayas and
southern Siberia, which has been used for medicinal purposes in Central Asia since the Middle Ages.
The species is a fragrant, annual plant producing essential oils with a strong, lemony scent,
commonly cultivated for ornamental, melliferous, and medicinal purposes [3,4]. Its florescence
usually takes place in June. It produces violet or white flowers located at the top of the shoot in the
form of an apparent ear composed of pseudowhorls. The essential oils produced by the flowers,
stem, and leaves, as well as its sugar-rich nectar, render this plant particularly attractive for
pollinating insects [5]. The plant’s essential oils contain e.g., citral, geranial, neral, geraniol, and
geranyl acetate [6]. Its above ground parts have been identified as a source of flavones, terpenes,
proteins, polypeptides, and 16 amino acid. In August, the plant produces fruit, i.e., schizocarps
containing 4 seeds each. The plant is relatively undemanding in terms of its cultivation, and does not
require particularly fertile or nutrient-rich soils; however, calcium-rich soils and well-maintained
cultures are preferred. Furthermore, cultivation in sun-filled areas facilitates higher concentrations
of the essential oil in the flowers and stalks [1]. The seed yield depends on the method of cultivation,
and the plant’s botanical form and can vary from 2500 to 2800 kg ha1 for the white and blue cultivar,
respectively [3]. The seeds contain 18–29% of fatty oils rich in essential unsaturated fatty acids
(approx. 90%): α-linolenic (61.0%), linoleic (20%), oleic (8.5%), palmitic (6.5%), and stearic (5.0%) [7].
The seeds also contain 21% protein, with a desirable amino acid composition, mucilage with a
soluble dietary fiber fraction, and essential oil [8]. Moldavian dragonhead oil is considered very
valuable due to its chemical composition; indeed, with its high content of UFAs, the oil obtained
from Dracocephalum moldavica seeds may be classified as one of the most sought after biooils in
phytomedicine and cosmetology. For this reason, the extracts and oil obtained from this plant are
commonly used in the pharmaceutic, cosmetic, and food industries [3].
The widespread use of dragonhead oil has drawn the attention of researchers to the problems
related to its storage and the influence of various factors affecting its quality.
A multivariate data analysis allows us to model the chemical and physical properties of simple
and complex compounds on the basis of spectroscopic data. The scope and applicability of
qualitative and quantitative analyses employing infrared spectroscopy can be enhanced by
embracing a statistical methodology in approaching certain research problems. Researchers working
in a variety of fields are increasingly encouraged to take advantage of this analytical tool, which
further confirms its great scientific potential.
Spectroscopic analyses in the infrared range entail the measurement of the vibration
frequencies in the chemical bonds of functional groups such as e.g., C-C, C-H, O-H, C-O, or N-H,
following the absorption of radiation [9,10]. The measured values are processed by applying a
number of mathematical procedures (including Fourier transform) to the registered absorption
spectrum, which is, in turn, correlated to the actual concentration of respective ingredients in the
sample in a process of calibration. The data were compressed and further processed statistically
using multivariate chemometric techniques, including Principal Component Analysis (PCA) and
Hierarchical Cluster Analysis (HCA).
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In the last few years, numerous scientific publications have demonstrated the usefulness of
spectroscopic methods in the study of the properties of vegetable oils and, above all, the assessment
of the quality of edible oils [11,12]. It has been recognized that these methods are valuable for
monitoring the quality of edible oils. The study of oils can be carried out with the use of absorption
spectroscopy (UV-VIS) [13–15] and infrared spectroscopy (IR) [16–21]. The latter method can be
applied for qualitative and quantitative measurements of parameters of edible oils such as free fatty
acid [22], peroxide value [23], iodine and anisidine value [24,25], lipid classes, and fatty acid
composition [26,27].
The application of chemometric tools for the description, classification, organization,
determination, and exploration of geographic origin and quality control of food products has
recently become a very active research area (e.g., [28,29] and references therein). Many authors have
attempted to use these tools to classify plant foods or other objects. For example, in [30] the authors
applied chemometrics to classify pomegranate juices on the basis of their antioxidant activity. They
reported the main determinant of this parameter to be cultivar. In [31], Wang and coauthors carried
out PCA to gain an overview of the similarities and differences among 10 algal species, and also
investigated the relationships between total phenolic content and different antioxidant activity
assays. There are many examples of such research directions at present.
The present study involved the use of multivariate PCA and HCA analyses to identify the main
sources of variance between the Moldavian dragonhead oil samples stored under different
conditions. The PCA and HCA results were used for the purposes of early classification and
interpretation of differing oil samples in the analyzed set.
The main goal of the study presented in the present paper was to analyze the usability of FTIR
spectroscopy combined with chemometrics for the purposes of controlling the quality of oil obtained
from Moldavian dragonhead seeds, relative to the time and conditions of its storage. Moreover,
relevant spectra were analyzed in detail with the use of the aforementioned analytical methods to
attempt to identify the spectroscopic (infrared) markers (relevant bands) which reflect the varying
rate of ageing processes relative to the conditions under which a given product is stored and the
external stimuli to which it is exposed.
2. Materials and Methods
The research material consisted of oil pressed from the seeds of Moldavian dragonhead
(Dracocephalum moldavica L.). Before pressing, the seeds were stored in bags at room temperature.
Both unheated and thermally-processed seeds were used. The heat treatment entailed heating seeds
to 70 °C, 100 °C, and 130 °C, on a metal tray placed in a laboratory drier for a period of 1 h. The oil
pressing process was conducted using a DUO screw press by Farmet (Czech Republic) with an
efficiency of 18 to 25 kg·h1 and an engine speed of 1500 rpm. A 10 mm nozzle was used. After
pressing, the oil was left for 2 days to allow natural sedimentation to occur, after which it was placed
in 10 cm3 dark-glass bottles which were impenetrable by sunlight. Some samples were placed in an
argon atmosphere, while others were exposed to oxygen. Directly prior to pressing, control samples
were collected for the respective temperatures of seed drying and pressing atmospheres. The
remaining 80 samples were stored at two different temperatures: 7 °C (refrigerator) and 20–22°C
(air-conditioned laboratory room) for a period of 1, 2, 3, or 6 months, with and without exposure to
The four samples selected for the study were characterized by constant pressing temperature,
i.e., 130 °C, and storage temperature, i.e., refrigerated at 7 °C. Therefore, the variables were: the
storage atmosphere (argon or oxygen), the color of the bottle (dark or clear), and the storage time.
The oil obtained from pressing was analyzed in terms of its fatty acids profile, acid value (AV),
peroxide value (PV), anisidine value (AnV), and iodine value (IV). The general color (GC) was
determined, along with the content of carotenoid and chlorophyll pigments, β-carotene, tocopherols,
and PC-8.
The fatty acids profile was determined with the use of gas chromatography combined with
mass spectrometry. The oil samples were used to obtain methyl esters in accordance with PN-EN
Sustainability 2019, 11, 6414 4 of 16
ISO 12966-2, and their division was conducted using a Trace GC Ultra chromatograph with an ITQ
1100 spectrometer (Thermo Scientific, USA) with the use of a Rtx-2330 column (105 × 0.25 × 0.25 μm)
by Restek. The carrier gas was helium, applied at a constant flow-through rate of 1mL/min.; the
temperature range was from 60 to 250 °C (5 °C/min.), and the injection temperature was 250 °C.
FTIR Measurements: Measurements of ATR-FTIR background corrected spectra (25 scans for
each sample) were carried out with a HATR Ge trough (45° cut, yielding 10 internal reflections)
crystal plate at 20 °C, and were recorded with a 670-IR spectrometer (Agilent Technologies, Santa
Clara, CA 95051, USA). The Ge crystal was cleaned with ultra-pure organic solvents (Sigma-Aldrich,
Darmstadt, Germany). The instrument was continuously purged with argon for 40 min before and
during measurements. Absorption spectra at a resolution of one data point per 1 cm1 were obtained
in the region between 4000 and 400 cm1. Scans were Fourier-transformed and averaged with
Grams/AI 8.0 software (Thermo Electron Corporation; Waltham, MA, United States, USA).
Chemometric analysis: All the registered spectra were subjected to multivariate analyses,
specifically, hierarchical cluster analysis (HCA) and principal component analysis (PCA), conducted
with the use of the OriginPro software (OriginLab, Northampton, MA, USA) and PCA for spectra
application. The numbers associated with the names of every sample in the chemometrics analysis
correspond to the conditions of FTIR spectra measurements, that is, number 1 corresponds to the
conditions described on Figures 1 and 2, etc.
3. Results and Discussion
The cold-pressed Moldavian dragonhead oil was characterized by a unique content of fatty
acids [1,2]. Over 90% of the fatty acids present in this oil are unsaturated, of with over 80% are
polyunsaturated fatty acids. The content of palmitic acid (C16:0) was 3.84%, palmitoleic acid (C16:1)
–0.19%, stearic acid (C18:0)–1.71%, oleic acid (C18:1)–6.81%, linoleic acid (C18:2 (9,12), n-6 omega-6
fatty acid)–19.01%, α-linolenic acid ALA (C18:3 (9,12,15), n-3 omega-3 fatty acid)–67.91 %, and other
acids approx. 0.54%. The results showed that the three predominant fatty acids in the Moldavian
dragonhead oil were linolenic (67.9%), oleic (6.8%) and linoleic (19.0%) acids. The content of
saturated fatty acids was very low (less then 6%), whereas the oil was rich in unsaturated ones. The
contents of mono and polyunsaturated fatty acids were 7.0% and 86.9%, respectively. Compared to
other important high-linolenic oils, such as flax and chia oils, the linolenic acid content in Moldavian
dragonhead seed oil was higher than that of flax (50%) and chia (62%) oils. The n-3 to n-6 ratio (3.5)
was higher than that of flax (3.3) and chia (3.2) oils. The human body cannot synthesize linolenic
acid, and therefore, it is known, along with linoleic acid, as an essential fatty acid*. Due to the high
content of this fatty acid and high ratio of n-3/n-6, Moldavian dragonhead seed and the extracted oil
can be used as a food supplement, where enrichment with omega-3 fatty acids is needed.
Figures 1–4 present the ATR-FTIR spectra for the analyzed samples of the oil obtained from
Moldavian dragonhead seeds stored at 7 °C (refrigerated) in an Ar or O2 atmosphere, in a dark or
clear bottle, respectively: a—immediately after pressing, b—two weeks after pressing, c—four weeks
after pressing, d—10 weeks after pressing. The oil was pressed at a temperature of 130 °C. The
experimental constants were the oil pressing temperature (130 °C) and the particular storage
conditions. The samples were spread on a Zn–Se crystal and analyzed under a N2 atmosphere.
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1800 16 50 150 0 1350 1200 10 503000 2850
Wavenumber [cm
bsorbance [a. u.]
Figure 1. ATR-FTIR spectra for selected Moldavian dragonhead oil samples stored at 7 °C
(refrigerated) in an argon atmosphere in a clear bottle, respectively: a—immediately after pressing,
b—two weeks after pressing, c—four weeks after pressing, d—8 weeks after pressing. The spectra
are presented with the spectral range of 900–3150 cm1.
1800 16 50 150 0 1350 12 00 10 503000 2850
Wavenumber [cm
Absorbance [a. u.]
Figure 2. ATR-FTIR spectra for selected Moldavian dragonhead oil samples stored at 7 °C
(refrigerated) in an O2 atmosphere in a clear bottle, respectively: a—immediately after pressing,
b—two weeks after pressing, c—four weeks after pressing, d—8 weeks after pressing. The spectra
are presented with the spectral range of 900–3150 cm1.
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Figure 3. ATR-FTIR spectra for selected Moldavian dragonhead oil samples stored at 7 °C
(refrigerated) in an argon atmosphere in a dark bottle, respectively: a—immediately after pressing,
b—two weeks after pressing, c—four weeks after pressing, d—8 weeks after pressing. The spectra
are presented with the spectral range of 900–3150 cm1.
Figure 4. ATR-FTIR spectra for selected Moldavian dragonhead oil samples stored at 7 °C
(refrigerated) in an O2 atmosphere in a dark bottle, respectively: a—immediately after pressing,
b—two weeks after pressing, c—four weeks after pressing, d—8 weeks after pressing. The spectra
are presented with the spectral range of 900–3150 cm1.
Table 1 and Tables S1–S3 (in Supplementary Materials) provide a description of all the
characteristic bands present in the oil samples selected for the study, along with the related
vibrations of particular functional groups.
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Table 1. Positions of the maxima of absorption spectra and assignment to the relevant vibrations as
recorded for Moldavian dragonhead oil samples stored at 7 °C (refrigerated), in an argon atmosphere
and a clear bottle, respectively: a—immediately after pressing, b—two weeks after pressing, c—four
weeks after pressing, d—8 weeks after pressing.
Type and Origin of Vibrations
Position of Bands (cm1)
a b c d
3010 3008 3007 3013
2956 2963 2965 2961 νas(-C-Hvst, -CHa) and νs(-C-Hvst, -CHa) (aliphatic groups in
2926 2926 2925 2928
2853 2853 2852 2854
1743 1742 1743 1743
(-C=Ovst) in esters
1708 1701 1709 1701
(-C=Ovw) in acids
1656 1647 1656 1651
νvw(-C=C-, cis-)
1588 591 1600 1613
- - 1589 1557
- - - 1540
- - - 1515
1459 1460 1460 1457 δvw(-C-H) w CH2 and in CH3, groups, deformation
(scissoring) νvw(-C-H, cis-) deformation (ring)
- - 1429 1428
1373 1375 1375 1369/1393 νw, m, vw (-C-H, -CH3) and deformation
1302 1318 1304/1348 - δm(-C-H, -CH3)
1271 1262 1268 1267 νm(-C-O) or δm(-CH2-)
1236 1240 1237 - νm(-C-O) or δm(-CH2-)
1161 1159 1160 1161 νm(-C-O)
1097 1099 1100 1098
νm,vw(-C-O) 1067 1025 1065 1028
1027 - 1030 -
966 968 964 964 δw(-HC=CH-, trans-) out-of-plain deformation
ν—stretching vibrations, δ—deformation vibrations, s—symmetric, as—asymmetric, st—strong, w—weak.
3.1. FTIR Spectroscopic Analysis of Moldavian Dragonhead Oil Samples
All the infrared (FTIR) spectra for the selected Moldavian dragonhead oil samples revealed
very intensive bands which correspond to specific vibrations of the respective functional groups
contained in ingredients typically found in this type of food. Plant fats and potential oleaginous
materials are substances composed primarily of various fractions of triglyceride groups, mainly
differing in terms of the degree and form of the acyl groups’ unsaturation, as well as the length of
their chains [9]. Numerous publications provide the appropriate associations of the particular
spectral bands in oils, both animal and vegetable, and other fats [10,32–34] with specific vibrations in
particles or groups thereof, although many bands are not easily assigned to respective functional
groups. Table 1 and Tables S2–S3 (in Supplementary Materials) present in detail the frequencies of
characteristic spectra, including the most significant broadenings/enhancements of the respective
spectral bands for the four analyzed time-frames of oil sample storage, as well as their association
with the respective functional groups (with a detailed review and comparison with data available
from the literature [9,35–37]. The subscript text indicates the intensity of the observed bands within
typical IR spectra for this type of biological sample. It should be pointed out that, in this case, the
association of the maxima corresponding to the mode of stretching vibrations in the IR spectra of the
analyzed samples is considerably easier than assigning the bands corresponding to deformation
vibrations. This is due to the fact that bands corresponding to the vibrations of the latter type often
tend to overlap. The presented FTIR spectra reveal vibrations of the methylene group, located in the
Sustainability 2019, 11, 6414 8 of 16
spectral range from 1350 to 1150 cm1 [9]. They are stretching vibrations of the -C-H group bonded
with CH3 (approx. 1350–1360 cm1, in out samples 1370 cm1), as well as deformation vibrations in
this group (~1160 cm1, in our samples 1159–1165 cm1). In this case, the stretching vibrations of the
ester bond ν(C-O) are a combination of two asymmetric vibrations, namely those of C-C(=O)-O and
O-C-C [10,38]. The former vibrations are typically considerably more intensive [12]. The bands are
located at approx. 1300 (as C-C(=O)-O, in our case, approx. 1270 cm1, as visible enhancement of the
band with the maximum at 1235–9 cm1) and at approx. 1000 cm1 (in our case 1028 to 1036 cm1 for
these groups).
In turn, bands related to the vibrations of saturated esters C-C(=O)-O occur between 1240 and
1160 cm1 (in our case approx. 1234–40 cm1) [39], whereas for unsaturated esters, the vibrations are
more often generated at lower frequencies [9]. On the other hand, the O-C-O band originating from
primary alcohols appears in the region from 1100 to 1020 cm1 (in our case approx. 1029–31 cm1, as
mentioned above), whereas in the case of secondary alcohols, the band usually appears with the
maximum at approx. 1100 cm1 (in our case 1090–1093 cm1). Both types of esters descried above are
present in triglyceride particles. In the literature, the mentioned band (at approx. 1239–4 cm1) has
been associated exclusively with out-of-plane bending vibrations of the methylene group [40].
Another two bands presented in Table 1 and Tables S1–S3 (in Supplementary Materials) (as
well as in Figures 1 and 2) are somewhat more difficult to identify: the maximum of the first band is
at approx. 1416–18 cm1, and that of the second at approx. 1320 cm1 (most likely a band broadening,
see Figures 1–4). The first group of vibrations with the maximum at approx. 1416–18 cm1
(depending on the duration of the experiment) is often assigned to the vibrations of the methyl
groups in the aliphatic chains of the analyzed oils [36,40]. The second group of bands (most likely
band broadening or enhancement) with the maximum at approx. 1320 cm1 (in all the samples—not
shown so as not to obscure the presentation) is observed simultaneously with the bands with the
maximum at approx. 980 cm1 and lower wave numbers. It should be noted that the band at approx.
920 cm1 (depending on duration of the experiment, i.e., more or less intensive), which appears in all
oil samples, is related to the stretching vibrations of cis-substituted olefin groups [35], or can be
connected with the vibrations of the vinyl group.
The oil samples examined at the initial stages of the experiment produced largely similar
spectra in the infrared range. Depending on the duration of the experiment (storage time,
irrespective of analogous storage conditions), the particular spectra started to reveal significant
differences in terms of the intensity and position of the respective bands (the shifts were not large
but very important; discussed further in the text). In each case, we observed the maximum
absorbance, which was clearly correlated to the particular storage conditions (i.e.,
duration/atmosphere and bottle color). All spectra in Figures 1–4 are shown analogically, and
indicate very evident ageing effects in the case of Moldavian dragonhead oil samples.
Other very important vibration regions were also observed with respect to the bands with
maxima at approx. 1745-1 cm1, which were typical of the stretching vibrations of the carbonyl C=O
group [9] in ester groups. Next to the band (characteristic of the vibrations of the carbonyl group in
esters), we observed, on the lower wavenumber side, a clearly-visible enhancement with the
maximum at approx. 1700-15 cm1 (whose intensity also increased together with the ageing effect),
which corresponded to the vibrations of a carbonyl group, but in this case, found in the acidic
groups of the analyzed samples [9].
The next band, with a maximum at 1655-3 cm1, corresponded to the stretching vibrations of the
-C = C- group (particularly the cis-transformation) [33]. It is noteworthy that the intensity of those
bands increased with longer storage times of the respective samples, which clearly evidences
ongoing ageing processes (discussed further in the text). A very characteristic region was also
observed for the vibrations with the maximum at 1461–3 cm1 and originating from the -C-H
deformation vibrations in CH2 and CH3 groups (bending vibrations). One should also mention the
vibrations in the region from 900 to 650 cm1 (partially not presented due to low intensity)
corresponding, in the analyzed case, to the characteristic deformation vibrations of the -HC=CH-
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groups (out-of-plain cis-conformation) and ring vibrations of the aforementioned groups (δ(-(CH2)n-
and -HC=CH- (cis-)) [9].
The next very important band corresponded to the =C-H stretching vibrations
(trans-transformation) with a maximum at approx. 3063–4 cm1 (not shown), which originated from
the vibrations of triglyceride fractions [34]. With respect to the =C-H stretching vibrations in the
cis-configuration, very characteristic and intensive vibrations were observed with the maximum at
approx. 3007/12 cm1 (Figures 1 and 4, Table 1 and Tables S1–S3 (in Supplementary Materials)).
Vibrations with the maxima at approx. 2952/8, 2922/8, and 2852/7 cm1 originated, respectively, from
the -C-H stretching vibrations in -CH3, CH2 groups belonging to the aliphatic groups in triglycerides
It should be emphasized that the spectra of the analyzed oil samples revealed clear
discrepancies in the shape of the bands, particularly in the region from 1780 to 1670 cm1 [36]. Most
of the analyzed samples showed a clearly-defined, slight enhancement of the band at 1743/6 cm1
(corresponding to the vibrations of the C=O group, as discussed above) on the lower wavenumber
side, with a clear maximum at approx. 1700–16 cm1 [42], which can be associated with the formation
of a hydrogen bond between C=O…H-O-H groups. Simultaneously to the emergence of the band at
1700–16 cm1, we observed an increase in intensity at approx. 1350–70 cm1 [22,42], which can also be
associated with the stretching vibrations of C-O and C-C groups (as described above). Furthermore,
the area between 1100 and 1300 cm1 also corresponded to stretching vibrations of the C-O group,
but the same indicated minor discrepancies between the analyzed oil samples, regardless of the
storage time. The bands may display a slight increase in intensity with the decreasing affinity of the
particles that generate them toward for the formation of the hydrogen bond between C=O…H-O-H,
and, as such, constitute a perfect marker of the preliminary ageing processes taking place in the
analyzed samples.
In summary, the results of the spectroscopic studies revealed significant differences with
respect to certain bands which constitute important spectroscopic markers of the ageing processes
taking place in the analyzed oil samples. In particular, the observation of spectra within the range
from 1715 to 1500 cm1 in the samples stored for 8 weeks revealed significant changes in terms of the
position and intensity of the band characteristic of the carbonyl group, with the maximum at approx.
1744 cm1. The region from 1715 to 1500 cm1 is related mainly to various vibrations originating from
the C-C and C=C groups and evidencing the progress of ageing processes (with the oxygenation of
fatty acids contained therein). One should also mention the band with a maximum at approx. 1426
cm1, related to the vibrations of C-H groups in acids. Very significant changes, particularly in the
8th month of the experiment, were observed in the shape of the band with the maximum at approx.
1369 cm1, as well as with regard to the shift of the band at 1237 cm1, which also reflected the
aforementioned changes. The impact of the manner of storage was also noticeable: significant
spectral changes were correlated with the varying storage conditions. This confirms the significant
impact of storage conditions on the quality and durability of the product.
3.2. Chemometrics Studies
The HCA analysis allows for the visualization of the group and sub-group arrangement of the
spectra. The HCA (Figure 5) revealed the intragroup similarity within the considered samples and
generated clusters in each group. The difference in the spectral range was established by considering
similar areas of groups in all the samples. While the HCA dendrogram indicates differences in the
groups of investigated samples of oils, there are important questions that remain unanswered. For
example, which variations in the functional group between the samples bring about the difference in
the HCA analysis? How do vibrations of different functional groups in samples vary in the terms of
their intensity and shift? These questions need to be considered to specify the measurement of the
FTIR data. Therefore, PCA was used further in order to get answers to the aforementioned
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Figure 5. Hierarchical Cluster Analysis (HCA) for FTIR Spectra of all oil samples.
A principal component analysis (PCA) [43] allowed us to visualize a given dataset with respect
to several main components, while accounting for possibly the highest possible percentage of the
set’s variance. After applying the PCA, the initial set of variables is reduced to a number of hidden
variables of principal components (PC) [44–46]. The scree plot (Figure 6) reveals that the greatest
impact on the variance of the analyzed spectra registered for our oil samples was related to the first
three principal components. Figures 7 and 8 present the score plot for the principal components PC1
vs. PC2 in the PCA model corresponding to the Moldavian dragonhead oil samples stored under
various conditions. The results for all samples and the first two principal components PC1 and PC2,
which jointly accounted for 95.5% of the data matrix variance, are presented in Figures 7 and 8. Oil
samples were clearly classified into three groups (Figures 6–8). The first, Group A, includes oil
samples a1, i.e., immediately after pressing (argon, clear bottle), and d1, i.e., 8 weeks after pressing
(argon, clear bottle). The above were samples where no enhancement was observed of the band at
1743 cm1, characteristic of the vibrations of the C=O group in esters. However, in the remaining
bands (Table 1), clear differences in terms of their intensity and position could be identified.
A sample from Group C, d2, i.e., oil sample stored in an argon atmosphere, in a clear bottle,
analyzed 8 weeks after pressing, clearly stood out from the other samples. This sample formed its
own, one-element cluster. Such an organization into groups of the samples stems from the
measurements of the sample spectra [47]. When analyzing the spectra of all oil samples stored in an
oxygen atmosphere and in clear bottles (a2, b2, c2, d2), we concluded that the highest intensity was
observed for oil sample d2. On the other hand, the remaining oil samples analyzed after 8 weeks in
storage (d3, d4) revealed significant similarities, as evidenced by their relative proximity on the
dendrogram (Figure 5). It can be observed that oils d3 and d4, constituting a subgroup of Group C,
were located in the vicinity of oil d2 (Group C), which indicated significant similarity. At the same
time, sample d1, included in Group A, revealed the highest spectral intensity of all oil samples
analyzed after 8 weeks of storage.
Sustainability 2019, 11, 6414 11 of 16
The remaining oil samples were classified under Group B. This distribution could be the result
of their particular physicochemical properties. Moreover, an analysis of the loading plot (Figures 9
and 10) reveals that PC1 was negatively correlated with all the characteristic spectra of the oil
samples, whereas PC2 was positively correlated only with the νs(-C-Hvst, -CHa) vibrations (aliphatic
groups in triglycerides) (approx. 2854 cm1).
Figure 6. Plot of eigenvalues for PCA of FTIR spectra.
Figure 7. 3D Score plot of PCA.
Sustainability 2019, 11, 6414 12 of 16
Figure 8. 2D score plot of PCA. PC1 vs. PC2.
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Figure 9. 3D loading plot of PCA.
Figure 10. Loading plot of PC1 and PC2 for reference spectrum a1, a2, a3, a4.
4. Conclusions
1. Principal component analysis (PCA) was used to identify the main sources of variance in the
Fourier-transforms infrared (FTIR) spectra of oil samples obtained from Moldavian dragonhead
seeds and stored under different conditions. PCA combined with HCA allowed the samples to
be explored in terms of their similarities, relative to the storage method with respect to their
FTIR spectra. Due to its inherent simplicity, quick and non-invasive character, this method may
prove useful in monitoring the physicochemical changes in oils or e.g., the oxidative state in oils
relative to the time and conditions under which they are stored.
2. The analyzed oil samples were characterized by a very good fatty acids profile, which
confirmed their value as food products with significant health benefits. Spectral analysis
revealed significant changes with respect to bands associated in the literature to various fat
fractions contained in the oil. The noticeable changes occurring after 8 weeks in storage in
infrared spectra located within the ranges of 1720–1500 cm-1 and ~1426 cm1, 1369 and 1237 cm1,
constituted markers which are evidence of the advancement of the ageing processes in the
analyzed samples. Changes related to aging of the sample were related to the intensification of
bands reflecting the vibrations of C-C, C=C, and C=O groups; as such, they constitute perfect
marker bands which can be easily correlated with the given oil’s shelf life and the oxidative
processes that affect it. However, only a detailed chemometric analysis allowed us to
complement and fully follow differences between the respective samples which reflected the
particular storage conditions.
3. The advent of FTIR with multivariate analysis has revolutionized many research fields. FTIR
offers unique advantages, as it reflects the overall vibrations of the components and their
Sustainability 2019, 11, 6414 14 of 16
interactions within the samples as spectra, in addition to being non-invasive and label-free,
unlike conventional methods of this kind.
In this study, we utilized technique FTIR to analyze oil samples from Moldavian dragonhead
seeds. This technique, combined with chemometric analysis, was capable of differentiating the
sample response in relation their similarity and value as food products with significant health
benefits. It is expected that the presented results may prove useful in defining the spectroscopic
markers of the ageing processes that take place in oil samples, which significantly affect the quality
and shelf-life of oil products. Moreover, the study illustrated a reliable, quantitative method of
detecting preliminary differences between oil samples without the need to resort to costly, standard
chemical methods.
Supplementary Materials: The following are available online at
Author Contributions: Conceptualization, A.M. (Arkadiusz Matwijczuk), T.O. and A.K.; methodology, A.M.
(Arkadiusz Matwijczuk), T.O. and A.M. (Alicja Matwijczuk); validation, A.W., E.C. and M.C.; formal analysis,
A.M. (Arkadiusz Matwijczuk), A.W., D.W. and A.N; data curation. A.M. (Arkadiusz Matwijczuk), T.O., A.K.,
A.M. (Alicja Matwijczuk), A.N., A.W. and D.W. writing—original draft, A.M. (Arkadiusz Matwijczuk), T.O.,
A.K., A.M. (Alicja Matwijczuk), A.N., A.W. and D.W. All authors read and approved the final manuscript.
Funding: This research received no external funding.
Acknowledgments: The part of research of Agnieszka Niemczynowicz in publication was written as a result
internship in Valencia, Spain, co-financed by the European Union under the European Social Fund (Operational
Program Knowledge Education Development), carried out in the project Development Program at the
University of Warmia and Mazury in Olsztyn (POWR.03.05. 00-00-Z310/17). The authors Agnieszka
Niemczynowicz and Arkadiusz Matwijczuk acknowledge the Cost project CA 15126 and CA15216.
Conflicts of Interest: The authors declare no conflict of interest.
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... PCA was applied to find difference in samples and potential dimensionality of the system. 38 Figure 2 shows a clear trend with increased processing temperature, for example, from B009 (raw feathers) to B16 (processed at 160°C). ...
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Jellyfish is an emerging aquaculture species, farmed for Oriental cuisines and nutraceutical ingredients. This study aimed to examine antioxidative and antimicrobial potentials of various fractions of the jellyfish, Acromitus hardenbergi. The bell and oral arms of the jellyfish were sequentially extracted with petroleum ether (PE), dichloromethane (DCM), chloroform (CHCl3), methanol (MeOH), and water (H2O) to extract its bioactive in an increasing polarity gradient. Test fractions were assayed for antiradical activities using electron spin resonance spectrometry, β-carotene-linoleate model and Folin-Ciocalteu assay; and antimicrobial activity against 2 Gram-negative bacteria, 4 Gram-positive bacteria and 2 fungal species using the disc diffusion assay. All fractions were also subjected to Fourier Transform Infrared (FTIR) analysis to identify types of functional groups present. It was found that the hydrophilic extracts (H2O fractions) possessed the most effective radical scavenging activity (p < 0.05) while the lipophilic extracts (PE fractions) the most active antimicrobial activity, especially against Gram-positive bacteria (p < 0.05). Total oxidation substrates content was found to be highest in the PE fractions of jellyfish bell and oral arms (p < 0.05). FTIR data showed that the H2O and MeOH fractions contains similar functional groups including -OH, -C=O, -N-H and -S=O groups, while the PE, DCM, and CHCl3 fractions, the -CH3, -COOH groups. This study showed that A. hardenbergi contains antioxidants and antimicrobials, thereby supporting the traditional claim of the jellyfish as an anti-aging and health-promoting functional food. Bioassay-guided fractionation approach serves as a critical milestone for the strategic screening, purification, and elucidation of therapeutically significant actives from jellyfish.
This research investigates the effects of different extraction processes on the oil extractability, oxidative stability, bioactive compounds, and antioxidant activity of crude rice bran oil (CRBO). The experimental extraction processes include hexane extraction (HE), cold press extraction (CE), thermally pretreated cold press extraction (CCE), and ultrasound-pretreated cold press extraction (UCE). The results show that thermal cooking and ultrasound pretreatment significantly improve the oil extractability of the cold press extraction process. The oil yields of CE, CCE, and UCE were 14.27, 17.31, and 16.68 g oil/100 g rice bran, respectively. The oxidative stability of CE and CCE oils was higher than HE and UCE oils, as evidenced by the synchrotron-radiation-based Fourier transform infrared (SR-FTIR) absorption peak. The ρ-anisidine values of HE, CE, CCE, and UCE were 0.30, 0.20, 0.91, and 0.31, respectively. Meanwhile, ultrasound pretreatment significantly reduced the bioactive compounds and chemical antioxidant activity of UCE oil. The CE, CCE, and UCE oils (0.1% oil concentration) exhibited higher inhibitory effects against hydrogen-peroxide-induced cellular oxidative stress, compared to HE oil (0.39% oil concentration). Essentially, CCE is operationally and environmentally suitable for improving the oil yield, oxidative stability, bioactive compounds, and antioxidant activities of CRBO.
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Different strategies have been used to degrade the molecular structure of lignins in natural fibers. Both chemical and biological processes can obtain different types of lignins for industrial use. In this study, a variation of the spectral intensity of the thermo-mechanical and fungi-modified Bambusa oldhamii (giant bamboo) and Guadua angustifolia Kunt fibers were examined via Fouriertransform infrared spectroscopy. The giant bamboo and Guadua angustifolia Kunt specimens were modified using a non-chemical alternative steam pressure method for degrading lignins, followed by mechanical sieving to obtain fibers of different lengths. The obtained fibers were treated with the Fusarium incarnatum-equiseti MF18MH45591 strain in a 21 d degradation process. The samples were subjected to Fouriertransform infrared spectroscopy before and after the strain treatment. The intensity variation was found to be in the spectral range of 1200 cm−1 to 1800 cm−1, in which lignin components are commonly found in most plant species. A multivariate analysis of the principal components of the treated and untreated control samples confirmed the changes in the spectral region of interest, which were associated with the thermo-mechanical and fungal treatment.
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Dracocephalum moldavica is a valuable reward plant for flower visitors. The aim of the study was to ecologically characterise its flowers and leaves and assess the seasonal and daily dynamics of flowering in two white- and blue-flowered forms of this species in 2004 and 2005. Additionally, the duration and abundance of plant flowering as well as the nectar amount and sugar content were analysed. The signalling attractants of the plant include an intense scent emitted by trichomes located not only on its flowers but also on its stem and leaf surfaces. The average corolla length is 24 mm and the corolla tube, which can be completely filled with nectar, is 8.6 mm long. The floral lifespan was shown to reach 2-3 days and the mean blooming duration of both forms of dragonhead 45-48 days. The white-flowered plants produced a substantially greater number of flowers (5352) than the blue-flowered form (2965). The nectar amount obtained from ten blue flowers was 15.33 mg and that extracted from white flowers reached 17.56 mg, with 49.4% and 51.5% content of sugar, respectively. The total sugar mass produced by one white-flowered plant was 4656 mg, while one blue-flowered plant yielded 2164 mg of sugars. The sugar yield calculated in the study for the white-flowered form (586 kg · ha−1) was two-fold higher than that in the blue-flowered plants.
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Aromatic plants are rich in essential oils with considerable antimicrobial properties. The aim of this study was to investigate chemical composition, antimicrobial activity and antioxidant properties of Melissa officinalis and Deracocephalum moldavica essential oils (EOs). The identification of chemical constituents of the EOs was carried out using gas chromato-graphy-mass spectrometry analysis and antimicrobial activity of the EOs was evaluated by disc diffusion assay as well as determination of minimal inhibitory concentration (MIC) and minimal bactericidal concentration against four important food-borne bacteria: Salmonella typhimorium, Escherichia coli, Listeria monocytogenes and Staphylococcus aureus. Antioxidant activity of the EOs was also determined by 2,2-diphenyl-1-picrylhydrazyl, 2,2-azinobis 3-ethylbenzo thiazoline-6-sulfonic acid and β-carotene bleaching tests. The major compounds of D. moldavica were geranial (28.52%), neral (21.21%), geraniol (19.60%), geranyl acetate (16.72%) and the major compounds of M. officinalis EO were citronellal (37.33%), thymol (11.96%), citral (10.10%) and β-caryophyllene (7.27%). The underlying results indicated strong antimicrobial effects of the oils against tested bacteria. Staphylococcus aureus with the lowest MIC value (0.12 mg mL⁻¹) for both EOs was the most sensitive bacterium, although, antibacterial effect of M. officinalis EO was stronger than D. moldavica. In addition, the results of the antioxidant activity showed that both EOs had notable antioxidant properties. In conclusion, both EOs are appropriate alternatives as potential sources of natural preservative agents with the aim of being applied in food industries.
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Application of Moldavian dragonhead (Dracocephalum moldavica L.) leaves in extruded snacks was evaluated. Directly expanded corn snacks (crisps) were supplemented with 5–20% of dragonhead leaves. The supplemented snacks were characterized to have improved nutritional value and were a good source of dietary fibre. The presence of phenolic compounds, especially rosmarinic acid, showed a high antioxidant potential and a radical scavenging activity of tested snacks, especially if a high content of additive was used. The increasing amount of additive also had an impact on the physical properties of extrudates lowering the expansion ratio, water absorption and solubility, yet increasing bulk density, cutting force and the breaking index of the enriched snacks. The highest viscosity was observed at 5 and 10% addition level. The increasing amount of dragonhead leaves lowered the brightness of snacks and increased the greenness tint significantly. A sensory evaluation showed good acceptability of snacks enriched with up to 15% of dragonhead dried leaves. Dried leaves of the Moldavian dragonhead seem to be a prospective functional additive for extruded crisps with a high nutritional value, especially because of dietary fibre and rosmarinic acid content, a strong antioxidant potential and acceptable sensory properties.
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Due to its pharmacological activity, Sambucus nigra L. is excellent potential component of functional food. The main aim of presented study was quantitative and qualitative analysis (LC-ESI-MS/MS) of phenolic acids and flavonoids present in extracts obtained from corn snacks with addition of elderberry fruits or flowers. Additionally, antiradical activity of samples was determined. Moreover, the comparison of various extraction methods of polyphenols from that functional food was made. In corn snacks, without additives, nine phenolic compounds were identified. These were: protocatechuic, 4-OH-benzoic, caffeic, p-coumaric, salicylic, ferulic acids, rutin, isoquercetin and apigenin-7-glucoside. In the extract from Sambucus flowers and extract from snacks containing 20% of Sambucus flowers fifteen polyphenols were found. They were additionally: gallic, gentisic, vanillic, sinapic acids, kaempferol-3-rutinoside and astragalin. The radical-scavenging activity of the extracts was determined spectrophotometrically against DPPH• (2,2-diphenyl-1-picrylhydrazyl) radical and using thin layer chromatography. The high antiradical potential was observed for crude extracts from Sambucus flowers or fruits and for extracts enriched with 20, 10, 5% of Sambucus flowers. The product with a 20% addition of fruits revealed moderate free radical scavenging properties.
Background The development of statistical software has enabled food scientists to perform a wide variety of mathematical/statistical analyses and solve problems. Therefore, not only sophisticated analytical methods but also the application of multivariate statistical methods have increased considerably. Herein, principal component analysis (PCA) and hierarchical cluster analysis (HCA) are the most widely used tools to explore similarities and hidden patterns among samples where relationship on data and grouping are until unclear. Usually, larger chemical data sets, bioactive compounds and functional properties are the target of these methodologies. Scope and approach In this article, we criticize these methods when correlation analysis should be calculated and results analyzed. Key findings and conclusions The use of PCA and HCA in food chemistry studies has increased because the results are easy to interpret and discuss. However, their indiscriminate use to assess the association between bioactive compounds and in vitro functional properties is criticized as they provide a qualitative view of the data. When appropriate, one should bear in mind that the correlation between the content of chemical compounds and bioactivity could be duly discussed using correlation coefficients.
Edible fats and oils are among the basic components of the human diet, along with carbohydrates and proteins, and they are the source of high energy and essential fatty acids such as linoleic and linolenic acids. Edible fats and oils are used in for pan- and deep-frying, and in salad dressing, mayonnaise and processed foods such as chocolates and cream. The physical and chemical properties of edible fats and oils can affect the quality of oil foods and hence must be evaluated in detail. The physical characteristics of edible fats and oils include color, specific gravity, refractive index, melting point, congeal point, smoke point, flash point, fire point, and viscosity, while the chemical characteristics include acid value, saponification value, iodine value, fatty acid composition, trans isomers, triacylglycerol composition, unsaponifiable matters (sterols, tocopherols) and minor components (phospholipids, chlorophyll pigments, glycidyl fatty acid esters). Peroxide value, p-anisidine value, carbonyl value, polar compounds and polymerized triacylglycerols are indexes of the deterioration of edible fats and oils. This review describes the analytical methods to evaluate the quality of edible fats and oils, especially the Standard Methods for Analysis of Fats, Oils and Related Materials edited by Japan Oil Chemists' Society (the JOCS standard methods) and advanced methods.
Long thermal oxidative kinetic and stability of four different edible oils (colza, corn, frying, sunflower) from various brands were surveyed with the use of attenuated total reflectance–Fourier transform infrared spectroscopy (ATR–FTIR) combined with multivariate curve resolution-alternative least square (MCR-ALS). Sampling from the heated oils (at 170 °C) was performed each 3 h during a 36-h period. Changes in the ATR–FTIR spectra of the oil samples in the range of 4000–550 cm−1 were followed as a function of heating time. MCR-ALS was utilized to resolve the concentration and spectral profiles of three detected kinetic components. Three variations in resolved concentration profiles were related to the thermal-deduction of triacylglycerol of unsaturated acid, appearance of hydroperoxides form of triacylglycerols and generation of secondary oxidation products. The kinetic profiles of these species were dependent on the type of oil. The proposed method can define a new way to monitor the oils’ quality.
Our work explored, for the first time, monitoring peroxide value (PV) of omega-3 rich algae oil using ATR-FTIR spectroscopic technique. The PV of the developed method was compared by that obtained by standard method of Association of Official Analytical Chemists (AOAC). In this study, peak area integration (PAI), partial least squares regression (PLSR), and principal component regression (PCR) were used as the calibration techniques. PV obtained by the AOAC method and by FTIR-ATR technique were well correlated considering the peak area related to trans double bonds and chemometrics techniques of PLSR and PCR. Calibration model was established using the band with a peak point at 966 cm⁻¹ (990-940 cm⁻¹) related to C-H out of plane deformation vibration of trans double bond. Algae oil oxidation could be successfully quantified using PAI, PLSR and PCR techniques. Additionally, hierarchical cluster analysis was performed and significant discrimination was observed coherently with oxidation process.
The article presents the results of spectroscopic studies of two compounds from the 1,3,4-thiadiazole group, i.e. 4-(5-methyl-1,3,4-thiadiazole-2-yl)benzene-1,3-diol (C1) and 4-(5-heptyl-1,3,4-thiadiazole-2-yl)benzene-1,3-diol (C7), present at different molar concentrations in DPPC liposome systems. In the case of both investigated compounds, fluorescence measurements revealed the presence of several emission bands, whose appearance is related to the molecular organisation induced by changes in the phase transition in DPPC. Based on the interpretation of FTIR infrared spectroscopy spectra, we determined the molecular organisation of the analysed compounds in multilayers formed of DPPC and the 1,3,4-thiadiazoles. It was found that the compound with a longer alkyl substituent both occupied the lipid polar head region in the lipid multilayer and interacted with lipid hydrocarbon chains. In turn, the compound with a shorter alkyl substituent interacted more strongly with the membrane polar region. Based on the knowledge from previous investigations conducted using different solvents, the fluorescence effects observed were related to the phenomenon of molecular aggregation. The effects were strongly influenced by the structure of the compound and, primarily, by the type of the alkyl substituent used in the molecule. The substantial shortening of fluorescence lifetimes associated with the effect of longwave emission (with a maximum at 505 nm) decay also confirms the model of aggregation effects in the analysed systems. Similar effects can be very easily distinguished and associated with respective forms of the compounds in biologically relevant samples.