Abstract and keywords
Abstract (English):
Introduction. Our study aimed to apply medium infrared (MIR/FTIR) spectroscopy to evaluate the quality of various sports supplements available in the Polish shops and gyms. Study objects and methods. The study objects included forty-eight sports supplements: whey (15 samples), branched-chain amino acids (12 samples), creatine (3 samples), mass gainers (6 samples), and pre-workouts (12 samples). First, we determined the protein quantity in individual whey supplements by the Kjeldahl method and then correlated the results with the measured FTIR spectra by chemometric methods. The principal component analysis (PCA) was used to distinguish the samples based on the measured spectra. The samples were grouped according to their chemical composition. Further, we correlated the spectra with the protein contents using the partial least squares (PLS) regression method and mathematic transformations of the FTIR spectral data. Results and discussion. The analysis of the regression models confirmed that we could use FTIR spectra to estimate the content of proteins in protein supplements. The best result was obtained in a spectrum region between 1160 and 2205 cm–1 and after the standard normal variate normalization. R2 for the calibration and validation models reached 0.85 and 0.76, respectively, meaning that the models had a good capability to predict protein content in whey supplements. The RMSE for the calibration and validation models was low (2.7% and 3.7%, respectively). Conclusion. Finally, we proved that the FTIR spectra applied together with the chemometric analysis could be used to quickly evaluate the studied products.

Spectroscopy, FTIR, medium-infrared, chemometric, PCA, PLS, sports supplements, whey, creatine, BCAA, gainers, pre-workouts
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Food supplements are concentrated sources of
nutrients (i.e. minerals and vitamins) or other substances
with a nutritional or physiological effect that are
marketed in “dose” form (e.g. pills, tablets, capsules,
or liquids in measured doses) [1]. In the EU, food
supplements are regulated as foods. Therefore, it is the
responsibility of the manufacturer, importer, supplier
or distributor to ensure the safety of food supplements
placed on the market.
The use of dietary supplements is mainly widespread
in sport. People are continually searching for
supplements to help them lose weight, boost energy, and
build muscles. There are some supplements which are
commonly used to achieve these goals [2].
One of them is a whey protein supplement, the
most important nutrient to boost athletic performance.
Whey protein is popular among athletes, bodybuilders,
fitness models, as well as people seeking to improve
their performance in the gym. Numerous studies show
that it can help increase strength, gain muscle, and lose
significant amounts of body fat [3, 4]. Some specific
types of protein are made for certain scenarios, such
as casein protein for a slow-release protein and whey
protein for a faster release. The main types of whey
protein are concentrates (WPC), isolates (WPI), and
hydrolysates (WPH).
The branched-chain amino acids (BCAAs) –
leucine, iso-leucine, and valine – are among the nine
essential amino acids for humans that account for 35%
of essential amino acids in muscle proteins. They are
unique as the only amino acids used directly by muscles
as energy during exercise [5].
Wójcicki K. Foods and Raw Materials, 2020, vol. 8, no. 1, pp. 177–185
The next commonly used supplement in sport is
creatine which increases lean body mass, skeletal muscle
strength, as well as muscle power and endurance [6].
Creatine supplementation appears to raise the creatine
level in muscle cells and cause weight gain through
an increase in lean body mass with no effect on fat
mass [7, 8].
Pre-workout supplements are multi-ingredient
dietary formulas designed to boost energy and athletic
performance. While some pre-workout supplements have
carbohydrates, most are carbohydrate- and calorie-free.
Others contain caffeine, beet juice, or amino acids, such
as arginine, citrulline, and ornithine, to increase blood
flow to the muscles.
Mass gainers are products mostly directed for
men who find it difficult to build lean muscle mass.
They contain high amounts of calories, as well as
carbohydrates and protein, making them a perfect meal
replacement for people with quick metabolism.
Due to increased consumption of sports supplements
and EU regulations, there is a need for a quick and
precise method to evaluate their quality. The defects
of traditional measurements create a possibility of
adulteration. For example, the commonly used the
Kjeldahl method, which determines protein content in
samples, is time-consuming and unable to distinguish
the protein nitrogen from the non-protein nitrogen [9].
Nowadays, adding inexpensive amino acids and amino
acid derivatives to protein supplements to modify their
content has become a common adulteration method
which is hard to detect [9]. Moreover, dishonest
producers provide incorrect information on the
packaging regarding the amounts of ingredients.
Some methods have been proposed to ensure the
quality of sports supplements. Jiao et al. used the Raman
spectroscopy combined with multivariate analysis for
rapid detection of adulterants in whey protein [8]. High
values of R2 and low errors of prediction for partial
least squares (PLS) analysis prove that it could be
used to detect adulterants in WPC. Champagne and
Emmel demonstrated the Fourier transform infrared
(FTIR) with attenuated total reflectance (ATR) as
a tool for detecting adulteration in raw materials of
dietary supplements [10]. The researchers proved that
vibrational spectroscopy could be used to identify the
presence of known adulterants intentionally spiked into
dietary ingredients, including erectile dysfunction drugs,
steroids, weight loss drugs, and Melamine.
Pereira et al. proposed using fluorescence
spectroscopy to detect and characterize adulterated
whey protein supplements [11]. The adulteration was
performed by adding creatine, caffeine, and lactose
to WPC samples at different levels (10%, 20%, and
30% w/w). The time-resolved fluorescence analysis
showed increased mean intensity lifetime in all
adulterated samples, compared to pure WPC. This study
proved that fluorescence spectroscopy was able to evince
adulteration in WPC powders.
Another use of the fluorescence technique was
reported by Pulgarin et al. [12]. The authors used the
emission spectroscopy to characterize several whey
samples subjected to different treatments and conditions.
Their results indicated that the fluorescent amino acids,
tyrosine and tryptophan, were responsible for the
intrinsic fluorescence of whey. Martin et al. predicted
the protein content in single wheat kernels using
hyperspectral imaging, while Ingle at al. applied NIR
spectroscopy to determine the protein content in powder
mix products [13, 14].
High-performance liquid chromatography (HPLC)
is one of the most common techniques used to
determine the concentration of ingredients. The HPLC
technique was applied by several authors to measure the
concentration of taurine, caffeine or vitamins in energy
drinks [15–17]. These studies exemplify a growing
demand for new, more efficient techniques to assess the
quality of food products and their ingredients. Compared
to conventional techniques or chromatography analysis,
infrared spectroscopy allows measuring the sample’s
eco-friendliness – without sample preparation or the use
of chemical reagents. In addition, FTIR spectroscopy
can be successfully used in the analysis of amino acid
profiles, as confirmed by [18, 19].
In this study, we applied FTIR spectroscopy coupled
with chemometrics to evaluate the quality of sports
supplements. This method is very efficient as the
spectral profile in one measurement can provide various
information about the product that could not be given by
any conventional technique in common use.
Our main objectives were to create a regression
model using PLS analysis to determine the total
amount of protein in the product and to distinguish
various ingredients by the FTIR spectra and principal
component analysis (PCA).
Samples. Our study objects included forty-eight
samples of sports supplements from different producers:
whey (15 samples), BCAAs (12 samples), creatine
(3 samples), mass gainers (6 samples), and pre-workouts
(12 samples). The samples were in the form of powders
or liquids.
Protein determination. The protein content in whey
protein samples was assessed by the Kjeldahl method,
using a conversion factor of total nitrogen to protein
(6.38 for milk products, 6.25 for meat products, and 5.70
for vegetables) [20]. Three parallel trials were performed
for each sample. The percentage of protein in a sample
(X) was calculated according to the formula [20]:
X= (a ∙ n ∙ 1.4 ∙ f )/m
where a is the amount of the standard solution of
hydrochloric acid used for titration of ammonia in a
specific sample, cm3; n is the molar concentration of
hydrochloric acid used for titration; m is the sample
Wójcicki K. Foods and Raw Materials, 2020, vol. 8, no. 1, pp. 177–185
mass, g; f is the conversion factor of total nitrogen to
protein (6.38 for milk products, 6.25 for meat products,
and 5.70 for vegetables); 1.4 is the amount of nitrogen
corresponding to 1 cm3 of 0.1 molar solution of
hydrochloric acid, mg.
FTIR measurements. Medium infrared spectra
were performed on a 4700 FTIR spectrometer (Jasco,
Japan). Single beam spectra of the sample were collected
and rationed against the background of air. For each
sample, MIR spectra were recorded from 4000 to
600 cm–1 by co-adding 16 interferograms at a resolution
of 4 cm–1. The measurements were performed in
Data analysis. Principal component analysis
(PCA). Principal component analysis was performed
on the FTIR spectra of whey protein supplements to
distinguish the samples. PCA is a multivariate technique
that linearly transforms an original set of variables into
a substantially smaller set of uncorrelated variables that
represents most of the information in the original data
set. Data for PCA are arranged in a two-way matrix,
in which column vectors represent variables and row
vectors represent the “objects” whose variables are
measured [21]. The PCA analysis was carried out using
Unscrambler X (CAMO, Oslo, Norway) software.
Partial least squares (PLS). The partial least
squares (PLS) regression method was used to determine
the relation between the samples’ spectra and the content
of protein in whey supplements. We selected regions of
spectra and data preprocessing options to optimize the
model. In total, 45 spectra were measured (15 samples
in triplicate). The set of independent variables X was the
FTIR spectra and the set of dependent variables Y was
the protein content. Full cross-validation was applied to
the regression model.
The regression models were evaluated using the
adjusted R2 and the root mean-square error of crossvalidation
(RMSECV), as the term indicating the
prediction error of the model. The quality models were
evaluated by the ratio of the standard deviation of
reference data for the validation samples to the RMSEP
(RPD). The predicted values were compared to the
reference values. The PLS analysis was carried out using
Unscrambler X (CAMO, Oslo, Norway) software.
Protein determination. The protein contents
in whey protein samples (measured by the Kjeldahl
method) are given in Table 1.
The results show that the producers declared
similar values to those marked. For most producers,
the differences from the declared values did not exceed
5 g/100 g of protein, which is considered as acceptable.
The highest difference between the value declared
and that determined by the Kjeldahl method was
observed for three samples. They were from Producer 9
(84.7 g/100 g vs. 73.87 g/100 g), Producer 8 (82 g/100 g
vs. 75.92 g/100 g), and Producer 15 (85 g/100 g vs.
76.73 g/100 g). However, most producers declared the
correct protein value on the package of their products.
Sports supplements spectra in medium infrared
range. The medium infrared absorption spectra of the
sports supplements measured against air are presented in
Fig. 1.
According to the data reported in [23], the absorption
spectra of whey products had two prominent features,
Amide I (about 1650 cm–1) and Amide II (about
1540 cm–1) bands. The former arose primarily from the
C=O stretching vibration and the latter was attributed
to the N-H bending and C-N stretching vibrations of
the peptide backbone. The band with the maximum
absorption at about 3268 cm–1 was assigned to Amide A.
The band at 3000–2825 cm–1 corresponded to the C-H
stretching vibration, while the low intensity bands at
Table 1 Protein content in whey protein samples measured by the Kjeldahl method [22]
Producer Type of protein Declaration, g Determined, g Standard deviation, g
Producer 1 WPC+WPH+WPI 72.72 72.72 1.98
Producer 2 (vegetarian) – 56.7 54.72 0.29
Producer 3 WPI 85 86.30 4.39
Producer 4 WPI+WPC 78.5 81.49 0.28
Producer 5 WPC+WPI+WPH 71 74.18 1.25
Producer 6 WPC+WPI 71 73.04 1.08
Producer 7 WPC+WPI+WPH 63 65.31 1.67
Producer 8 WPC+WPI 82 75.92 2.48
Producer 9 WPI 84.7 73.87 0.91
Producer 10 WPI+WPC 79.2 78.02 1.45
Producer 11 WPC+WPI 71 68.69 0.31
Producer 12 WPC 70 71.08 0.36
Producer 13 WPC+WPI 80 78.21 0.52
Producer 14 WPI 88 85.32 0.81
Producer 15 WPI 85 76.73 0.87
WPI – whey protein isolate, WPC – whey protein concentrate, WPH – whey protein hydrolysate
Wójcicki K. Foods and Raw Materials, 2020, vol. 8, no. 1, pp. 177–185
about 1241 cm–1 and 1100 cm–1 were assigned to the P-O
stretching vibrations [23].
Zhu et al. [24] found that the absorption spectra
of branched chain amino acids (BCAA) showed the
concentration of effective wavelengths of amino acids
(e.g. valine, leucine, isoleucine, and glycine) mainly
in the fingerprint region (500–1700 cm–1). Based on
the literature, we can describe the main bands in these
products. The band with two maximum absorption
peaks at about 1575 cm–1 and 1509 cm–1 could be
assigned to isoleucine [24]. The band with the maximum
at about 1400 cm–1 corresponded to glycine that does not
contain asymmetric carbon atoms [24]. The valine bands
were also observed in the fingerprint region. The band at
665 cm–1 was assigned as a bending mode of CO2. The
bands at about 753 cm–1 and 776 cm–1 were assigned as
wagging and bending of CO2 group, while vibrations
between 900 and 965 cm−1 as mainly due to the C–C
stretching vibration. The medium intensive band at
2817–3000 cm–1 was assigned to the C-H hydroxyl
group [24].
The creatine MIR absorption spectra have not been
widely reported in literature. Based on the chemical
composition of creatine (which is also an organic acid),
we can infer that the creatine spectrum should be similar
to the BCAA spectrum. The differences in the intensity
and shape of some bands are probably due to a high
concentration of aminoacetic acid and guanidine in the
creatine sample.
The pre-workout absorption spectra have not been
widely described in literature either. According to
the studies of caffeine determination in Singh et al. or
Abdalla, pre-workouts containing caffeine have some
typical bands for that component [25, 26]. Thus, it could
be used to confirm the presence of this ingredient in the
Principal component analysis (PCA). The PCA
was used to distinguish the medium infrared spectra
obtained from different types of sports supplements.
The PCA data were plotted on a graph of first principal
component (PC1) vs. second principal component
(PC2), as shown in Fig. 2. The PCA was conducted for
all the products and for groups of products. The results
were diversified into (1) all supplements, (2) protein
supplements, (3) creatine supplements, (4) BCAAs, (5)
mass gainers, and (6) pre-workout supplements (Fig. 2).
Sports supplements are products to which producers
add various mixes of ingredients depending on market
needs and prevailing trends. These ingredients may
include vitamins, minerals, herbs, and amino acids.
In our study, we applied the PCA analysis to the
spectra acquired from forty-eight samples which
were measured in triplicate and then averaged. For the
whole spectrum (4000–400 cm–1), the first and second
principal components (PC1 and PC2) described 78% of
total variation (61% and 17%, respectively), as shown in
Fig. 2a.
Based on the data in Fig. 2a, we identified three
main groups of products. The first one included products
characterized by positive values of PC1 and negative
values of PC2 (BCAAs and pre-workouts). These
products differed from the others in their physical state
(they were liquids). The second group was products
which primarily contained proteins and amino acids.
They included mostly proteins, mass gainers, and
creatine. The third group (mostly with a positive PC1)
was composed of BCAAs and pre-workouts. The main
ingredient in these products was branched amino acids.
Figure 1 Absorption spectra of sports supplements in medium infrared region (4000–600 cm–1) [22]
Wójcicki K. Foods and Raw Materials, 2020, vol. 8, no. 1, pp. 177–185
The PCA results for protein supplements are
presented in Fig. 2b. For the whole spectrum, the first
and second principal components described 93% of
total variation (53% and 40%, respectively). Based on
the distribution of the samples, we distinguished three
groups of protein products. The first group included
supplements with high amounts of whey protein
isolate (WPI) and negative values of PC1. The second
group contained supplements made from whey protein
concentrate and characterized by positive PC1 and PC2.
Finally, the third group included products based on
green protein (plant proteins for vegans) with positive
PC1 and negative PC2.
Fig. 2c presents the PCA results for creatine samples.
According to the data, creatine with the addition of
caffeine was characterized by positive values of PC1
and PC2. Pure creatine and creatine with additives were
in the opposite sites (negative values of PC1) and close
The PCA results for BCAA supplements are shown
in Fig. 2d. The first and second principal components
described 96% of total variation (90% and 6%,
respectively). Based on the distribution of samples, we
identified three main groups of BCAA products. Fluid
BCAAs were characterized by negative values of PC1
and positive values of PC2. Solid samples had a positive
Figure 2 PCA results for medium infrared spectra of sports supplements. Scores plot for two significant principal components:
PC1 vs PC2. (a) all samples and full spectra at 4000–600 cm–1; (b) proteins; (c) creatines; (d) BCAA; (e) gainers;
(f) pre-workouts [22]
(c) (d)
(а) (b)
(e) (f)
Wójcicki K. Foods and Raw Materials, 2020, vol. 8, no. 1, pp. 177–185
PC1. Pure glutamine was in the quarter which had a
positive PC1 and a negative PC2. We also found some
BCAA samples with additives in that quarter. According
to the information on the packaging, these samples
contained glutamine. The rest of the BCAA supplements
(with positive values of PC1 and PC2) were samples
without glutamine.
Fig. 2d features the PCA results for mass gainer
supplements. We found that the first and second
principal components described 83% of total variation
(64% and 19%, respectively). Based on the data, we
distinguished two groups of gainers. The first group
was characterized by negative values of PC1 while the
second, by positive values of PC1. Due to insufficient
information on the packaging, it was hard to determine
the differences between them. It is worth emphasizing
that group A contained supplements from various
producers, while group B had only two products of the
same producer. In addition, the products in group B
could be found on a low-price shelf on the market.
The last group of sports supplements exposed to
PCA included pre-workout products (Fig. 2e). The first
and second principal components described 93% of total
variation (70% and 23%, respectively). We identified
two groups of pre-workout supplements. The first group
included liquid samples with negative values of PC1,
while the second contained solids with positive values
of PC1. The samples in the second group differed from
each other in the amount of caffeine. Those with lower
amounts of caffeine had negative values of PC2, while
those with higher amounts of caffeine had positive
values of PC2.
Partial least squares regression (PLS). PLS was
used to quantitatively evaluate the concentration of
protein in whey protein supplements based on their
spectral characteristics. Different types of mathematical
pre-processing were applied to the spectra before
building the model. First, we analyzed complete spectra
in all the spectral regions. Next, we chose specific subregions,
relying on the regression coefficients for the
complete spectra and the chemical information in the
specific sub-regions (Fig. 3).
The PLS regression results for the full spectrum
(4000–400 cm–1) without any pretreatment revealed
a correlation between the spectra and the protein
composition. R2 for the calibration and validation models
amounted to 0.76 and 0.62, respectively. It meant that
the models had a medium-good capability to predict the
protein content in whey supplements. The RMSE for the
calibration and validation models was also low (3.5%
and 4.7 %, respectively), confirming their medium-good
quality (Fig. 3a). The regression results were improved
when specific spectral regions were used instead of the
complete spectra. R2 for the calibration and validation
models reached 0.85 and 0.76, respectively. It meant
that the models had a good capability to predict the
protein content in whey supplements. The RMSE for the
calibration and validation models was also low (2.7%
Figure 3 Predicted versus actual concentration of protein in whey supplements obtained by PLS calibration. (a) full FTIR
spectrum; (b) sub-region: 1467–1600 cm–1; (c) full spectra after SNV normalization; (d) sub-region: 1160–2205 cm–1 after SNV
normalization [22]
(c) (d)
(а) (b)
Wójcicki K. Foods and Raw Materials, 2020, vol. 8, no. 1, pp. 177–185
and 3.7%, respectively), confirming the good quality of
the models (Fig. 3b).
Next, we performed the mathematical preprocessing
of the spectra (using SNV normalization).
R2 for the calibration (full spectrum) and validation
models equaled 0.73 and 0.54, respectively. The RMSE
was also low (3.7% and 5.2%, respectively), which
confirmed that the quality of the models was mediumgood
(Fig. 3c). The regression results were improved
when specific spectral regions were used instead of the
complete spectra. R2 for the calibration and validation
models amounted to 0.91 and 0.75, respectively. This
suggested a good capability of the models to predict the
protein content in whey supplements. The RMSE for the
calibration and validation models was also low (2.1%
and 3.8%, respectively), which confirmed their good
quality (Fig. 3d).
Based on the results, we found that the rapid
FTIR method had an accuracy comparable to the
Kjeldahl method. The difference between the values
determined by the Kjeldahl method and those predicted
by FTIR was about 1.2 g (Table 2). In addition, our
complementary method offered several advantages:
it is simple, fast (less than a minute) and requires no
chemicals or reagents, compared to traditional methods.
Our study aimed to investigate the potential of
medium infrared (FTIR) radiation in combination with
a multiway analysis in monitoring the quality of sports
supplements. The spectra of selected sports supplements
had a different shape and intensity, depending on the
chemical composition. Based on the characteristic
spectra, the FTIR could be used to confirm the presence
or absence of a given ingredient in the sample.
The results of the PCA analysis (sample distribution)
showed that the FTIR spectra coupled with PCA offered
a promising tool for distinguishing sports supplements
based on their ingredients.
The regression analysis (PLS) indicated that FTIR
spectroscopy could replace the time-consuming Kjeldahl
method as a much faster technique to predict the
concentration of protein in whey supplements that does
not require any reagents.
Thus, we found FTIR spectroscopy to be a promising
approach to quality evaluation of sports supplements.
The author declares that there is no conflict of


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