1. Introduction
There is an increasing interest in the quality of foodstuffs, and agricultural research continues to focus on improving the nutrient profile of food products. Milk is a valuable commodity that is consumed directly, as well as being a minor and major ingredient in many food products [
1]. It is also rich in nutrients, a resource of proteins (2.6–4.2%), vitamins (0.1%), minerals (0.7%), and fatty acids (95–96% of total milk fat), and is considered by many as an essential part of a healthy diet [
2,
3]. In Europe, milk provides 9% of the dietary energy supply, 19% of the dietary protein supply, and between 12–14% of dietary fat supply [
4].
According to the Agriculture and Rural Development, Analysis and Outlook Unit European’s farms produced 172.2 million tonnes of raw milk in 2018, a number that they expect to increase to 179 million tonnes by 2030, but at a slower pace (+0.6%) than in 2008–2019, and represents a year-on-year increase of 1.6 million tonnes (+1% per year on average) [
5]. In Slovenia, dairy farmers produced 564,000 tons of cows’ milk in 2019 (1.2% less than in 2018), and 164,000 tons of drinking milk, which represents a decrease of more than 2% compared to 2018. Despite the decrease, imports increased by almost 13% [
6]. Consumers prefer milk with favorable sensory qualities, such as flavor, which depends on animal management factors, including breed, lactation stage, processing techniques, and diet regime. However, diet is considered the primary and the most sensitive factor responsible for creating a specific milk flavor [
7] and also a significant factor affecting its fatty acid (FA) composition. These differences also reflect differences in regional dairy production systems, and linking a milk product to a specific region is of high importance as a recognition of quality [
1]. Quality linked to geographical origin has created significant interest in building local and regional food systems across Europe, including Slovenia.
Lipid content and FA profile are considered to have an important role in the human diet [
7,
8]. For example, certain milk FAs, such as linoleic and α-linolenic FAs (C18:2ω-6 and C18:3ω-3), are essential and cannot be synthesized by the human body [
2]. Further, a lower proportion of saturated fatty acids (SFA) and a higher proportion of unsaturated fatty acids (UFA), especially polyunsaturated fatty acids (PUFA), is desirable [
9]. The consumption of SFA (especially lauric (C12:0), myristic (C14:0), and palmitic acids (C16:0)) [
9] is associated with cardiovascular disease, while UFAs are considered as beneficial for human health. Other functional food components are omega-3 polyunsaturated FA (ω-3 PUFAs), which improve neurological functions and are essential in early human development years, and conjugated linoleic acid (CLA), which has anti-carcinogenic, anti-diabetic, anti-atherogenic effects [
10,
11].
Farmers can significantly alter the FA composition of milk by managing the nutrition of their dairy cows [
12]. Fresh forages (especially grass) in the diet enhance the concentration of unsaturated FA, such as α-linoleic acid and CLA, and decrease the levels of SFA, while adding grass conservation products (hay or silage) increases the proportion of SFA in milk [
13]. Besides, the total SFA concentration of milk fat is usually lower in summer compared to winter due to the higher consumption of summer forage crops that have a higher content of PUFAs. The higher content of monounsaturated fatty acids (MUFA) and PUFA in milk from cows grazing in highland regions can be attributed to differences in the botanical composition since higher botanical diversity and energy shortage in cows grazing in mountain pastures modifies the bacterial population and lipid accumulation of UFAs in the rumen [
14]. Fatty acid composition of milk fat has also been used as a criterion to detect adulteration of milk, such as the substitution of part of the fat or proteins of plant or animal origin and admixtures of milk of different species. The method to characterize the matrixes according to the animal species can be greatly improved when combined with the content of triacylglycerols [
15].
The effects of feeding regime can also be tracked using stable isotope analysis using isotope ratio mass spectrometry (IRMS). In dairy products, the isotope composition is also primarily determined by the cows’ diet, as well as their metabolisms [
16]. Differences in stable C isotope abundance is mainly the result of the different ingested proportion of feeds derived from C
3 and C
4 plants. The metabolism of C
4 plants, such as corn or sugar, uses a different biosynthetic pathway to fix atmospheric CO
2 compared to C
3 plants (grass and cereals), resulting in the accumulation of the heavier
13C isotope compared to C
3 plants, which leads to higher
δ13C values. These differences also show up in the isotopic composition of FAs [
17,
18]. Since the spectrum of plants used for feeding purposes depends mainly on local soil and climatic condition, stable isotope composition can also encompass information about the geographical origin of dairy products useful for authenticity control.
Up to now, studies have focused on stable isotope ratio measurements of
δ13C,
δ15N, and
δ34S values in casein,
δ2H,
δ18O in milk water [
19,
20,
21,
22] and Sr in dry milk samples [
21]. One of the most recent significant advances has been the development of compound-specific stable isotope analysis (CSIA) that enables the identification of relevant biomarkers, such as fatty acids, in food authenticity studies. Some studies have even looked at the correlation between long-chain FAs (α-linolenic FA-C18:3ω-3, eicosapentaenoic FA-C20:5ω-3) and stable isotope measurements to distinguish between organic and conventionally produced milk [
17,
23]. In another study, the authors investigated the relationship between the carbon isotope compositions of CLA in milk and fatty acids in different dietary sources (C
3 versus C
4 plants) to understand the transformation of FA from diet to milk [
17]. The results suggested that the
δ13C-change in CLA did not originate from the microbial biohydrogenation in the rumen, but most probably from endogenous desaturation of
t11–18:1.
Only a few studies, however, have focused on
δ13C and
δ2H values in milk fatty acids. Ehtesham and co-workers [
24] demonstrated that
δ2H values in precipitation were highly correlated with the
δ2H values in bulk milk and specific fatty acids (butyric, myristic, palmitic, and oleic acid). Separation of milk powder origin to geographic sub-regions within New Zealand has been achieved, with clear discrimination between South Island and North Island and with significant clustering of regions. Further, a linear discriminant analysis (LDA) model based on
δ2H and
δ13C values of butyric, myristic, palmitic, and oleic fatty acids has provided the best separation of samples from the Northern and Southern parts of New Zealand [
1]. Ehtesham et al. [
25] also focused on the relationship between
δ2H and the FAs in milk and the water component of milk (feed and farm water). The authors found that the
δ2H values of FAs in feed and
δ2H values of farm water were related to the
δ2H values of milk FAs, milk solids, and milk water and could be used as a biogeochemical marker surrogate to environmental conditions. This approach can also be applied to determine the dietary regime and geographical origin of milk products where the water has been removed (milk powder) or is altered in the case of processed milk products (cheese and butter).
The main objective of this study was to evaluate both the need and options for origin tracing, focusing on Slovenian milk. In 2016, the Slovenian Ministry of Agriculture, Forestry, and Food began a three-year project to promote and raise awareness of the importance and characteristics of locally produced and processed foods. During this time, the protective mark “Selected Quality” national scheme and the “Selected Quality-Slovenia” was established. Nowadays, most milk and dairy products, produced and processed in Slovenia, use the “Selected Quality - Slovenia” protective mark. This mark indicates that the products have the following distinguishing properties: (i) the origin of raw milk—the milk and other dairy products are produced entirely in the same country, Slovenia; (ii) milk quality—excellent microbiological quality of milk; (iii) freshness of raw milk—it’s 15 h at most from the takeover of milk at the collection site to its acceptance into the processing plant. Therefore, to protect the obtain mark and prevent possible fraud, a robust screening method to determine the authenticity and regional traceability of milk is needed. In this study, two methods (fatty acid composition and isotope ratios of carbon within fatty acids) were applied. Additionally, the effect of the production year and season on the FA composition of milk was also investigated. Finally, the FA profiles pertaining to the milk’s essential and beneficial components were also studied, and a comparative study was made to examine the differences in the quality of milk from different geographic regions in Slovenia.
3. Materials and Methods
3.1. Milk Collection and Storage
During a 3-years study (from 2012 to 2014), in total, 231 raw cow milk samples were collected. Samples were collected twice per year in winter and summer from four geographical regions in Slovenia: Mediterranean (n = 18), Pannonian (n = 90), Dinaric (n = 51), and Alpine (n = 72). Samples were collected from five Slovenian dairies, each supplied by milk from different farms and transported to the laboratory. The geographical characterization of the sampling location: latitude, longitude, altitude, and the number of samples in each location can be found in the
supplementary material (Table S2). Each sample was divided into four subsamples and stored in plastic containers at −20 °C. Sampling data is shown in
Table 4.
3.2. Chemicals and Standards
Dichloromethane (CH2Cl2, for organic residue analysis), methanol (MeOH, for organic residue analysis), and hexane (C6H14, for organic residue analysis) were purchased from J. T. Baker B. V. (Deventer, Netherlands). Sodium hydroxide (NaOH, puriss. p.a., ACS reagent, reag. Ph. Eur., ≥98%, pellets) and boron trifluoride-methanol solution (14% in methanol) were obtained from Sigma-Aldrich (St.Louis, MI, USA). Deionized water (18.2 MΩ) was made using a Mili-Q System (Merck Millipore, Watertown, MA, USA). A standard mixture from Supelco (Bellefonte, PA, USA), named Supelco 37 Component FAME Mix in dichloromethane, containing the methyl esters of 37 fatty acids, was used.
The accuracy of the δ13C determination was checked with the following international reference materials: polyethlene foil IAEA-CH-7 (δ13C = −32.15 ± 0.04‰) and sucrose IAEA-CH-6 (δ13C = −10.45 ± 0.03‰) obtained from International Atomic Energy Agency (IAEA, Vienna, Austria), L-glutamic acids USGS40 (δ13C = −26.39 ± 0.04‰) obtained from U.S. Geology Survey (USGS, Virginia, USA) and laboratory reference materials: casein IAEA-CRP 2013 (δ13C = −20.3 ± 0.09‰) (IAEA, Vienna, Austria), UreaC (δ13C = −28.3 ± 0.2‰), and fatty acid methyl nanodecanoate (δ13C = −30.0 ± 0.1‰) (Restek, Bellefonte, PA, USA).
3.3. Analytical Procedures
3.3.1. Extraction and Esterification of Milk FAs
Frozen milk samples were thawed (37 °C) and homogenized. Milk fat consists predominantly of triacylglycerides, which were extracted using the in-situ-trans-esterification method without prior extraction of the fat from samples according to the method of Park and Goins (1994). The total lipids fraction was extracted from the milk samples (450 µL) with dichloromethane (300 µL) and 0.5 M sodium hydroxide in methanol (3 mL), purged with nitrogen and heated at 90 °C for 10 min, after which the samples were cooled rapidly. Fatty acid methyl esters (FAMEs) were formed by adding 14% BF3-methanol solution (3 mL) and heating the sample at 90 °C for a further 10 min. After cooling, the fatty acids methyl esters (FAMEs) were extracted with hexane (1.5 mL) and transferred to a GC vial and stored at −20 °C.
3.3.2. Gas Chromatography of Fatty Acids
The characterization of FAMEs was performed using Agilent 6890N (Network GC System, Agilent Technology, Santa Clara, CA, USA) gas chromatography with FID detector (GC-FID). The separation was achieved on an Omegawax 320, 30 m × 0.32 mm, × 0.25 µm, on a capillary column (Supelco, Bellefonte, PA, USA). The temperature program was as follows: 50 °C (held 2 min) to 220 °C at 4 °C/min (held 20 min). The carrier gas was helium in constant flow mode (1 mL/min). The injector was set to 260 °C and the detector to 280 °C. The individual fatty acids were identified and quantified by comparing their retention times with those of a standard Supelco 37 component FAME Mix (Supelco) and expressed in weight percent of total fatty acids. Procedural blanks were analyzed with each set of samples. Standard Supelco 37 component FAME mix was analyzed after every ten samples to verify the stability of the analytical system. Method precision based on measurements of replicate (n = 2) real samples was 5%. Results were expressed as the percentage of each fatty acid with respect to the total fatty acids [
45]. This percentage was calculated using the peak area of the samples corrected with the respective correction factors, according to Christie and Han [
46].
3.3.3. Elemental Analysis-Isotope Ratio Mass Spectrometry (EA-IRMS)
The stable carbon isotope ratio measurements were reported in
δ—notation expressed in per mile (‰) relative to the Vienna-Pee Dee Belemnite (V-PDB) standard following Equation (1) [
47]:
where superscripts
i and
j denote the highest and the lowest atomic mass number of element E, and
RP and
RRef is the ratio between the heavier and the lighter isotopes (in case of carbon,
13C/
12C) in the sample (
P) and reference material (
Ref).
To determine the bulk carbon isotope composition, approximately 1 mg of freeze-dried milk was weighed into a tin capsule, closed with tweezers, and placed into the automatic sampler of the elemental analyzer. All analyses were performed separately on a Europa Scientific 20–20 continuous flow mass spectrometer with an ANCA-SL solid–liquid preparation module (Sercon, Crewe, UK). Analyses were normalized against international standards: IAEA-CH-7 and IAEA-CH-6 with δ13C values of −32.15 ± 0.04‰ and −10.45 ± 0.04‰, respectively. For independent control, laboratory reference material IAEA-CRP 2013 with δ13C value −20.3 ± 0.09‰ and UreaC with δ13C value −28.3 ± 0.2‰ were used. The analytical precision, expressed as the standard deviation of control material, was ± 0.2‰.
The 13C/12C ratio of synthetic fatty acid standard C19:0 (methyl nanodecanoate, RESTEK) was determined using a Europa Scientific 20–20 continuous flow mass spectrometer with an ANCA-SL solid–liquid preparation module (Sercon, Crewe, UK). Results were further normalized against two international reference standards: IAEA-CH-7 and IAEA-CH-6. For independent control, the international reference material USGS40 with δ13C values of −26.39 ± 0.04‰ was used. Analytical precision, expressed as the standard deviation of the control materials, was ± 0.2‰.
3.3.4. Compound Specific Isotope Analysis of δ13C in Fatty Acids
The Isotopic compositions of individual FA were determined using an Agilent 6890N GC-C system coupled to an IsoPrime GV IRMS (GV Instruments, Manchester, UK)). The separation was achieved using a DB-1MS (60 m × 0.32 mm × 0.25 µm) capillary column (Agilent J&W, USA). The temperature program was as follows: 120 °C (held 1 min) to 300 °C (held 20 min) at 3 °C/min. The carrier gas was helium in the constant flow mode (1 mL/min). The injector temperature was 260 °C, and the oxidation reactor (Cu/O) in the 6890N GC/C system was 900 °C. Peak identification of individual fatty acids was performed by comparing their retention times with those in the standard Supelco 37 component FAME Mix, which was analyzed in the measurement sequence. Instrument stability was ≤0.08‰. C19:0 FAME (methyl nanodecanoate) with
δ13C values of −30 ± 0.1‰ (prior determined on EA-IRMS) was used as a laboratory reference material. For data normalization, a single-point normalization method was used [
48]. The precision of measurements expressed as the standard deviation of the laboratory reference material was 0.3 to 0.5‰.
3.4. Statistical Evaluation
For statistical evaluation, FAs were considered individually and grouped in classes as follows: saturated fatty acids (SFA), unsaturated fatty acids (UFA), MUFA, ω-3 PUFA, ω-6 PUFA, and CLA. Statistical calculations and multivariate analysis were carried out using the XLSTAT software package (2020.1.3, Addinsoft, New York, NY, USA). The statistical evaluation was performed using R, where non-parametric tests were used, i.e., Kruskal–Wallis followed by a post hoc test. In the case of pairwise comparison, a Mann–Whitney test was used. Basic statistics included mean values (median and arithmetic mean), standard deviation (SD), minimum and maximum, while for multivariate analysis, discriminant analysis (DA) was used.
