The Provenance of Slovenian Milk Using 87Sr/86Sr Isotope Ratios

This work presents the first use of Sr isotope ratios for determining the provenance of bovine milk from different regions of Slovenia. The analytical protocol for the determination of 87Sr/86Sr isotope ratio was optimised and applied to authentic milk samples. Considerable variability of 87Sr/86Sr ratios found in Slovenian milk reflects the substantial heterogeneity of the geological background of its origin. The results, although promising, cannot discount possible inter-annual or annual variation of the Sr isotopic composition of milk. The 87Sr/86Sr ratios of groundwater and surface waters are in good correlation with milk, indicating that the Sr isotopic fingerprint in milk is reflective of cow drinking water. The 87Sr/86Sr ratio has the potential to distinguish between different milk production areas as long as these areas are characterised by geo-lithology. Discriminant analysis (DA) incorporating the elemental composition and stable isotopes of light elements showed that 87Sr/86Sr ratio together with δ13Ccas and δ15Ncas values have the main discrimination power to distinguish the Quaternary group (group 6) from the others. Group 1 (Cretaceous: Carbonate Rocks and Flysch) is associated with Br content, 1/Sr and δ18Ow values. The overall prediction ability was found to be 63.5%. Pairwise comparisons using OPLS-DA confirmed that diet and geologic parameters are important for the separation.


Introduction
Proof of provenance has increased in relevance over the past decade because of its positive impact on food safety, quality and consumer protection per national legislation and international standards and guidelines. This trend also coincides with an increase in consumer demand for local and regional food, which is considered higher quality, safer and more sustainable. This has created interest in building local and regional food systems across Europe, including Slovenia. Most milk and dairy products, produced and processed in Slovenia, now use the "Selected Quality-Slovenia" mark, which indicates that the product is of Slovenian origin. The characteristics of milk are highly dependent on the farming practices and the soil where cattle graze, thereby, from the geographical region, reflecting specific and peculiar geologic information. Consequently, the geographic origin of milk and dairy products is an important factor affecting quality.
The geographical origin of milk and especially dairy products has been frequently traced by using stable isotope analysis of light elements (δ 2 H, δ 13 C, δ 15 N, δ 18 O and δ 34 S) [1][2][3][4] or in combination with the multi-elemental analysis [5][6][7][8]. Recently, isotopic information from heavy elements in soil and food has been explored for its potential to serve as reliable geographical tracers for food origin. In particular, the isotopic composition of strontium (Sr) has proven to be a promising tool for discriminating at a regional level. It  [31] with dairy farm locations ( Table 1). The map was prepared by J. Vrzel.

87 Sr/ 86 Sr Isotope Ratio in Authentic Slovenian Milk
Although milk contains about 87% of water, its proteins, carbohydrates, and especially fat make its matrix very complex in the Sr isotope analysis. If not adequately destroyed, organic remnants can irreversibly adsorb on the extraction resin, thus reducing its exchange capacity and leading to a reduction in the Sr recovery and possibly to isotopic fractionation. The method was optimised in terms of completeness of mineralisation, chemical recovery of Sr isolated from the sample matrix (Table S2), minimal contamination, and turnaround time. The blanks of analyte-free media were prepared using the same materials and reagents as for the samples. A procedure for optimisation and validation of the analytical method for accurate 87 Sr/ 86 Sr isotope ratio measurement in milk is fully described in Supplementary Materials with Tables S1-S5, while the analytical protocol is presented in Figure 2.
In summary, as presented in Figure 2, for pretreatment of the milk samples, 0.30 g were subjected to microwave digestion and then evaporated to dryness and redissolved in 1 mL of 8M HNO3. A column (2 mL) was filled with 0.30 g resin, activated by washing with HCl. The resin was acidified with 3 mL HNO3 before sample loading to prevent any loss of Sr. Subsequently, the sample solution was loaded onto the column. Rb was eluted with 5 mL of 8M HNO3, after which the Sr was collected in purified water washes ( Table   Figure 1. Geological map of Slovenia as indicated [31] with dairy farm locations ( Table 1). The map was prepared by J. Vrzel. The climatic conditions in Slovenia do not allow year-round grazing on outdoor pastures. Additionally, the landscape is diverse, where not all areas allow the growing of appropriate feed, so the geographical origin of winter feed may change. Both circumstances are responsible for the change in the cow's diet. To evaluate these changes, milk samples were sampled during summer and winter in 2014 and the winter of 2015. Further, the elemental and stable isotopic composition of light elements (H, C, N, O and S) of authentic milk samples was determined to characterise authentic Slovenian milk.

87 Sr/ 86 Sr Isotope Ratio in Authentic Slovenian Milk
Although milk contains about 87% of water, its proteins, carbohydrates, and especially fat make its matrix very complex in the Sr isotope analysis. If not adequately destroyed, organic remnants can irreversibly adsorb on the extraction resin, thus reducing its exchange capacity and leading to a reduction in the Sr recovery and possibly to isotopic fractionation. The method was optimised in terms of completeness of mineralisation, chemical recovery of Sr isolated from the sample matrix (Table S2), minimal contamination, and turnaround time. The blanks of analyte-free media were prepared using the same materials and reagents as for the samples. A procedure for optimisation and validation of the analytical method for accurate 87 Sr/ 86 Sr isotope ratio measurement in milk is fully described in Supplementary Materials with Tables S1-S5, while the analytical protocol is presented in Figure 2. ). The Sr solution was then evaporated and purified again through extraction separation. Finally, the 87 Sr/ 86 Sr isotope ratios were determined using MC ICP-MS. Isotope Analysis Using MC ICP-MS Strontium isotope ratio determinations were carried out using a Nu II multi-collector ICP-MS instrument (Nu Instruments, Ametek Inc., Wrexham, UK) fitted to an Aridus II TM Desolvating Nebulizer System (Teledyne Cetac, Omaha, NE, USA) by the procedure of Zuliani et al. (2020) [32]. All samples were run in a standard-sample-standard bracketing sequence using standard Sr isotopic solution (NIST SRM 987: Strontium carbonate; 87 Sr/ 86 Srcertfied = 0.71034 ± 0.00026; National Institute of Standards and Technology, Gaithersburg, MD, USA).

Multi-Elemental Analysis Using EDXRF
The multi-elemental composition of milk, including Sr stable isotope ratio, was performed using freeze-dried and homogenised milk samples. Energy-dispersive X-ray fluorescence spectrometry was used to determine the following elements: calcium (Ca), chloride (Cl), potassium (K), phosphorus (P), sulphur (S), bromide (Br), rubidium (Rb), and strontium (Sr). Each milk sample (0.5-1.0 g) was pressed into a pellet using a hydraulic In summary, as presented in Figure 2, for pretreatment of the milk samples, 0.30 g were subjected to microwave digestion and then evaporated to dryness and redissolved in 1 mL of 8M HNO 3 . A column (2 mL) was filled with 0.30 g resin, activated by washing with HCl. The resin was acidified with 3 mL HNO 3 before sample loading to prevent any loss of Sr. Subsequently, the sample solution was loaded onto the column. Rb was eluted with 5 mL of 8M HNO 3 , after which the Sr was collected in purified water washes (Table S4). The Sr solution was then evaporated and purified again through extraction separation. Finally, the 87 Sr/ 86 Sr isotope ratios were determined using MC ICP-MS.
Isotope Analysis Using MC ICP-MS Strontium isotope ratio determinations were carried out using a Nu II multi-collector ICP-MS instrument (Nu Instruments, Ametek Inc., Wrexham, UK) fitted to an Aridus II TM Desolvating Nebulizer System (Teledyne Cetac, Omaha, NE, USA) by the procedure of Zuliani et al. (2020) [32]. All samples were run in a standard-sample-standard bracketing sequence using standard Sr isotopic solution (NIST SRM 987: Strontium carbonate; 87 Sr/ 86 Sr certfied = 0.71034 ± 0.00026; National Institute of Standards and Technology, Gaithersburg, MD, USA).

Multi-Elemental Analysis Using EDXRF
The multi-elemental composition of milk, including Sr stable isotope ratio, was performed using freeze-dried and homogenised milk samples. Energy-dispersive X-ray fluorescence spectrometry was used to determine the following elements: calcium (Ca), chloride (Cl), potassium (K), phosphorus (P), sulphur (S), bromide (Br), rubidium (Rb), and strontium (Sr). Each milk sample (0.5-1.0 g) was pressed into a pellet using a hydraulic press. As primary excitation sources, the annular radioisotope excitation sources of Fe-55 (10 mCi) and Cd-109 (20 mCi) from Isotope Products Laboratories (Valencia, CA, USA) were used. The emitted fluorescence radiation was measured using an energy dispersive X-ray spectrometer composed of a Si(Li) detector (Canberra Industries, Meriden, CT, USA), a spectroscopy amplifier (M2024, Canberra Industries, Meriden, CT, USA), ADC (M8075, Canberra Industries, Meriden, CT, USA) and PC based MCA (S-100, Canberra Industries, Meriden, CT, USA). The spectrometer was equipped with a vacuum chamber. The energy resolution of the spectrometer was 175 eV at 5.9 keV. An analysis of the X-ray spectra was made using the AXIL (IAEA, Vienna, Austria) spectral analysis program [33,34].
Sample preparation and the analytical procedure were critically tested and evaluated according to uncertainty, accuracy, and limits of detection (LOD) in our previous investigation [35].

Isotope Ratio Mass Spectrometry (IRMS) Measurements
Stable isotope ratio measurements were performed using isotope ratio mass spectrometry (IRMS) and reported using the δ-notation in ‰ using Equation (1) [36]: where superscripts i and j denote the highest and the lowest atomic mass number of element E, and R P and R Ref indicate the ratio between the heavier and the lighter isotope ( 2 H/ 1 H, 13 C/ 12 C, 18 16 O ratio in milk water (δ 18 O w ) was determined directly in milk using the equilibration method where the sample was purged with a reference CO 2 /He gas (5% CO 2 , 95% of He) at 40 • C for three hours. Measurements were performed using a Multiflow system (IsoPrime, Cheadle Hulme, Manchester, UK) connected to a continuous flow IRMS (GV Instruments, Manchester, UK). Analyses were calibrated against two internal laboratory reference materials: Snow water (δ 18 O = −19.73 ± 0.02‰) and seawater (δ 18 O = −0.34 ± 0.02‰). For independent control, laboratory reference material Milli-Q water was used as control material (δ 18 O = −9.12 ± 0.04‰). The internal laboratory and independent laboratory reference materials were calibrated against international reference materials: V-SLAP2 (Standard Light Antarctic Precipitation, δ 18 O = −55.5 ± 0.02‰) and V-SMOW (Vienna-Standard Mean Ocean Water 2, δ 18 O = 0 ± 0.02 ‰).
Further, 13 C/ 12 C, 15 N/ 14 N and 34 S/ 32 S ratios were determined in casein samples. Milk fat was removed by centrifugation (Type Centric 322 A, TEHTNICA, Železniki, Slovenia, 10 min at 3200 rpm), and casein by precipitation from the skimmed milk by acidification at pH 4.3 with 2M HCl (Carlo Erba, Val de Reuil, Italy) followed by centrifugation for 10 min at 3200 rpm. The precipitate was rinsed twice with Milli-Q water (Millipore, Burlington, MA, USA), followed by acetone and petroleum ether (Carlo Erba, Val de Reuil, Italy) and freeze-dried [37].
The freeze-dried casein sample was transferred to a tin capsule, closed with tweezers and placed into the autosampler of the elemental analyser. For 13 C/ 12 C, 15

Statistical Analysis
All samples were prepared in triplicate, and the data are presented as mean with standard deviation (SD) of triplicate independent experiments. Statistical analysis was performed using the XLSTAT software package (Addinsoft, New York, NY, USA). Simple statistical analyses were carried out, including an analysis of variance (ANOVA) with the Mann-Whitney (MW) and Kruskal-Wallis (KW) tests, since the data are not normally distributed. Furthermore, to determine the key factors responsible for differentiation of the region of the geographical origin of milk, a discriminant analysis (DA) was used. Moreover, orthogonal partial least squares discriminant analysis (OPLS-DA) was introduced for pairwise comparisons among two overlapping geological groups using the SIMCA ® software package (Umetrics, Umea, Sweden).

Strontium Isotope Ratio of Authentic Slovenian Milk
The first values for the 87 Sr/ 86 Sr ratio in Slovenian milk samples (n = 77) are presented in Table 1. Slovenia is a relatively small country covering a mere 20,273 km 2 but boasts great diversity in complex geology, relief, hydrological systems, and vegetation. Unfortunately, this diversity was not observed to the same extent in the analysed milk samples.
The 87 Sr/ 86 Sr ratios in the milk samples collected from farms at different locations showed a moderate degree of variation, spanning from 0.708 to 0.713. When comparing the 87 Sr/ 86 Sr ratios between samples collected during summer and winter seasons of 2014 (Table 1), a certain degree of variability for some samples was observed; however, the differences were not statistically significant (Mann-Whitney; p = 0.9623). Further, no statistical difference was observed in 87 Sr/ 86 Sr ratios according to the year of production (Mann-Whitney; p = 0.1318). The same conclusion may be drawn from the concentrations of Sr in the milk samples. On the other hand, the reported δ 13 C and δ 15 N data of Slovenian milk reflect intra-annual changes in diet [8].
The Kruskal-Wallis test indicates that only four parameters are significantly related to the geological region (p < 0.001): 87 Sr/ 86 Sr ratios, δ 13 C cas , δ 15 N cas and Br. The relationship between 87 Sr/ 86 Sr ratios in the milk samples and rock type at each sampling location was also explored. The type and age of the soil were obtained from the geological map provided by the Geological Survey of Slovenia [31] (Figure 1). The 87 Sr/ 86 Sr isotope ratios in milk samples studied are in line with the isotopic values predicted for Slovenia, according to Hoogewerff et al. (2019) [38]. By their model, the soil 87 Sr/ 86 Sr ratios of most of Slovenia's central and western parts should be in the range of 0.708 to 0.709. The 87 Sr/ 86 Sr ratios should be higher in the north-eastern part, ranging from 0.710 to 0.712. The values found in milk in the present study are in agreement with the modelled values.
Moreover, this information is in line with the bedrock composition and age. Indeed, most of the Slovenian territory is covered by tertiary and quaternary dolomites, limestones and alluvial deposits such as sandstones and claystones. There is a slight difference between milk samples from locations with quaternary alluvial deposits with alumo-silicate rocks with 87 Sr/ 86 Sr ratios ranging between 0.710 and 0.712, and locations with limestone and dolomite bedrock with 87 Sr/ 86 Sr ratios in the range from 0.708 to 0.710. On closer examination of the regional Slovenian milk samples, the overlap highlights the similarity between the geological and pedological characteristics of originating regions (Figure 3).  butter [24], cheese [27,30], and milk [29,30]. Dots on the vertical lines refer to the results obtained from the literature, whereas lines indicate the span of values. The 87 Sr/ 86 Sr isotope ratios in Slovenian truffles are also presented [39].
A specific pattern among samples was observed when comparing the Sr isotopic and elemental signatures in Slovenian milk samples based on geology (Figure 4)  butter [24], cheese [27,30], and milk [29,30]. Dots on the vertical lines refer to the results obtained from the literature, whereas lines indicate the span of values. The 87 Sr/ 86 Sr isotope ratios in Slovenian truffles are also presented [39].
The data were compared with the Slovenian truffles, which have 87 Sr/ 86 Sr ratios ranging from 0.710 to 0.713 [39]. The values correspond to Slovenian milk samples except for the highest 87 Sr/ 86 Sr ratio of 0.71375 determined in truffles from Bloke, a karst plateau. When comparing the Sr isotopic ratios in dairy products originated from other countries with Slovenian milk, the span of the 87 Sr/ 86 Sr expressed in lower values has been recorded for cheese from Germany and Switzerland [24] and New Zealand [29].
In contrast, the 87 Sr/ 86 Sr ratios in milk and cheese from Quebec vary with a wide range of values, from 0.70961 up to a maximum of 0.71447, indicating a relative enrichment with radiogenic isotope 87 Sr in Proterozoic and during the Paleozoic carbonate intrusive and limestone rocks composing the St. Lawrence Platform [30,40]. The large variability of Sr ratios in dairy products reflects the vast diversity of underlying bedrock and soils formed from them. Therefore, the widely scalable results of Sr ratios reflect the substantial heterogeneity of the geological background of its origin.
A specific pattern among samples was observed when comparing the Sr isotopic and elemental signatures in Slovenian milk samples based on geology (Figure 4). 7 Sr/ 86 Sr isotope ratios in various dairy products from different countries, as reported in the literature. Horilines define the limits of the 87 Sr/ 86 Sr values measured in Slovenian milk of different geological regional icated. References used for various dairy products worldwide: butter [24], cheese [27,30], and milk [29,30]. rtical lines refer to the results obtained from the literature, whereas lines indicate the span of values. The e ratios in Slovenian truffles are also presented [39].
A specific pattern among samples was observed when comparing the Sr isotopic and elemental signatures in Slovenian milk samples based on geology (Figure 4).   Although several samples overlap, two trends can be identified: the first with high Sr concentration and high 87 Sr/ 86 Sr ratios (>0.7110) mainly from areas with quaternary alluvial deposits with alumo-silicate rocks and the second one related to lower 87 Sr/ 86 Sr ratios (<0.7090) at carbonate dominated areas. The overlapping values can be explained by: (i) different weathering rates of specific minerals in the rocks and soils, movement of water and sediments in a grazing area can influence Sr and Rb contents in milk samples leading potentially to different 87 Sr/ 86 Sr isotope ratios [27,41], (ii) the consumption of imported plants, particularly those enriched with high Ca and Sr content, can significantly alter the 87 Sr/ 86 Sr signatures in dairy products, even when consumed in small amounts. Thus, a consideration of total dietary intake is necessary when interpreting 87 Sr/ 86 Sr results.
The second source of Sr in milk is related to the drinking water supply. In Slovenia, most of the drinking water originates from groundwater and especially in the karst regions of the Sava River watershed, where river water represents the primary source of groundwater [42,43]. Therefore, we compared the 87 Sr/ 86 Sr ratios of milk with unpublished data of 87 Sr/ 86 Sr in the Sava, Ljubljanica, Pivka, Kamniška Bistrica and Logaščica rivers and rivulets and those determined in some mineral and spring bottled waters [32]. For comparison, we selected locations that lie close to the rivers for which the 87 Sr/ 86 Sr ratios are available. A good correlation between milk and groundwater data was observed ( Figure 5), indicating that groundwater can represent an important source of Sr.
gions of the Sava River watershed, where river water represents the primary source of groundwater [42,43]. Therefore, we compared the 87 Sr/ 86 Sr ratios of milk with unpublished data of 87 Sr/ 86 Sr in the Sava, Ljubljanica, Pivka, Kamniška Bistrica and Logaščica rivers and rivulets and those determined in some mineral and spring bottled waters [32]. For comparison, we selected locations that lie close to the rivers for which the 87 Sr/ 86 Sr ratios are available. A good correlation between milk and groundwater data was observed ( Figure 5), indicating that groundwater can represent an important source of Sr. However, it is interesting to note that most of the 87 Sr/ 86 Sr values for milk are higher than their corresponding river samples. One of the possible explanations could be the use of agricultural lime for soil improvement in fertile areas present mainly in the eastern part of Slovenia. This part is also known for its intensive agricultural practices where some field areas in specific locations are used to produce fodder plants for feeding livestock. It has been reported that the application of agricultural lime to low-calcareous soils can significantly lower the 87 Sr/ 86 Sr ratio of the watershed [44]. In these areas, maise silage is detected in more than 80% of the milk samples.
Given that the cow's body is up to 70% of water, the 87 Sr/ 86 Sr analysis of local drinking water might be helpful. Livestock in the Pannonian region is fed on the locally produced food, which also confirms the result of milk from Radenci ( 87 Sr/ 86 Sr = 0.71119), matching the 87 Sr/ 86 Sr ratio of the mineral water from the source Radenci (0.71120). This finding aligns with the investigation performed in the Parmigiano Reggiano milk and cheese production area [45]. In her study, the 87 Sr/ 86 Sr isotope ratio on water, whole milk, and diet However, it is interesting to note that most of the 87 Sr/ 86 Sr values for milk are higher than their corresponding river samples. One of the possible explanations could be the use of agricultural lime for soil improvement in fertile areas present mainly in the eastern part of Slovenia. This part is also known for its intensive agricultural practices where some field areas in specific locations are used to produce fodder plants for feeding livestock. It has been reported that the application of agricultural lime to low-calcareous soils can significantly lower the 87 Sr/ 86 Sr ratio of the watershed [44]. In these areas, maise silage is detected in more than 80% of the milk samples.
Given that the cow's body is up to 70% of water, the 87 Sr/ 86 Sr analysis of local drinking water might be helpful. Livestock in the Pannonian region is fed on the locally produced food, which also confirms the result of milk from Radenci ( 87 Sr/ 86 Sr = 0.71119), matching the 87 Sr/ 86 Sr ratio of the mineral water from the source Radenci (0.71120). This finding aligns with the investigation performed in the Parmigiano Reggiano milk and cheese production area [45]. In her study, the 87 Sr/ 86 Sr isotope ratio on water, whole milk, and diet samples allowed the construction of a linear relationship with multiple independent variables, from which the 87 Sr/ 86 Sr ratio of the milk is mainly correlated with the 87 Sr/ 86 Sr ratio of the hay. Thus, results indicate milk samples reflect the 87 Sr/ 86 Sr ratio of the feed linked to the soil and water. This is also in agreement with Stevenson et al. (2015) [30], in which the authors demonstrated a good correlation between the Sr isotopic composition of milk, cheese, and the bedrock geology of the dairy farm locations.

Discriminant Analysis
In the next step, we check if the 87 Sr/ 86 Sr ratio can increase the differentiation of Slovenian milk samples according to the geological region using different statistical approaches. In our statistical evaluation, stable isotope and elemental composition in milk samples were also included. The data are presented in Table S6, while the detailed description of these parameters according to geographical origin is described in Potočnik et al. [8].
Sixty-three milk samples of four different geological regions (1-Cretaceous: Carbonate Rocks and Flysch, n = 8; 2-Jurassic-Triassic: Carbonate Rocks, n = 15; 3-Neogene: Carbonate Rocks, Paleogene: Deposits, n = 17; 6-Quaternary: Deposits, n = 23) and twenty-two parameters including 87 Sr/ 86 Sr, δ 18 Ow, δ 13 Ccas, δ 15 Ncas, δ 34 Scas, Mn, Fe, Cu, Rb, Sr, Ca, K, Cl, S, P, Zn, Br, 1/Sr, Rb/Sr, Ca/Sr and K/Rb were processed by DA. In Figure 6, DA modelling results were shown as a discriminant function score plot (a) and a discriminant loadings plot (b). In the functional score plot, each group (centroid) is represented by a scatter plot, while in the loadings plot, they appear as a set of vectors indicating the degree of association of the corresponding initial variables with the first two discriminant functions. In the latter, the degree of distribution of each parameter in the classes is revealed. The first two discriminant functions accumulated 89.2% of the total variability. Two groups (groups 1 and 6) show a good tendency of separation among each other and from groups 2 and 3, which overlap slightly. Group 1 (Cretaceous: Carbonate Rocks and Flysch) is positioned in the right part of DA graph and is associated with the vectors of Br, 1/Sr and δ 18 Ow. The mean values of these parameters in the centroid are the highest and the most influential for the separation. Inspection of the mentioned parameters with KW test reveals that they are significant for separating group 1 from the rest. A substantial amount In the functional score plot, each group (centroid) is represented by a scatter plot, while in the loadings plot, they appear as a set of vectors indicating the degree of association of the corresponding initial variables with the first two discriminant functions. In the latter, the degree of distribution of each parameter in the classes is revealed. The first two discriminant functions accumulated 89.2% of the total variability. Two groups (groups 1 and 6) show a good tendency of separation among each other and from groups 2 and 3, which overlap slightly. Group 1 (Cretaceous: Carbonate Rocks and Flysch) is positioned in the right part of DA graph and is associated with the vectors of Br, 1/Sr and δ 18 O w . The mean values of these parameters in the centroid are the highest and the most influential for the separation. Inspection of the mentioned parameters with KW test reveals that they are significant for separating group 1 from the rest. A substantial amount of Br indicates that geologically is associated with a marine basement rocks origin. Higher δ 18 O w are also typical for coastal regions. Further, group 6 positioned in the upper right part of the plot a is associated with vectors 87 Sr/ 86 Sr, δ 13 C cas and δ 15 N cas and according to KW test significant for discrimination among groups 1, 3 and 6. This group is located in the eastern part of Slovenia, located in Quaternary deposits, and it is also related to intensive milk production with higher content of corn in cow feed. Group 3, located in the lower right part of biplot a, is associated with Sr vectors, and inspection by KW and ANOVA tests reveal that both are significant for separation. Groups 2 and 3 are located in the lower part of biplot a, and here, δ 15 N cas and Br are significant for discrimination between both groups. The prediction ability was the highest for the Quaternary group (91.3%) and the lowest for group 3 (Neogene + Paleogene; 41.2%), with an overall prediction of 63.5%.
Further, OPLS-DA tests for pairwise comparisons among two overlapping geological groups (2-Jurassic + Triassic, 3-Neogene + Paleogene: Figure 7) was calculated similarly to in the study performed by Chung et al. (2020) [46]. This model had an explanatory power of 94% (F1) for variation in the X variables and displayed high quality, goodness of fit, and predictability. It was found that the separation of these two groups is governed by δ 15 N cas values govern, concentrations of Br and Rb/Sr ratio, indicating that not only geologic parameters are important for the separation, but also the way of cow feed and milk production-intensive with more corn silage or grass silage representative of the Jurassic + Triassic group.
to in the study performed by Chung et al. (2020) [46]. This model had an explanatory power of 94% (F1) for variation in the X variables and displayed high quality, goodness of fit, and predictability. It was found that the separation of these two groups is governed by δ 15 Ncas values govern, concentrations of Br and Rb/Sr ratio, indicating that not only geologic parameters are important for the separation, but also the way of cow feed and milk production-intensive with more corn silage or grass silage representative of the Jurassic + Triassic group.

Conclusions
In this study, we investigated the feasibility of the Sr isotope ratio analysis, combined with multivariate statistical analysis to discriminate milk samples from Slovenia based on their provenance. The 87 Sr/ 86 Sr ratios in milk samples were determined using an optimised method, which showed sufficient precision and accuracy to detect variations in Sr isotopic compositions between milk samples. Although Slovenia covers a relatively small area, its geology, geography and climate vary substantially. Large regional variability of 87 Sr/ 86 Sr ratios in Slovenian milk was observed, overlapping with other regions' values. Thus, a complete separation of the regions based solely on the 87 Sr/ 86 Sr ratio of the milk was not possible. However, it was found that a combination of Sr isotopic profiling coupled to multivariate analysis is a promising tool for characterising milk according to geological origin. The milk produced in the Quaternary areas had high Sr content and higher 87 Sr/ 86 Sr values and differed from those produced in carbonate dominated areas with lower 87 Sr/ 86 Sr values.
In conclusion, the 87 Sr/ 86 Sr ratio can distinguish between different dairy areas as long as geolithological differences characterise these areas. In cases of a similar geological environment, combining elemental concentrations and isotope ratios, both light and heavy isotopes, might be advantageous. However, this approach is limited in the case of Slovenian milk. The close distance between macro-regions in Slovenia and the variations in

Conclusions
In this study, we investigated the feasibility of the Sr isotope ratio analysis, combined with multivariate statistical analysis to discriminate milk samples from Slovenia based on their provenance. The 87 Sr/ 86 Sr ratios in milk samples were determined using an optimised method, which showed sufficient precision and accuracy to detect variations in Sr isotopic compositions between milk samples. Although Slovenia covers a relatively small area, its geology, geography and climate vary substantially. Large regional variability of 87 Sr/ 86 Sr ratios in Slovenian milk was observed, overlapping with other regions' values. Thus, a complete separation of the regions based solely on the 87 Sr/ 86 Sr ratio of the milk was not possible. However, it was found that a combination of Sr isotopic profiling coupled to multivariate analysis is a promising tool for characterising milk according to geological origin. The milk produced in the Quaternary areas had high Sr content and higher 87 Sr/ 86 Sr values and differed from those produced in carbonate dominated areas with lower 87 Sr/ 86 Sr values.
In conclusion, the 87 Sr/ 86 Sr ratio can distinguish between different dairy areas as long as geolithological differences characterise these areas. In cases of a similar geological environment, combining elemental concentrations and isotope ratios, both light and heavy isotopes, might be advantageous. However, this approach is limited in the case of Slovenian milk. The close distance between macro-regions in Slovenia and the variations in climate affecting these regions make discrimination between milk samples of different origins more difficult, particularly when milk samples originate from locations positioned close to a zone between two or more regions and thus share a similar isotopic signature.
Further, it has been confirmed that the cow's diet and geologic parameters are important for the separation. Indeed, our study shows the correlation between the isotope ratio of strontium in milk and possible source of drinking water, in which diverse sources of strontium from the environment are reflected. However, to better understand the influence of different factors, i.e., water, feed and supplements, on the Sr isotope ratio in the milk samples, future research should investigate the 87 Sr/ 86 Sr ratio utilising paired samples of feed, water, and soil originating from the same location as the milk. In the perspective of food traceability, the database of the 87 Sr/ 86 Sr values in soils and waters in Slovenia could be also beneficial for future studies of local foods, where it can be used as a reference map to identify the authenticity of particular food product, or whether there are any unexpected isotopic variations.
Supplementary Materials: The following are available online at https://www.mdpi.com/article/10 .3390/foods10081729/s1: The Supplementary Materials describes the optimization and validation of the analytical method for 87 Sr/ 86 Sr isotope ratio determination in milk; Table S1: Microwave-assisted acid digestion program used for pre-treatment of milk sample; Table S2: Comparison of the Sr concentrations obtained after microwave digestion of freeze-dried milk samples (mean ± standard deviation; n = 3); Table S3: Determined Sr concentrations after pre-treatment in certified reference materials, NIST SRM 8435 and IAEA-153 (mean ± standard deviation; n = 3);