Geographical Variation in Pasturelands and Their Impact on the Physicochemical Characterization and Fatty Acid Composition of Cheese in Caraș-Severin County, Romania

Abstract

In Caraș-Severin County, Romania, the integration of sustainable agricultural practices with organic dairy production represents a unique opportunity to promote agro-tourism farms and guesthouses. This study examines the synergy between the chemical composition of pastures from three farms in different alleys and the impact on the chemical composition of dairy products produced on those farms. Thus, the comparative analysis of two types of traditional cow’s cheeses (soft and mature) from three different areas of Caraș-Severin County was pursued, as well as of the feed given to the animals from which the raw material for obtaining the cheeses originated. Initially, the physicochemical profile of the pastures (fresh grass and grass hay) was analyzed in terms of proximate composition (moisture, lipids, proteins, ash and carbohydrates), and the content of bioactive compounds (total polyphenols, antioxidant activity using the DPPH method). The proximate composition of the cheese samples, including moisture, lipids, proteins, ash and carbohydrates was analysed, and the content of fatty acids. A correlation was also made between the content of bioactive compounds in feed samples and fatty acid profile of the cheese samples. Our findings demonstrate that the geographical area and the chemical composition of the pasture have a considerable influence on the physicochemical characterization and fatty acid composition of the cheese. The cheese from the mountain area had a higher fat, protein and polyunsaturated fatty acid content compared to the samples from the hill and plain areas.

1. Introduction

Caraș-Severin County, located in the southwestern part of Romania, is known for its rich natural landscapes, including mountains, forests, and rivers, as well as a diverse cultural heritage. The county’s varied terrain supports a wide range of organic farming activities, with livestock farming and dairy production being an important part of the local rural economy. These practices not only benefit the environment by promoting biodiversity and reducing pollution but also improve the quality of dairy products [1].

Controlled grazing allows cows to graze different plots in rotation, thus preventing soil degradation and promoting the regeneration of natural vegetation. The implementation of organic farming on a dairy farm involves the use of organic fodder grown on uncontaminated pastures and fields and allowing cows to graze freely on organic pastures. Organic production and processing involve the manufacture of milk, cheese, yoghurt and other dairy products without the use of synthetic preservatives and additives, minimizing processing to preserve nutritional value [2,3,4].

Due to growing interest in healthy animal products with a high polyunsaturated fatty acid (PUFA) content [5,6], organic dairy farms prioritize the welfare of cows by ensuring that they have access to open pastures and natural feed without synthetic additives. Higher amounts of beneficial elements including omega-3 fatty acids, conjugated linoleic acid (CLA), and vitamins in milk are a result of this diet, which is frequently high in natural grasses and forages [1,4].

The beginning of oxidation can be controlled and reduced by adding antioxidant items to animal feed or adding them directly into the finished product. Natural antioxidants are thought to be safer than their synthetic equivalents and have garnered more interest recently due to their perceived safety, lower environmental impact, and economic advantages [5,7].

The chemical composition of grassland is significantly influenced by altitude, directly influencing the quality and nutritive value of forage available to livestock. Studies show that variations in altitude affect not only biodiversity and vegetation structure but also the content of essential nutrients including protein, fat, carbohydrates and minerals. Altitude also influences total phenolic content in permanent grasslands, with higher altitudes showing significant increases in phenolic compounds due to changes in botanical composition [8,9].

The geographical area and the method of cow feeding influence the milk fatty acid profile, texture, appearance and chemical composition of cow’s milk cheese, with differences observed in long-chain, unsaturated, saturated and specific fatty acids [10,11,12].

These studies highlight the impact of cow feeding and pasture management on the fatty acid composition and proximate composition of cheese made from cow’s milk, which has important implications for the nutritional value and health of humans. It was demonstrated that mountain cheeses differ from their lowland counterparts in that they contain more unsaturated fatty acids and less saturated fatty acids [13].

The main aim of our study was to evaluate and assess the quality indicators of organic dairy products obtained from cows reared on three separate farms in Caras-Severin County in Romania. The present work is original in the fact that, so far, there are few comparative studies between cheese samples from different geographical areas, using the same breed of animals and the same type of feed as a source of nutrition.

The effect of the geographic region and feed on the chemical composition of fresh and ripened cow’s cheese was addressed.

The objectives of the study presented in this manuscript are: (i) to analyze the proximate composition of fresh and dried grass and their bioactive compound content; and (ii) to analyze the proximate composition and fatty acid content of fresh and matured cow’s milk cheese obtained in three processing units belonging to three agro-tourism farms.

2. Materials and Methods

2.1. Locations of the Study

The investigation was carried out in three distinct agritourism guesthouses in Caraș-Severin County, in south-western Romania, which also have small dairy farms that produce cheese for tourists. All three guesthouses are located in the same geographical area, but at different altitudes: one in the lowland area in the village of Sacu (45°33′57″ N 22°07′48″ E and altitude of 154 m.a.s.l.), the second in the village of Văliug (45°13′35″ N 22°01′44″ E and altitude of 550 m.a.s.l.) and the third in the village of Cozia (45°52′4″ N 22°50′28″ E aand altitude of 1130 m.a.s.l.).

2.2. Management and Feeding of Animals

The feeding method used for these cows was pasture-based. The owners used an organic fertilization system, using organic wastes such as poultry litter and dairy cow manure.

The farms from which the samples were collected were selected on the basis of two criteria: (1) the use of pastures belonging to the farms as the main source of animal feed throughout the grazing season; (2) cheese production exclusively from the milk of the animals reared on the farm. Cows of the indigenous breed Bălțata Românească Simmental were reared on all three farms. The milk was collected in May 2024. Both dry and fresh grass samples that were fed to the animals during the period of cheese sample collection and cheese samples were analyzed. Grass and cheese samples were collected similarly from all three locations. Grasses were collected from ten different areas of pasture, randomly chosen and cut according to the feeding behavior of the cows at a height of approximately 5 cm. On all three farms, samples of hay and fresh grass cut daily were collected in triplicate and thoroughly homogenized in a mixing vessel, after which a 500 g sample was taken from the whole mass. The hay and fresh grass samples were stored in a vacuum-packed freezer until analysis. Samples of soft and matured cheese were taken straight from the farm and placed in sterile 500 mL plastic containers within 2 to 3 h in a portable refrigerator at +4 °C. From the time of arrival at the laboratory until analysis, samples were kept in the refrigerator at +4 °C. Analyses were performed within 48 h after the samples arrived at the laboratory.

Table 1. Abbreviation of analyzed samples.

Sample	Abbreviation
Fresh grass from Sacu	FGS
Grass hay from Sacu	GHS
Fresh grass from Văliug	FGV
Grass hay from Văliug	GHV
Fresh grass from Cozia	FGC
Grass hay from Cozia	GHC
Soft cow cheese from Sacu	SCCS
Mature cow cheese from Sacu	MCCS
Soft cow cheese from Văliug	SCCV
Mature cow cheese from Văliug	MCCV
Soft cow cheese from Cozia	SCCC
Mature cow cheese from Cozia	MCCC

displays the studied samples’ abbreviations.

2.3. Determination of the Physicochemical Characteristics of Fresh Grass and Grass Hay

2.3.1. Determination of Proximate Composition

Official AOAC methods were used to determine proximate composition of dried and fresh grass, i.e., moisture, ash, crude fat and crude protein [14].

2.3.2. Antioxidant Profile of Fresh Grass and Grass Hay

The Preparation of Plant Extracts

Samples of fresh grass and grass hay were extracted with ethyl alcohol (70:30, v/v) in water (Sigma-Aldrich KGaA, Darmstadt, Germany). In total, 0.5 g of each haygrass sample was weighed into covered containers to which 25 mL of 70% ethyl alcohol was added. Using a linear motion stirrer (DLAB SK-L180-Pro, DLAB SCIENTIFIC Co., Ltd., Beijing, China), the samples were stirred for 30 min. Before being analyzed, the homogenized extracts were kept at 4 °C after being filtered through Whatman No. 42 filter paper (Sigma-Aldrich KGaA, Darmstadt, Germany).

Determination of TPC

To determine the total polyphenol content (TPC), 0.5 mL of each of the six previously produced extracts (from fresh grass and grass hay samples) were measured. Then, 1.25 mL of a Folin–Ciocalteu solution (diluted 1:10 in water) from Sigma-Aldrich Chemie GmbH in Munich, Germany, was added to each extract. After allowing the resultant mixture to rest at room temperature for five minutes, 1 mL of Na₂CO₃ 60 g/L (Geyer GmbH, Renningen, Germany) was added to each sample. The mixtures obtained were placed in a thermostat (INB500 from Memmert GmbH, Schwabach, Germany) and kept at a temperature of 50 °C for a duration of 30 min. Incubation was followed by measuring absorbance at 750 nm using a UV–Vis spectrophotometer (Specord 205; Analytik Jena AG, Jena, Germany). The calibration curve was obtained using Gallic acid (Sigma-Aldrich Chemie GmbH, München, Germany), with concentrations ranging from 5 to 250 μg/mL. Three measurements were conducted for each sample, and the results were reported in milligrams of gallic acid equivalent per kilogram of dry weight [15].

Determination of Antioxidant Capacity by 1,1-Diphenyl-2-picrylhydrazyl (DPPH)

The antioxidant activity (AA) was measured using an ethanolic solution of 1,1-diphenyl-2-picrylhydrylpicrylhydrazyl (DPPH, Sigma-Aldrich, Taufkirchen, Germany) at a concentration of 0.03 mM. In order to achieve a concentration of 1 mg/mL, the stock solution of the plant extract (fresh grass and hay grass) was produced in 70% ethanol. To obtain concentrations of 500, 250, 125, 50, 25, 10, and 5 µg/mL, dilutions were prepared. One milliliter of each dilution extract was mixed with 2.5 milliliters of DPPH solution. The mixture was given a thorough shake and then left to stand at room temperature in the dark for 30 min. Following this break, absorbance at 518 nm was measured using a UV–Vis spectrophotometer (Specord 205; Analytik Jena AG, Jena, Germany). The reference point was set at 70% ethyl alcohol. After three samples were examined, the average [16].

2.4. Description of the Production Process of the Two Cheeses Samples

For the present study, fresh cheese and matured cheese obtained from the same batch of milk were chosen. The technology used to obtain the two types of cheese is similar, the difference being that the matured cheese is additionally subjected to the maturing process for 30 days. We chose to study these two types of cheese to see the cheese’s chemical composition’s progression over time (30 days).

The two cheese types studied in this paper (SCC and MCC) were obtained according to the technology adapted from Banu [17] described in Figure 1.

2.5. Determination of Physicochemical Characteristics of Cheese

2.5.1. Determining the Cheese’s Proximate Composition

For analysis, the cheese samples were shredded to a homogeneous mass. Physicochemical analysis was performed on the cheese samples for moisture, protein, lipid, salt and ash content. Official methods were used to assess the physicochemical quality parameters: moisture—ISO 5534:2004 [18], ash—ISO/CD 9877|IDF 258 [19], protein—ISO/TS 17837:2008 [20] and fat—SR ISO 3433:2008 [21].

2.5.2. Determination of Fatty Acid Content

Following the derivatization of fatty acids as methyl esters, the fatty acid profile (FAME) was determined using the procedure that is thoroughly detailed in Posta et al. (2022) [22].

Using the peak area normalization method—the ratio of the peak area corresponding to a specific component to the overall area of all peaks—fatty acids were identified using the NIST 05 spectrum library. Every analysis was carried out three times. The total of C4:0–C24:0 was used to compute saturated fatty acids (SFA), C16:1–C22:1 was used to calculate monounsaturated fatty acids (MUFA), and C18:2, C18:3, and C20:4 were used to calculate polyunsaturated fatty acids (PUFA). The total of MUFA and PUFA was used to determine unsaturated fatty acids (UFA).

2.6. Statistical Analysis

In this study, every determination was made in triplicate, and the findings were reported as mean values and standard deviation (SD). In the statistical processing, the fatty acid profile of the cheese samples and the TPC content and antioxidant activity of fresh grass and hay grass extracts were correlated, along with any statistically significant variations between samples for all parameters assessed. For statistical analysis, Microsoft Excel 365 was utilized. The t-test was used to compare the values recorded for the studied samples statistically, and a value was deemed significant if p < 0.05.

3. Results

3.1. Determination of the Physicochemical Characteristics of Fresh Grass and Grass Hay

3.1.1. Determination of Proximate Composition

Table 2. Proximate composition of the samples.

Sample	Chemical Parameters
	Moisture (g/100 g)	Protein (g/100 g)	Lipids (g/100 g)	Ash (g/100 g)	Carbohydrates (g/100 g)	Energy Value (kcal/100 g)
FGS	83.60 ± 2.75 a	2.60 ± 0.09 f	0.37 ± 0.01 e	3.09 ± 0.10 f	10.34 ± 0.34	55.09 ± 1.89
GHS	7.82 ± 0.24 d	9.95 ± 0.33 c	2.46 ± 0.08 b	7.26 ± 0.22 c	72.51 ± 2.51	351.98 ± 12.22
FGV	86.70 ± 3.05 b	4.08 ± 0.12 e	0.46 ± 0.01 d	3.76 ± 0.12 e	5.00 ± 0.16	40.46 ± 1.37
GHV	8.25 ± 0.27 e	11.41 ± 0.36 b	2.77 ± 0.09 b	7.89 ± 0.26 b	69.68 ± 2.39	349.29 ± 12.14
FGC	89.30 ± 3.08 c	5.57 ± 0.18 d	0.55 ± 0.01 c	4.17 ± 0.14 d	0.71 ± 0.02	29.27 ± 1.01
GHC	9.10 ± 0.30 f	13.05 ± 0.43 a	3.43 ± 0.11 a	8.54 ± 0.27 a	65.88 ± 2.27	346.59 ± 12.08

The results of the parameters listed in the table represent the mean value of the three determinations performed individually for each sample ± standard deviation (SD). Statistically significant differences between samples were compared using the t-test, and different superscript letters (a–f) in the same column indicate statistically significant differences between samples (p < 0.05). FGS—Fresh grass from Sacu; GHS—Grass hay from Sacu; FGV—Fresh grass from Văliug; GHV—Grass hay from Văliug; FGC—Fresh grass from Cozia; GHC—Grass hay from Cozia.

displays the proximate composition of the samples of fresh grass and grass hay.

The results show that fresh grass samples have a substantially greater moisture content than dry hay pots. It is also visible that there are significant differences among fresh samples, as well as among dry samples. In the case of fresh grass samples, the moisture was in the range of 83.60–89 g/100 g and in the case of dry hay samples between 7.82 and 9.10 g/100 g.

The samples that were analyzed had protein contents that fell between 2.6 and 13.05 g/100 g, with significant differences between fresh (FGS, FGV and FGC) and dry samples (GHS, GHV and GHC) and between the geographical area of harvest. The highest protein content was recorded for samples harvested from the mountain area (0.55 g/100 g for FGC and 13.05 g/100 g for GHC), followed by samples harvested from the hill area (4.08 g/100 g for FGV and 11.41 g/100 g GHV) and the lowest values were recorded for samples harvested from the plain area (2.60 g/100 g for FGS and 9.95 g/100 g for GHS).

The freshness of the samples and the harvesting region had an impact on the lipid content as well. Thus, dry hay samples had the highest levels ever recorded (2.46–3.43 g/100 g) compared to fresh grass samples (0.37–0.55 g/100 g). The highest lipid content was recorded for the mountain samples (0.55 g/100 g for FGC and 3.43 g/100 g for GHC), followed by the hill samples (0.46 g/100 g for FGV and 2.77 g/100 g for GHV) and the plant samples (0.37 g/100 g for GHC).

In the case of mineral substances, the trend recorded for the other parameters continued, i.e., the highest mineral substance content was recorded for the samples harvested from the mountain area (4.17 g/100 g for FGC and 8.54 g/100 g for GHC), followed by the samples harvested from the hills (3.76 g/100 g for FGV and 7.89 g/100 g for GHV) and the samples from the plain which recorded the lowest values (3.09 g/100 g for FGS and 7.26 g/100 g for GHS).

3.1.2. Antioxidant Profile of Fresh Grass and Grass Hay

Determination of the Amount of Total Polyphenols Content (TPC)

Figure 2 displays the total polyphenol content (TPC), which is given in mg GAE/g dry matter (d.w.), of the alcoholic extracts of the fresh grass and grass hay samples that were investigated.

The data obtained for the six extracts (Figure 2) indicate that GHC had the highest TPC concentration at 98.61 mg GAE/g d.w., while FGS had the lowest at 22.49 mg GAE/g d.w.

It can be seen that for both fresh grass and grass hay, the highest TPC values were recorded for samples collected from the mountain area (FGC—35.72 mg/g d.w. and GHC—98.61 mg/g d.w.), followed by samples collected from the hill area (FGV—27.46 mg/g d.w. and GHV—92.43 mg/g d.w.) and the lowest values were recorded for samples collected from the plain area (FGS—22.49 mg/g d.w. and 87.24 mg/g d.w.). Also, the comparative analysis reveals that the grass hay samples had markedly higher values compared to the fresh grass samples. The t-test revealed statistically significant differences (p < 0.05) across all the samples analyzed.

Determination of Antioxidant Capacity by DPPH (1,1-Diphenyl-2-picrylhydrazyl)

Figure 3 displays the antioxidant activity of samples of fresh grass and grass hay.

As with TPC, it is evident that GHC had the highest antioxidant activity (649.27 μg/mL) while FGS had the lowest (105.49 μg/mL).

It can be seen that for both fresh grass and grass hay, the highest values of antioxidant activity were recorded for the samples collected from the upland area (GFC—337.09 μg/mL and GHC—649. 27 μg/mL), followed by samples collected from the hill area (FGV—229.46 μg/mL and GHV—428.18 μg/mL), and the lowest values were recorded for samples collected from the lowland area (FGS—105.49 μg/mL and GHS—249.38 μg/mL). Also, from the comparative analysis of the obtained values it can be seen that grass hay samples compared to the fresh grass samples, the reported values were substantially greater. The t-test revealed statistically significant differences (p < 0.05) across all the samples analyzed.

3.2. Determination of the Physicochemical Characteristics of Cheese

3.2.1. The Proximate Composition of Cheese Samples

Many elements, including ripening time, weather, and animal feed, affect the content and quality of cheeses [23].

Table 3. The proximate composition of cheese samples.

Samples	Chemical Parameters
	Moisture (g/100 g)	Protein (g/100 g)	Lipids (g/100 g)	Ash (g/100 g)	Carbohydrates (g/100 g)	Energy Value (kcal/100 g)
SCCS	57.71 ± 2.05 B	16.25 ± 0.54 A	23.11 ± 0.79 A	1.88 ± 0.05 A	1.05 ± 0.03 B	277.19 ± 9.65 A
MCCS	53.28 ± 1.84 b	16.87 ± 0.57 a	26.37 ± 0.90 a	2.04 ± 0.06 a	1.44 ± 0.04 c	310.57 ± 10.71 a
SCCV	57.17 ± 2.02 B	16.59 ± 0.56 AB	23.72 ± 0.82 A,B	1.97 ± 0.05 A	0.55 ± 0.01 A	282.04 ± 9.79 B
MCCV	52.69 ± 1.79 a,b	16.98 ± 0.60 a	27.01 ± 0.92 a,b	2.19 ± 0.08 b	1.13 ± 0.03 b	315.53 ± 10.94 a,b
SCCC	56.24 ± 1.84 A	16.82 ± 0.57 B	24.18 ± 0.81 B	2.23 ± 0.08 B	0.53 ± 0.01 A	287.02 ± 9.89 C
MCCC	51.32 ± 1.73 a	17.50 ± 0.61 b	27.93 ± 0.95 b	2.47 ± 0.09 c	0.78 ± 0.02 a	324.49 ± 10.91 b

The parameters shown in the table indicate the average values of the three separate calculations made for each sample, plus or minus the standard deviation (SD). The t-test was used to examine statistically significant differences between samples; statistically significant differences (p < 0.05) are indicated by distinct superscript letters (a–c for soft cheese and A–C for matured cheese) in the same column. SCCS—Soft cow cheese from Sacu; MCCS—Mature cow cheese from Sacu; SCCV—Soft cow cheese from Văliug; MCCV—Mature cow cheese from Văliug; SCCC—Soft cow cheese from Cozia; MCCC—Mature cow cheese from Cozia.

displays the proximate composition of cheese samples.

The study of the data shows that the moisture content was higher in soft cheese (56.24–57.71 g/100 g) compared to ripened cheese (51.32–53.28 g/100 g). The highest content was recorded for SCCS (57.71 g/100 g) and the lowest for MCCC (51.32 g/100 g). It can be seen that as the altitude of the cheese sample’s origin increases, the moisture content decreases.

The protein content varied within the range of 16.25–17.50 g/100 g, the maximum value for MCCC and the lowest value for SCCS. Soft cheese samples showed lower protein content (16.25–16.82 g/100 g) compared to ripened cheese samples (16.87–17.50 g/100 g). In the case of protein, feed quality had a direct influence on the samples of cheese’s protein content, i.e., the higher protein proportions recorded in fresh grass and hay grass are also reflected in the higher protein content recorded for cheese from the hill and mountain region compared to cheese from the plain.

The lipid content ranged from 23.11 to 27.93 g/100 g, with the lowest value also recorded for SCCS and the highest value for MCCC. Also, similar to the protein content, the samples of ripened cheese recorded lower lipid content (23.11–24.18 g/100 g) compared to the samples of ripened cheese (26.37–27.93 g/100 g).

The length of the ripening period, which may be brought on by some water partially evaporating, may be the cause of the elevated protein and fat content in ripened samples [24].

The ash content analysis showed values ranging from 1.88 to 2.47 g/100 g, with the highest for MCCC and the lowest value recorded for SCCS. The content of this parameter was also higher in ripened cheese samples (2.04–2.47 g/100 g) than in soft cheese samples (1.88–2.23 g/100 g).

Both for protein, lipids and mineral substances, the values recorded were influenced by the altitude of origin of the samples as well as by the chemical composition of the feed. The ascending order of the values obtained for protein, lipid and mineral content is: lowland cheese samples < hill cheese samples < mountain cheese samples. The lowland and mountain samples showed statistically significant differences (p < 0.05).

The carbohydrate content calculated based on the determined values ranged from 0.53 to 1.44 g/100 g, the maximum value recorded for MCCS and the minimum value for SCCC. The calculated energy value ranged from 277.19 to 324.49 kcal/100 g, the protein and lipid content having a direct influence on this characteristic.

3.2.2. Determination of Fatty Acid Content

Table 4. Fatty acids content of cheese samples.

Fatty Acids, (g/100 g Fatty Acids)	SCCS	MCCS	SCCV	MCCV	SCCC	MCCC
C8:0	0.34 ± 0.02 a	2.38 ± 0.11 e	1.24 ± 0.06 c	1.67 ± 0.07 d	1.09 ± 0.05 b	1.17 ± 0.05 c
C10:0	1.14 ± 0.05 c	3.30 ± 0.15 e	0.89 ± 0.04 b	1.56 ± 0.07 d	0.84 ± 0.04 a,b	0.71 ± 0.04 a
C12:0	2.78 ± 0.13 c	2.88 ± 1.13 c	2.018 ± 0.10 b	3.21 ± 0.15 d	1.58 ± 0.08 a	1.62 ± 0.07 a
C14:1	0.58 ± 0.03 b	0.36 ± 0.02 a	0.66 ± 0.03 b	0.58 ± 0.03 b	0.60 ± 0.03 b	0.56 ± 0.03 b
C14:0	9.97 ± 0.50 a,b	10.93 ± 0.53 d	10.08 ± 0.49 b	9.61 ± 0.46 a	11.09 ± 0.55 d	10.45 ± 0.49 c
C15:0	2.76 ± 0.13 c	2.84 ± 0.13 c	2.24 ± 0.11 b	1.46 ± 0.07 a	2.13 ± 0.11 b	2.25 ± 0.09 b
C16:1	1.17 ± 0.05 b	0.82 ± 0.04 a	2.07 ± 0.10 c	1.11 ± 0.05 b	1.04 ± 0.05 a,b	0.96 ± 0.04 a
C16:0	35.99 ± 1.76 f	33.42 ± 1.65 e	32.49 ± 1.61 d	31.53 ± 1.58 c	27.37 ± 1.35 a	28.08 ± 1.36 b
C17:0	1.35 ± 0.07 c	1.22 ± 0.05 b,c	1.06 ± 0.05 b	1.47 ± 0.06 d	0.72 ± 0.03 a	0.82 ± 0.03 a
C18:0	12.27 ± 0.59 a,b	13.25 ± 0.64 c	11.94 ± 0.59 a	12.66 ± 0.62 b	14.38 ± 0.71 d	15.65 ± 0.77 e
C18:1	25.57 ± 1.28 b	22.76 ± 1.12 a	28.43 ± 1.40 c	28.85 ± 1.42 c	31.22 ± 1.55 d	30.63 ± 1.51 d
C18:1, n9 trans	0.01 ± 0.001 a	0.34 ± 0.02 c	0.60 ± 0.03 d	0.03 ± 0.001 a	0.54 ± 0.03 d	0.10 ± 0.01 b
C18:1, trans-11	0.97 ± 0.05 b	nd *	0.74 ± 0.04 a	0.96 ± 0.04 b	0.83 ± 0.04 a	1.00 ± 0.05 b
C18:1, trans-12	1.36 ± 0.07 b	2.22 ± 0.11 d	0.99 ± 0.05 a	2.09 ± 0.09 c,d	1.05 ± 0.05 a	1.94 ± 0.10 c
C18:2	1.32 ± 0.07 a	1.39 ± 0.07 a	2.42 ± 0.10 b	1.41 ± 0.07 a	3.99 ± 0.18 c	3.85 ± 0.17 c
C18:2, n8, 11	0.43 ± 0.02 a	0.68 ± 0.03 b	0.95 ± 0.04 f	0.76 ± 0.04 d	0.88 ± 0.04 e	0.64 ± 0.03 b
C19:1	0.25 ± 0.01 b,c	0.20 ± 0.01 a,b	0.57 ± 0.03 e	0.31 ± 0.02 d	0.28 ± 0.01 c,d	0.14 ± 0.01 a
C20:0	0.23 ± 0.01 a,b	0.24 ± 0.01 b	0.21 ± 0.01 a,b	0.20 ± 0.01 a,b	0.18 ± 0.01 a	0.21 ± 0.01 a,b
Other	1.17 ± 0.05 a,b	0.77 ± 0.04 d	0.40 ± 0.02 c	0.53 ± 0.03 d	0.19 ± 0.01 b	0.13 ± 0.01 a
MUFA	29.90 ± 0.88 b	26.70 ± 0.75 a	34.06 ± 0.99 c	33.93 ± 0.95 c	35.56 ± 1.04 d	35.32 ± 1.02 d
PUFA	1.74 ± 0.04 a	2.07 ± 0.05 b	3.37 ± 0.09 c	2.17 ± 0.06 b	4.87 ± 0.14 d	4.49 ± 0.12 d
SFA	66.82 ± 1.84 e	70.46 ± 1.97 f	62.17 ± 1.73 c	63.37 ± 1.78 d	59.38 ± 1.61 a	60.96 ± 1.65 b

The results are shown as the average of three measurements plus or minus the standard deviation (SD). The lowercase letters (a–f) on the row represent statistically significant differences between samples (p < 0.05) as determined by the t-test. * nd—not detected; SCCS—Soft cow cheese from Sacu; MCCS—Mature cow cheese from Sacu; SCCV—Soft cow cheese from Văliug; MCCV—Mature cow cheese from Văliug; SCCC—Soft cow cheese from Cozia; MCCC—Mature cow cheese from Cozia.

shows the fatty acid composition of the cheese samples.

Based on the examination of the facts provided in Table 4, it is evident that for all six cheese samples, the major compounds identified were C16:0, C18:0 and C18:1. The cheese samples from the lowland area (SCCS—66.82% and MCCS—70.46%) exhibited the highest values for SFA, followed by the samples from the hilly area (SCCV—62.17% and MCCV—63.37%) and the minimum values were registered for the samples from the mountain area (SCCC—59.38% and MCCC—60.96%). For MUFA and PUFA the maximum values were registered for the mountain samples (SCCC—35.56% MUFA and 4.87% PUFA, MCCC—35.32% MUFA and 4.49% PU-FA), followed by the hill samples (SCCV—34.06% MUFA and 3/37% PUFA, MCCV—33.93% MUFA and 2.17% PUFA), and the minimum values were registered for the samples collected from the lowland area (SCCS—29.9% MUFA and 1.74% PUFA, MCCS—26.70% MUFA and 2.07% PUFA).

From the analysis of the fatty acid composition data, we can conclude that the chemical composition of the feed has a significant impact on the quality and chemical composition of the final products. Thus, fresh grass and hay grass from the mountain area, which had a higher polyphenol content and higher antioxidant activity, had an immediate impact on the fatty acid composition of the cheese, with higher MUFA and PUFA values compared to samples from the hill and plain areas.

3.3. Correlations between Variables

Table 5. Pearson correlation coefficient matrix for antioxidant profile of fresh grass and grass hay and fatty acid composition of cheese.

	TPC	IC50	C8:0	C10:0	C12:0	C14:1	C14:0	C15:0	C16:1	C16:0	C17:0	C18:0	C18:1	C18:1 trans	C18:1, trans-11	C18:1, trans-12	C 18:2	C 18:2, n8, 11	C19:1	C20:0
TPC	1.00
IC50	0.74	1.00
C8:0	−0.24	−0.59	1.00
C10:0	−0.40	−0.61	0.98	1.00
C12:0	0.17	−0.42	0.76	0.63	1.00
C14:1	0.24	0.37	−0.87	−0.91	−0.41	1.00
C14:0	−0.60	−0.20	0.07	0.26	−0.52	−0.46	1.00
C15:0	−0.35	−0.53	0.38	0.38	−0.03	−0.50	0.45	1.00
C16:1	−0.29	−0.20	−0.40	−0.42	−0.18	0.68	−0.41	−0.14	1.00
C16:0	−0.02	−0.65	0.57	0.42	0.73	−0.22	−0.45	0.48	0.20	1.00
C17:0	0.26	−0.36	0.62	0.45	0.97	−0.20	−0.70	−0.07	0.01	0.80	1.00
C18:0	0.24	0.69	−0.32	−0.21	−0.63	−0.16	0.55	−0.05	−0.58	−0.80	−0.73	1.00
C18:1	0.29	0.75	−0.89	−0.83	−0.68	0.72	−0.02	−0.67	0.17	−0.82	−0.61	0.50	1.00
C18:1 trans	−0.89	−0.43	−0.21	−0.03	−0.52	0.15	0.54	0.10	0.49	−0.29	−0.55	−0.08	0.15	1.00
C18:1, trans-11	0.72	0.70	−0.80	−0.89	−0.27	0.82	−0.54	−0.53	0.21	−0.26	−0.10	0.13	0.73	−0.37	1.00
C18:1, trans-12	0.34	0.18	0.68	0.64	0.54	−0.73	−0.08	−0.06	−0.66	0.07	0.41	0.24	−0.39	−0.59	−0.36	1.00
C18:2	−0.03	0.58	−0.75	−0.61	−0.95	0.36	0.52	−0.18	−0.03	−0.90	−0.96	0.78	0.80	0.39	0.33	−0.37	1.00
C18:2, n8, 11	−0.60	−0.07	−0.31	−0.16	−0.39	0.34	0.20	−0.48	0.52	−0.50	−0.40	−0.04	0.45	0.81	−0.11	−0.38	0.39	1.00
C19:1	−0.46	−0.36	−0.27	−0.25	−0.06	0.58	−0.33	−0.25	0.94	0.17	0.08	−0.66	0.12	0.61	0.06	−0.62	−0.11	0.68	1.00
C20:0	−0.06	−0.45	0.75	0.66	0.51	−0.66	−0.06	0.71	−0.14	0.73	0.49	−0.28	−0.89	−0.30	−0.58	0.48	−0.65	−0.58	−0.23	1.00

The two-tailed significance level of the correlation is 0.01. The values represented in the text with red color represent the significant correlations recorded between the analyzed variables.

shows the correlation between the antioxidant profile of fresh grass and grass hay and the fatty acid profile of the cheese.

A substantial positive correlation (r > 0.7) was found between IC50/C18:1 (r = 0.75) and IC50/C18:1, trans-11 (r = 0.70), while a strong negative correlation (r > −0.7) was seen between TPC/C18:1 trans (r = −0.89) and TPC/C18:1, trans-11 (r = −0.72). These findings are presented in Table 4’s correlation analysis. The IC50/C18:0 (r = 0.69) and IC50/C18:2 (r = 0.58) pairs showed a moderately favorable correlation (r > 0.5) and a moderate negative correlation (r > −0.5) for the TPC/C14:0 (r = −0.60) and TPC/C18:2, n8,11 (r = −0.60) pairs. We found mutual connections between the individual variables, which would show that chemical components are dependent on one another. The variables that were most closely associated were the antioxidant capacity (IC50) of fresh grass and dried grass samples and unsaturated fatty acids, indicating that the high content of bioactive compounds in feed leads to increased unsaturated fatty acid content in the resulting products (cheese) from the raw material (milk) from the animals.

4. Discussions

4.1. Determination of the Physicochemical Characteristics of Fresh Grass and Grass Hay

It is evident from the above analysis of all the parameters that the samples taken from the mountainous region had the highest values (FGC and GHC), followed by the samples from the hill area (FGV and GHV), and the samples taken from the plain (FGS and GHS) had the lowest recorded levels. Statistically significant differences were found between samples harvested from different geographical areas but also between samples of fresh grass and dry hay from the same area.

Similar proximate composition values were also presented in the literature. Younge et al. [25] demonstrated dry matter values ranging between 154 and 196 g/kg DM (with a mean 171 g/kg) for grass-silage and fresh grass harvested throughout the year at four distinct periods. Muhakka et al. reported a protein content ranging from 10.99 to 12.43% for several grass varieties [26]. Rochana et al. [27] reported dry matter content ranging from 34.33 to 36.08% and protein content ranging from 8.41 to 16.29%. Mir et al. reported a fat content between 1 and 4% for different types of grass [28]. In another study published by Stergiadis et al. [29], values between 10.60 and 32.4% for dry matter, 4.00–11.00% for ash, and 10.70–38.10% for protein were reported. Sheppard et al. [30] reported a dry matter content of 22% in fresh grass and 89.9% in hay grass, protein of 18.2% in fresh grass and 17.0% in hay grass in their study. Petrović et al. [31] reported for three clover species and discovered an ash content between 9.87 and 14.9 g/100 g, protein of 14.18–22.30 g/100 g and fat of 1.74–3.04 g/100 g.

The results obtained in our study regarding polyphenolic content of pastures are consistent with other related studies in the literature. In their study, Petrović et al. [31] reported on the polyphenol values of three clover species, which ranged from 29.00 to 120.1 mg GAE/g extract. Rapisarda and Abu-Ghannam [32] reported TPC values ranging from 19.95 to 29.43 mg GAE/g for several perennial grass samples harvested monthly from April to August. In another study, Sheppard et al. [30] reported a total polyphenol content of 44.6 g/kg d.w. in fresh grass and 47.1 g/kg d.w. in hay grass. Petrović et al. [31] reported TPC values ranging between 29.0 and 43.8 mg GAE/g DM.

Polyphenols are compounds that, when added to animal feed, have the role of reducing oxidative damage, which has a negative impact on derived products. The objective to produce healthier animal products with a higher ratio of polyunsaturated fatty acids to saturated fatty acids is correlated with an increase in lipoperoxidation [5]. Studies show that mountain meadow plants have a high polyphenol content, which gives them a higher nutritive value. This is due to cooler temperatures and increased exposure to UV radiation, factors that stimulate polyphenol production in plants [33]. Hill pastures provide an intermediate environment between mountains and plains. They benefit from a milder climate than the uplands, but with sufficient variations in temperature and humidity to stimulate polyphenol synthesis. The soils in hilly areas are often fertile, contributing to a rich floral diversity and hence a significant polyphenol content [34]. Lowland grasslands at lower altitudes have more stable and less extreme climatic conditions. They have a lower polyphenol content compared to upland and hill grasslands, due to reduced exposure to environmental stresses that stimulate the production of these compounds. However, species diversity and agricultural management can positively influence polyphenol content [35]. A study conducted in the Romanian Carpathians compared the polyphenol content of plants from mountain, hill and lowland grasslands. The results showed that plants from mountain pastures had a 30% higher polyphenol content than those from lowland pastures [36], while hill pastures had an intermediate polyphenol content, with approximately 20% higher than the plains [37].

Plants that have high levels of polyphenols are more resistant to oxidative stress and damage from free radicals. These substances end up in milk and indirectly in cheese through animal feed, where they support fatty acid stability and protect against rancidity [38].

Antioxidants are crucial in preventing cell damage caused by free radicals. In agriculture, plants with high antioxidant activity are valuable for animal feed, providing protection against oxidative stress and improving animal health [39]. The floral composition and diversity of plant species vary between mountains, hills and plains, contributing to the differences in antioxidant activity [40]. Similarly to TPC, studies show that plants from montane grasslands exhibit high DPPH antioxidant activity due to high concentrations of polyphenols and other antioxidants [41]. Hill pastures provide an intermediate environment between mountains and plains, the fertile soils in these areas support a rich floral diversity, which contributes to the significant antioxidant activity of plants [33], and lowland grasslands located at lower altitudes tend to have lower DPPH antioxidant activity compared to mountain and hillside grasslands, due to reduced exposure to environmental stresses that stimulate antioxidant production [35]. In the same study conducted in Romania, Popescu et al. [36] compared the DPPH antioxidant activity of plants from mountain, hill and lowland pastures and concluded that plants from mountain pastures had a DPPH antioxidant activity 35% higher than those from lowland pastures, while hill pastures showed an intermediate antioxidant activity, about 20% higher than lowland pastures [37].

Regarding the recorded values, other authors have reported similar values for the antioxidant activity of grasses intended for animal feed and especially for cows. Thus, Petrović et al. [31] in their study on three clover species, reported values of antioxidant activity ranging from 446.1 to 919.14 µg mL⁻¹. Vasiljević et al. [42] studied 46 species of clover intended for animal feed from different countries and regions, and reported DPPH values ranging from 6.4 to 120 µg/mL.

4.2. Determination of the Physicochemical Characteristics of Cheese

Vegetation type and soil in mountain, hill and lowland areas influence the composition of milk and thus of cheese [43]. Altitude, climate and soil specificity contribute to variations in the milk’s chemical composition [44]. Cheese from the mountain areas is often appreciated for its intense taste and firm texture due to its high protein and lipid content. The diverse vegetation and mineral-rich soils contribute to the complex nutritional composition of the milk [45]. Hill pastures provide a variable environment with an animal diet that may include a combination of grass and other forages. This is reflected in a cheese with a balanced nutrient profile, but with variation depending on the season and type of forage available [46].

Lowland cheese is influenced by the consistent diet of the animals, mainly based on cultivated fodder. This can lead to a more uniform cheese composition, with a higher water content and lower protein and lipid content [47].

A comparative study conducted in Romania examined the primary ingredients of cheese made from milk from pastures in the lowlands, hills, and mountains. The results showed that the mountain cheese had a protein and lipid content about 10–15% higher than the lowland cheese [36] and the hill cheese showed intermediate values, reflecting the diversity of forages and variability of environmental conditions [37].

Other studies in the literature have also reported values comparable to ours from the current investigation. Thus, Ojedapo et al. [48] recorded a fat content between 12.68 and 15.30%, protein between 14.74 and 20.13%, and dry matter between 33.43 and 36.36% for two types of cheese (unsalted and salted). In their study, Alexa et al. [49] reported a protein content of 15.50%, a lipid content of 8% and dry matter of 22% for fresh cow cheese samples, and Paszczyk et al. [23] reported a fat content of 27.03–27.68%, protein of 23.79–26.16% and water of 43.49–44.20% in their study.

Consistent with our findings, the same study also demonstrates that the matured cheese samples had lower protein and fat contents than the fresh cheese samples.

Our results on the fatty acid content of the cheese samples are in agreement with those published in the literature by other authors. Therefore, when Innocente et al. [13] examined the fatty acid profile of cheese made from cow milk whose cows were grazing on plain and mountain pastures, they found that the cheese made from the cow milk from the plain pastures had lower levels of saturated fatty acids and a higher content of unsaturated fatty acids than the cheese made from the cow milk from the mountain pastures. According to this study, the mountain cheese had 44.10% of total fatty acids from unsaturated fat, while the lowland cheese had 33.21% of total fatty acids from unsaturated fat. The mountain cheese had 53.74% saturated fatty acid content, while the lowland cheese had 63.44% total fatty acid content. Serrapica et al. [50] reported that for the cheese they analysed from the mountain area, there was an SFA content between 68. and 69.79 g/100 g of fatty acid, between 5.08 and 5.64 g/100 g PUFA and between 24.40 and 24.87 g/100 g of fatty acids for MUFA. The major compounds identified by them were C14:0 (11.39–12.09 g/100 g fatty acids), C16:0 (23.58–23.92 g/100 g fatty acids), C18:0 (10.01–10.59 g/100 g fatty acids) and C18:1 n9cis (10.01–10.59 g/100 g fatty acids).

The high polyphenol content and increased antioxidant activity of mountain pastures provide protection against the lipid oxidation of fatty acids, and this can be seen in the lipid profile of cheese and milk [41]. The cheese made from pasture milk in the hills exhibits a good balance between fatty acid stability and nutritional profile [33]. The fatty acids in the cheese obtained from milk from lowland animals are more susceptible to oxidation, thus affecting the stability and taste of the cheese [35]. The bioactive compounds and in particular the polyphenols from the pastures that are fed to the animals are inserted first into the milk and then the cheese, protecting the unsaturated fatty acids in the cheese against oxidation, preventing rancidity and increasing the product’s shelf life [38].

In the Romanian Carpathians, researchers evaluated the fatty acid composition and antioxidant activity of cheese made from milk from plain, hill, and mountain pastures. The results showed that mountain cheese had superior fatty acid stability due to its high polyphenol content and antioxidant activity [36]. Hill cheese exhibited a balance between fatty acid stability and antioxidant activity [37]. Plain cheese had the lowest level of antioxidant protection, affecting fatty acid stability and taste [35].

5. Conclusions

The primary finding of this study is that the quality of the products (fresh and matured cow’s cheese) was significantly impacted by the geographical origin of the cheese and grass samples. The feed given to the animals had a great influence on the proximate composition of the cheese samples. Thus, the high content of protein, lipids and ash in the grass fed to the animals varies in proportion to the protein, lipid and mineral content of the cheese samples. Also, higher polyphenol content and better antioxidant activity were obtained in the case of samples taken from the mountainous area, followed by the samples from the hill area, and the lowest values were obtained for the samples taken from the plain area. Moreover, the feed administered to the animals also influenced the fatty acid composition of the cheese samples, with an increase in the content of PUFA and MUFA in the samples from the mountainous area compared to the samples from the hill area and those from the plain area. The location of the production farm significantly influenced the quality and chemical characteristics of the cheeses.

Our results from the present study encourage organic dairy production based on organic farming practices and encourage further studies in the agri-tourism sector to see the influence on their economic viability.