*2.4. pH and Color*

Meat pH was evaluated at 24 (pH ultimate) and 48 h post-slaughtering (p.s.), using a calibrated pH-meter equipped with a spear-head electrode (Meat pH-meter; Hannah instruments, Model #HI99163; Serial #B0083102). While the pH at 24 h was measured directly on the carcasses, between the 12/13th ribs, in the mid region, the pH at 48 was measured in the aged steaks.

The meat color was measured on the steaks 24 h p.s., following the exposure of their surface to room temperature. A Konica Minolta Chroma Meter CR-410 (KONICA MINOLTA) was used to measure the attributes of lightness (*L\**), redness (*a\**) and yellowness (*b\**). The Chroma meter was operated using illuminant C mode. Prior to the measurements, the device was calibrated, using a white tile standard. Ten replicates were taken from every steak, with special care taken to avoid areas of connective tissue or intramuscular fat.

#### *2.5. Chemical Composition*

The chemical analyses were performed on 70 g pieces of meat. These included the determination of intra-muscular fat content (IMF%) using the Soxhlet method [22], crude protein (CP) content via the Kjeldahl method [23], moisture, and ash [24].

#### *2.6. Water Holding Capacity*

The water holding capacity was determined according to the Grau-Hamm method [25], with modifications [26]. Briefly, ~0.3 g of ground meat were weighed and placed on laminated plastic white paper, covered with a Whatman filter (No.1). This "cassette" was

set between two Plexiglass plates and subjected to a constant pressure of 1 kg for 10 min. The content of the WHC was measured according to the following equation:

$$\% \,\mathrm{WHC} = \left[ \left( (X \ast mio \,\mathrm{stur} \,\,\%) - (X - \mathrm{Y}) \right) / X \right] \ast 100 \tag{1}$$

where *X* is initial weight of the meat before pressing (g), and *Y* is the final weight of the meat after pressing (g).

### *2.7. Warner Bratzler Shear Force*

#### 2.7.1. Sample Preparation

The determination of shear force (SF) was performed according to AMSA 1995 [27] and Wheeler et al. [28]. Briefly, extra fat was removed from the surrounding muscle, and the steaks were frozen at −20 ◦C, in PA/EVOH/PE plastic bags, following 48 h of ageing. Prior to the analysis, the samples were thawed in the plastic bags, under circulating water, then moved to a 72 ◦C pre-warmed bath for cooking, until their core temperature reached 70 ◦C [27]. A temperature probe, HI 9061 (Hanna Food care Digital Thermometer, Bedfordshire, England), placed in the geometric center of a steak, was used to monitor the temperature. Following the cooking process, juices were poured out of the bag (for CKL measurement; see Section 2.8). The meat samples were cooled down and stored overnight at 4 ◦C.

#### 2.7.2. Coring and SF Measurement

Six cores with a diameter of 1.27 cm (0.5 inch) diameter were cut, on the following morning, from the chilled steaks, in parallel to the longitudinal orientation of the muscle fibers, enabling the shearing action to be perpendicular to the longitudinal orientation of the fibers. The cores were sheared using a V-shaped shear blade with a triangular aperture of 60◦, attached to an INSTRON Universal Testing Machine (Model 3343 Instron, UK Ltd. High Wycombe, UK), equipped with a 500 N loading cell, at a crosshead speed of 200 mm/min [27,28]. The Warner Bratzler SF values were calculated based on the average of the 6 cores, using Bluehill software. The peak force required to cut through the fibers was expressed in Newtons (N).

#### *2.8. Cooking Loss and Thawing Loss*

Cooking loss was expressed as the percentage of weight difference before and after cooking, according to the following equation [29]:

$$\% \text{ Cooking Loss} = \left[\frac{X - Y}{X}\right] \* 100\tag{2}$$

where *X* = weight of raw steak and *Y* = weight of cooked steak.

The thawing loss (TL), the loss of meat fluids due to thawing, was determined as described by Honikel 1998 [30].

#### *2.9. Sarcomere Length (SL)*

The sarcomere length was determined on thawed meat samples, according to the method used by Cross et al. [31]. The solutions for fiber fixation were prepared according to Koolmees et al. [32]. Briefly, samples without tendons were selected in triplicates from each tissue, and excised in small pieces (2.0 cm × 1.0 cm × 1.0 cm), in a longitudinal orientation of the fibers. An incision was made with a scalpel in the middle of each sample. The pieces were placed in 50 mL tubes fixed with 30 mL of 5% glutaraldehyde solution, for 4 h at 40 ◦C, followed by overnight fixation at 40 ◦C, with a 30 mL 0.2 M sucrose solution. Thereafter, flat tweezers were used to gently separate long and thin fibers from the samples. The separated fibers (about 15–20) were placed in a mortar that contained 3–4 mL 0.2 M sucrose solution, and ground with the pestle to a consistent "soup". The sarcomere length was determined by laser diffraction, using a neon-helium laser (HeNe Laser; λ = 632.8 nm),

which was mounted on an optics bench with a specimen-holding device and a screen, as previously described by Cross et al. [31]. The length of at least 10 projected sarcomeres was measured with a ruler for each biological sample. The SL was calculated by the following equation, as provided by Cross et al. [31]:

$$\mu = \frac{0.6328 \times D \times \sqrt{\left(\frac{T}{D}\right)^2 + 1}}{T} \tag{3}$$

in which *D* was the distance, in mm, from the specimen to the diffraction pattern screen and *T* referred to half of the separation distance (in mm) between the diffraction bands.

#### *2.10. Total Collagen Content*

The determination of the total collagen content was based on AOAC 990.26 [33], with adaptations from Starkey et al. [34]. Briefly, 20 g of meat were removed and trimmed of external fat and connective tissue. The meat was minced into a paste, and frozen in petri dishes for 3 h, at −20 ◦C, prior to lyophilization. The lyophilized samples were ground into powder, using a mortar and pestle. Triplicates of freeze dried muscle powder weighing 0.10 g were mixed with three ml of 3.5 M H2SO4 for subsequent hydrolyzation at 105 ◦C, for 16 h. Hydrolysis was terminated by the addition of 1.5 M NaOH to the hydrolyzed filtrate, prior to the determination of the hydroxyproline content, from a standard curve, as in Starkey et al. [34].

The content of Hydroxyproline (H) in the sample was calculated: H = h × 0. 25/m.

In which the h-hydroxyproline content as read from the calibration curve; 0.25—coefficient, based on the dilution factor and transition between the units; and m—weight of sample portion.

To convert hydroxyproline to total collagen, the following equation was used: total collagen, mg/g = H × 8 (with collagenous connective tissue containing 12.5% hydroxyproline, if nitrogen-to-protein factor is 6.25).

#### *2.11. Fatty Acid Profile*

The analysis of the FA profile was performed on the lyophilized muscles, as previously described [35]. Lipids were extracted from 1 g sample powder in a hexane: isopropanol solvent mixture, in accordance with Hara and Radin [36]. An aliquot of 40 mg of the lipid fraction was trans-methylated in accordance with Christie (1982) [37], with modifications [38]. Gas chromatography of the fatty acid methyl esters (FAME) was performed with a Hewlett Packard 6890 system, equipped with HP Chemstation software for peak integration. We used a Supelco SP-2560, 100-m fused silica capillary column of 0.25 mm i.d., with ultra-high purity helium carrier gas, at a flow rate of 20 mL/min. The injector and flameionization detector (FID) temperatures were 250 ◦C and 260 ◦C, respectively. The splitting ratio to the detector was 1:50. The oven temperature schedule was as follows: 140 ◦C for 5 min, T increase to 175 ◦C at 4 ◦C/min, constant 175 ◦C for 25 min, T increase to 220 ◦C at 4 ◦C/min, and constant 220 ◦C for 20 min. The total run time was 70 min. Standard FAME preparations (Sigma-Aldrich) were injected separately to relate the peaks to the FA. The FAME preparations used were methyl esters of: C10:0, C12:0, C14:0, C14:1, C16:0, C16:1, C18:0, C18:1t9, C18:1t10, C18:1t12, C18:1c9, C18:1c11, C18:1c12, C18:2c9c12, C18:3c6c9c12 (γ-linolenic), C18:3c9c12c15 (α-linolenic), C18:2t10c12 and C18:2c9t11 (conjugated linoleic acid; CLA), and C20:4c5c8c11c14 (arachidonic).

#### *2.12. Statistical Analysis*

All the variables met our assumptions of normality and were compared among the three farms or two breeds, using a one-way ANOVA, followed by a Bonferroni Multiple Comparison Test (*p* < 0.05). Pearson correlations between the meat quality phenotypes were calculated using the CORR procedure. Letters are used in the figures/tables to indicate pairwise differences identified through this analysis. All the statistical comparisons were conducted using SPSS version 21.0.

#### **3. Results & Discussion**

Sustainable food systems are designed to provide healthy and nutritious food that is available, accessible, and affordable to everyone for generations to come [39]. At the same time, sustainable systems, as engines of growth, nourish a continuous dialog between social, economic, and environmental components by: *(i)* encouraging local production and distribution infrastructures; *(ii)* protecting farmers and other workers (e.g., paying their salaries), consumers and entrepreneurs (e.g., profits or returns on assets); *(iii)* minimizing their negative effect on the natural environment. [40].

Many of these aspects should indeed be taken into consideration while aiming to promote sustainable beef production in Israel. However, in order to encourage stakeholders and decision-makers to set policies that will encourage positive transformations towards sustainable beef production, identifying the "intrinsic" properties of the food system that will ensure that its essential outcomes are continuously maintained [41] is a prerequisite. A cardinal obstacle ahead of this enterprise is the massive import of live beef animals to Israel [3]. Thus, an initial step to facilitate the above initiative would be through uncovering the advantages of local over imported beef production.

In the current study, we compared between key meat quality phenotypes, in the *LL* muscle, of Israeli Holstein and imported Australian male calves.

#### *3.1. Carcass Production*

Live bodyweight (BW), carcass weight, and dressing percentage are presented in Table 1. Although live BW did not differ among farms, nor between breeds, carcass weight and dressing percentage were significantly higher in the Australian calves (F3) in comparison with Holstein (F1 and F2; *p* ≤ 0.0001; Table 1). Although a slight significant difference in dressing percentage was revealed between F1 and F2 animals, statistical adjustment to the breed effect highlighted the superior carcass yield of the Australian calves (*p* ≤ 0.0001; Table 1). Indeed, crosses of beef X beef or beef X dairy animals are expected to produce heterogeneous progeny with higher growth rates and dressing percentage compared to dairy-bred cattle [42–44]. On the other hand, dairy-selected animals (e.g., Holstein Frisian) are known for their higher proportions of non-carcass parts, as external (head/feet/tail) and internal organs, offal fats and gastrointestinal tract [45], resulting from their engagement in the process of milk production [9,46–48].


**Table 1.** Carcass production of local Holstein (HOL) and imported Australian (AUS) male calves, adjusted to farm and breed effects. Farm 1 (F1; HOL; N = 62); Farm 2 (F2; HOL; N = 143); Farm 3 (F3; AUS; N = 169).

Different letters indicate significant differences between farms or breeds (*p* < 0.0001). BW = body weight; Dressing percentage was calculated as the ratio between hot carcass weight and live BW.

#### *3.2. Technological Parameters of Raw and Cooked Meat*

#### 3.2.1. pH and Color

Among others, ultimate pH (pHu; measured 24 h post-slaughter) is a major technical attribute that drives consumers' purchasing decisions about meat. It is influenced by different factors, such as individual cows' genetic background, their on-farm nutritional regime, and a variety of biochemical events occurring pre-and post-slaughter (e.g., the level of stress prior to slaughter and post-slaughter processing) [49].

Differences in initial pH and the rate of its decline mostly affect sarcomere shrinkage, protein denaturation and myofibrillar lattice spacing [50].

In the current study, the pHu values ranged from 5.74 ± 0.12 (F3) to 5.88 ± 0.28 (F1), and were affected by both farm (*p* < 0.0001) and breed (*p* = 0.0002; Table 2). While the pHu of the Holstein calves from F1 and F2 did not differ, statistical adjustment to breed revealed higher values in the Holstein meat (*p* = 0.0002; Table 2). Similar breed and farm effects were also determined 48 h post-slaughter (*p* < 0.0001; Table 2). These results, typical for meat without DFD or PSE syndromes, were in agreement with the pH values obtained in the *LL* muscle in other studies [51–53].

**Table 2.** Effects of farm and breed on pH, color attributes, thawing loss (TL), and water holding capacity (WHC) of raw meat, and cook loss (CKL) of thermally treated meat, from Holstein (HOL) and Australian (AUS) male calves. Farm 1 (F1; HOL; N = 62); Farm 2 (F2; HOL; N = 143); Farm 3 (F3; AUS; N = 169).


Different letters indicate significant differences between farms or breeds (*p* < 0.001). † pH ultimate measured in the carcasses 24 h post-slaughter; †† pH measured in the steaks 48 h post-slaughter; \* color attributes measured in the steaks 24 h post-slaughter.

> The variation in pHu mostly affected the meat color, an important technological and visual property of meat quality [4]. The light reflected from the surface of the meat is of primary importance, as it affects, to a great extent, consumers' perceptions and, hence, their purchasing decisions [50].

> In the present study, the meat color was determined 24 h post-slaughter (Table 2), and included attributes of brightness (*L\**), redness (*a\**) and yellowness (*b\**). These attributes did not differ between Holstein calves from F1 and F2, but varied significantly when compared to Australian calves from F3 (Table 2). Statistical adjustment to breed revealed differences in meat color characteristics (*L\**, *a\** and *b\**) between the two breeds (*p* ≤ 0.0001; Table 2). More specifically, while the Holstein meat had higher redness and yellowness scores, the Australian meat was brighter (*p* < 0.0001; Table 2). The color attributes reported herein were only in relative agreement with those presented by others [4,53–55], presumably due to environmental variations, such as on-farm rearing management and dietary regime, especially towards the end of the growing period. However, the most plausible effect seems technological; while in many studies color attributes are determined 14 days p.s., the data presented in the current study refer to 24 h p.s. Nevertheless, the attributes most appreciable to consumers favored the local Holstein meat, predicting its possible preference over imported Australian meat.
