Comparing Freeze-Thaw Cycle Effects on Pork Loin and Belly Quality and Muscle Characteristics

Comparing Freeze-Thaw Cycle Effects on Pork Loin and Belly Quality and Muscle Characteristics | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Comparing Freeze-Thaw Cycle Effects on Pork Loin and Belly Quality and Muscle Characteristics Kannika Umpuch, Siriporn Namted This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6850843/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study examined the effects of repeated freeze-thaw (F-T) cycles on pork loin and belly, two economically important cuts in Thai cuisine. Fifty samples underwent 0–4 F-T cycles, with evaluations of thawing and cooking loss, pH, color (CIE L*, CIE a*, CIE b*), chemical composition, and histological structure. Pork belly showed significantly higher CIE L* and CIE b* values and lower CIE a* than loin (p < 0.01). F-T cycles led to linear increases in CIE L* and CIE b* (p < 0.01), while CIE a* and pH in belly exhibited cubic trends (p < 0.05). Thawing loss decreased linearly in loin (p < 0.01) but remained unchanged in belly (p = 0.47). Cooking loss was lower in belly (p < 0.01), likely due to higher fat content. Histological analysis revealed progressive fiber disruption and reduced endomysium thickness (p < 0.05). Pork belly exhibited greater resilience to F-T cycles, with better moisture and structural retention. Limiting F-T cycles to fewer than three is recommended to maintain pork quality. Biological sciences/Physiology Biological sciences/Zoology freeze-thaw cycle pork loin pork belly meat quality muscle characteristics Figures Figure 1 Figure 2 Introduction Retail prices for pork belly and loin are projected at baht/kg and 185–190 baht/kg, respectively. Pork belly accounts for 9.62% of the whole carcass, while loin comprises 6.28% [ 1 ]. Pork belly contains 16.00–16.95% protein and 27.72–31.91% fat, compared to pork loin's 20.65–23.65% protein and 1.89–2.91% fat [ 1 , 2 ]. Pork belly is a prized ingredient in Thai cuisine, valued for its balance of fat and lean muscle, which contributes to its flavor and tenderness. It features traditional dishes and street foods. Due to its high fat content, pork belly is both desirable and economically significant. According to KResearch [ 3 ], it is in strong demand domestically and internationally, particularly in regions where it is used in products such as bacon. In Thailand, the quantity and quality of pork belly are key determinants of its market value. Therefore, it is crucial to monitor pricing trends for both pork belly and loin, especially concerning processing and storage conditions. Meat is highly perishable, and its quality is influenced by processing and storage conditions. Freezing is a commonly used preservation technique that extends shelf life and ensures food safety. Meat contains 50–75% water, which freezes during chilling [ 4 ]. However, repeated F-T cycles can lead to significant degradation of meat quality, affecting its physicochemical properties, protein structure, water-holding capacity, and texture [ 5 ]. The formation of ice crystals during freezing disrupts muscle microstructure, resulting in cell membrane rupture, protein denaturation, and moisture loss [ 6 ]. Although previous studies have explored the impact of repeated freeze-thaw (F-T) cycles on various meat types [ 7 – 9 ], their specific effects on the muscle characteristics and quality of pork loin and belly remain underexplored. This study examines the effects of repeated F-T cycles on the quality and muscle characteristics of pork loin and belly, aiming to optimize preservation techniques for high-value pork products. Materials and Methods Funding Statement This research was partially funded by the Department of Agriculture, Faculty of Agricultural Technology, Valaya Alongkron Rajabhat University, Thailand. The remaining resources were supported by the authors without external funding. Ethics Declaration This study did not involve any experiments on humans or animals, and therefore, no ethics approval or consent was required. Muscle Sampling A Total of fifty muscle samples were collected from commercial pigs and were randomly selected from a local meat distributor in Thailand. All pork samples were placed in an icebox and transported to the laboratory. Visible fat and connective tissue on the surface were carefully removed, after which the pork samples were cut into 2.5 cm-thick pieces perpendicular to the fiber direction, with each piece weighing 75.00 ± 5.00 g. The samples were then frozen and stored at −18 ± 1 °C for 4.5 days, followed by thawing at 4 ± 0.5 °C for 24 h, representing one F-T cycle [10]. All loin and belly pork samples were individually packed and randomly divided into five groups corresponding to 0, 1, 2, 3, and 4 F-T cycles. Thawing Loss and Cooking Loss Analysis Thawing loss was calculated as a percentage of weight loss in pork samples subjected to different F-T cycles, following the method described by Tippala et al. [11]. Briefly, the pork samples were weighed prior to freezing (M1). After thawing, surface water was removed using paper towels, and the samples were weighed again, with the weight recorded as M2. The thawing loss was calculated using the following formula: Thawing Loss (%) = ((M1 − M2) / M1) ×100% The samples were then placed in cooking bags and immersed in a 72°C water bath until the core temperature reached 70°C. After reaching the target temperature, the samples were cooled to room temperature by immersion in water and subsequently weighed again. Cooking loss was calculated using the following formula: Cooking Loss (%) = ((M1 − M2) / M1) ×100% where M1 is the weight before cooking, and M2 is the weight after cooking. pH and Meat Color Analysis The pH of the samples was determined using a pH meter (Orion 2 Star, Thermo Scientific, USA), which was standardized with reference buffers of pH 4.01 and 7.00, both allowed to stabilize at 25 °C prior to measurement [12]. Meat color characteristics (CIE L*, a*, and b*) were evaluated on the muscle surface using a Minolta Colorimeter (CR-300, Minolta Co., Tokyo, Japan). The instrument was calibrated with a white reference standard (Y = 93.5, x = 0.3132, y = 0.3198). Color measurements for both fresh and thawed samples were taken on freshly exposed surfaces after permitting the meat to bloom for 30 minutes [12]. Three measurements were recorded for each sample to ensure accuracy. The total color difference (ΔE) was calculated using the following equation: where , represent the lightness, redness/greenness, and yellowness/blueness values of fresh pork meat and F-T pork meat, respectively. Moisture Protein and Fat Content Moisture and protein content were determined using a procedure from AOAC [13-14]. The total moisture content of 3 g of samples placed in aluminum moisture pans was calculated from their pre-dried and dried weights (dried in an air oven at 104°C for 24 hours) and expressed as a percentage of the pre-dried weight and grams of water per gram of dry weight. Moisture content was measured in triplicate for each sample. Fat was extracted from 5 g of meat using chloroform/methanol (2:1), following the procedure outlined by Folch et al. [15]. Histochemical Analysis Histological evaluation was carried out on the porcine longissimus dorsi muscle from fresh meat, F-T 1 cycle, F-T 2 cycles, F-T 3 cycles, and F-T 4 cycles. The samples were cut into pieces measuring 0.5 × 0.5 × 1.0 cm and promptly fixed in a 10% buffered neutral formalin solution for 24 hours. Following fixation, the specimens were dehydrated with alcohol, cleared with xylene, infiltrated, and subsequently embedded in paraffin. Thin sections were cut to a thickness of 3 μm and stained with hematoxylin and eosin for general microscopic examination. Stained cross-sections were captured using a light microscope (Olympus FSX100, Tokyo, Japan) equipped with a 10× objective lens and a 10× eyepiece. Five images of distinct cross-sections from each muscle were captured. The samples were analyzed using Image-J software (National Institute of Mental Health, Bethesda, MD, USA). Approximately 300 fibers from five randomly selected fields in each muscle were measured to determine fiber diameters (μm). The thickness of the endomysium and perimysium was evaluated for each sample. Structural components were measured within a fiber bundle area, with 40 measurements taken for the endomysium thickness (μm) and 10 measurements for the perimysium thickness (μm) per image. The mean thickness was calculated based on the collected measurements [11,16]. Statistical Methods The experiment was designed as a completely randomized design (CRD) with multiple F-T cycles as the main treatment factor. Data were analyzed using analysis of variance (ANOVA) with the General Linear Model (GLM) procedure in SAS statistical software (ver. 6.4; SAS Institute, Cary, NC, USA). Differences among treatment means were determined using Duncan’s multiple range test (p < 0.05). yij = μ + τi + ϵij where μ = overall mean, τi = treatment effect of the i -th F-T cycle, and ϵij = random error. To evaluate the effects of repeated F-T cycles on pork quality attributes and muscle characteristics, polynomial contrast analysis was performed to assess linear, quadratic, and cubic trends in response to increasing F-T cycles. Additionally, orthogonal contrast analysis was employed to compare differences between pork loin and belly samples across measured variables, particularly focusing on thawing loss, color attributes, and muscle fiber characteristics. All statistical analyses were conducted at a significance level of p < 0.05, and results were reported as means ± standard error. Results and Discussions Effect of Pork Type on Color, pH and Chemical Composition Pork Loin The lightness (L*) of loin samples significantly increased with successive F-T cycles. Fresh meat had the lowest CIE L* value (53.10), while the 4th F-T cycle recorded the highest (55.56), with significant differences (p < 0.01). Redness (a*) decreased after the 1st F-T cycle, reaching its lowest value (9.65) in the 2nd cycle. Significant differences were observed across cycles (p < 0.01). Yellowness (b*) in fresh meat increased from 12.19 in fresh meat to 16.44 in the 4th F-T cycle (p < 0.01). Total color difference (ΔE) was significantly higher in repeated F-T cycles than in fresh meat (p < 0.01) (Table 1). pH values remained stable between 5.68 and 5.73 (p = 0.39). Moisture content decreased slightly with each F-T cycle, with fresh meat showing the highest value (70.19%), though this change was not statistically significant (p = 0.07). Protein and fat contents were not significantly impacted by the F-T cycles (Table 1). Pork Belly The lightness (L*) of belly samples significantly increased with successive F-T cycles (p = 0.01), with fresh meat having the lowest L* value (59.90), while the highest values were observed in the third (68.08) and fourth cycles (65.62). Redness (a*) showed no significant differences. Yellowness (b*) in fresh meat increased from 13.42 in fresh meat to 16.82 in the fourth cycle (p < 0.01). Total color difference (ΔE) tended to increase with repeated F-T cycles (p = 0.08) (Table 1). The pH values exhibited a borderline significant difference (p = 0.05), with the lowest in the 1st F-T cycle (5.81) and higher values in fresh meat and later cycles (5.96–6.01). Moisture and protein content were unaffected by F-T cycles. Fat content showed a tendency to change (p = 0.08), decreasing in the 1st and 2nd cycles before slightly increasing from 26.73% to 29.84% in the 4th cycle (Table 1). Comparison B etween Pork Loin and Belly A comparative analysis of the effects of F-T cycles on the color and chemical composition of pork loin and belly is presented in Table 1. Pork type significantly affected (p < 0.001) the CIE L*, CIE a*, and pH values. Pork belly exhibited higher CIE L* (p < 0.01), lower CIE a* (p < 0.01), and higher CIE b* (p = 0.03) values, suggesting a lighter and less red appearance compared to pork loin. Additionally, pork loin showed significantly lower pH values than pork belly (p < 0.01). Polynomial contrast analysis revealed that F-T cycles significantly affected the color parameters of both loin and belly. CIE L* and CIE b* values increased linearly in both cuts (P < 0.01), with pH and CIE a* following a cubic trend in belly (p 0.05). Pork loin had higher moisture and protein content but lower fat content than pork belly. The color differences in pork are linked to its chemical composition, including protein, fat, and water content. Pork belly typically contains more fat than loin, which explains its higher CIE L* and CIE b* values. The higher protein content in pork loin may contribute to a lower pH and increased drip loss. According to Huff-Lonergan and Lonergan [17], meat with higher protein and water content tends to have lower pH and higher drip loss. However, Medić et al. [12] found that frozen storage for 6–18 months increased meat pH, likely due to proteolysis releasing amino acids and dipeptides [18]. Unexpectedly, in this study, the F-T cycle had no effect on pork loin pH, while belly pH followed a cubic trend. Repeated F-T cycles disrupt muscle structures, releasing pro-oxidants like non-heme iron, which accelerate lipid oxidation [19]. Ice crystal formation during thawing further damages cells by expanding within muscle fibers, promoting oxidative deterioration, increasing water loss, and worsening meat color [20]. In this study, CIE L* and CIE b* values of both pork loin and belly increased significantly and linearly with each F-T cycle, while CIE a* followed a cubic trend. The increase in CIE L* and CIE b* values is likely due to structural damage from repeated F-T cycles, leading to moisture loss and greater surface reflectivity, making the meat appear lighter and more yellow [21]. The cubic trend in CIE a* suggests that initial myoglobin oxidation darkens the meat temporarily, but continued F-T cycles accelerate oxidative degradation, reducing redness [22]. After four cycles, water loss increases, and hemoglobin degradation appears to stabilize. Repeated F-T cycles significantly accelerate lipid oxidation, often resulting in the degradation of unsaturated fatty acids [23]. Qi et al. [24] reported reductions in saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), and individual free fatty acids following the first F-T cycle, likely due to the loss of compounds in the drip during thawing. Consistent with these findings, the present study observed a similar trend, with a noticeable decrease in fat content. Moreover, Han et al. [25] emphasized that repeated F-T cycles reduce moisture content, further exacerbating quality deterioration. Effect of Pork Types and F-T Cycle on Thawing Loss Orthogonal contrast analysis revealed a significant difference in thawing loss between pork loin and belly (P < 0.01), with loin samples exhibiting greater water loss. Thaw loss in pork loin significantly decreased across F-T cycles (P < 0.01), from 9.20% in the first cycle to 1.39% in the fourth cycle. In contrast, thaw loss in pork belly showed minimal variation (P = 0.47) (Table 2). Polynomial contrast analysis indicated a significant linear trend (P 0.05), suggesting that repeated F-T cycles had minimal effect on moisture loss in pork belly muscle (Table 2). Repeated F-T cycles typically decrease water-holding capacity (WHC) due to muscle fiber damage caused by ice crystal formation [5]. Wachirasiri et al. [26] also observed significant reductions in WHC with repeated F-T cycles, leading to deterioration in texture and sensory properties [6,17,27]. While the higher fat content in pork belly may help mitigate WHC loss, protein denaturation remains a significant factor affecting moisture retention [2,8]. This study suggests that the higher fat and lower protein content of pork belly enhance moisture retention and reduce thawing loss compared to pork loin. Effect of Pork Types and F-T Cycle on Cooking Loss Cooking loss differed significantly between pork loin and belly (Table 3), with loin exhibiting greater loss (33.01%) than belly (13.23%) (p < 0.01). In loin, cooking loss decreased significantly after the 4th F-T cycle, from 33.01% in fresh meat to 27.82% (p < 0.05). However, in pork belly, no significant change was observed between fresh (13.23%) and 4th F-T cycle samples (14.23%) (P = 0.50). Pork belly exhibited significantly lower cooking loss than loin, likely due to its higher fat and lower protein content, which may mitigate muscle protein degradation during cooking. Medić et al. [12] reported that the highest cooking loss occurred in fresh meat, whereas storage at −18°C for 3–6 months reduced this effect. Repeated freezing and thawing promotes water exudation, leading to a decline in moisture content over time [28]. Consequently, freeze-thawed meat retains less water, reducing the volume available for release during cooking. This aligns with Schulte et al. [29], who demonstrated that freezing alters muscle water retention. In the present study, F-T cycles had no significant impact on pork belly cooking loss. Effect of Pork Types and F-T Cycle on Muscle Fiber Characteristics The effects of pork type and F-T cycles on muscle fiber characteristics are shown in Table 4. Orthogonal contrast analysis identified a significant difference in muscle fiber diameter (p = 0.02), with belly muscle exhibiting larger fibers than loin. There were no significant differences in endomysium and perimysium thickness between the loin and belly (p = 0.873 and p = 0.923, respectively). Endomysium thickness in the loin significantly decreased with repeated F-T cycles, peaking at 17.02 µm in the second cycle and reaching its lowest value of 8.24 µm in the fourth cycle (p = 0.01) (Fig. 1 and 2). Additionally, muscle fiber diameter in the belly tended to be smaller in the third and fourth cycles compared to the first cycle (p = 0.05), indicating a possible trend of fiber shrinkage with repeated F-T cycles, with these cycles also exhibiting lower endomysium thickness than the other groups (p = 0.03). However, polynomial contrast analysis revealed no significant impact of F-T cycles on muscle fiber diameter, endomysium and perimysium thickness. This study reveals that pork belly has a larger muscle diameter than pork loin. Huff-Lonergan and Lonergan [17] suggest that muscle fiber size and structure are key factors influencing meat quality, with the more active loin containing smaller fibers and the less active, fattier belly containing larger fibers. While polynomial contrast analysis showed no significant effect of F-T cycles on muscle fiber characteristics, the third and fourth F-T cycles significantly reduced endomysium thickness in both pork loin and belly. Repeated F-T cycles disrupt the endomysium, creating gaps between muscle fibers, as observed by Qi et al. [24]. These cycles exacerbate mechanical damage by causing the melting and recrystallization of ice crystals, which disrupt lysosomal integrity and release enzymes that contribute to the partial degradation of myofibrillar proteins [19]. This degradation can further compromise meat quality [30]. Therefore, our findings indicate that repeated F-T cycles may contribute to muscle tissue damage and potential deterioration of meat quality. These effects appeared more prominent after three cycles and may vary depending on the pork cut. Therefore, limiting the number of F-T cycles to fewer than three could help preserve meat texture and overall quality, particularly in pork loin, which showed greater sensitivity compared to pork belly. Conclusion Pork loin and belly differed in color, pH, and chemical composition, with both affected by F-T cycles. Pork belly showed better water retention, with less thaw and cooking loss, while loin experienced reduced muscle fiber size and endomysium thickness. Limiting F-T cycles to fewer than three may help maintain quality in both cuts. Limitations This study evaluated only pork loin and belly under laboratory-controlled F-T cycles, which may differ from commercial conditions. External factors such as packaging methods, freezing rates as well as extended storage durations were not assessed. Additionally, sensory characteristics and oxidative stability were not evaluated, which could further inform consumer acceptance and shelf-life implications. Declarations Ethics Declaration This study did not involve any experiments on humans or animals, and therefore, no ethics approval or consent was required. Funding Statement This research was partially funded by the Department of Agriculture, Faculty of Agricultural Technology, Valaya Alongkron Rajabhat University, Thailand. The remaining resources were supported by the authors without external funding. 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Effect of freeze-thaw cycles on meat quality in the loin and belly of pork Fresh meat F-T cycle 1 F-T cycle 2 F-T cycle 3 F-T cycle 4 P value SEM Loin L* 53.10±0.75 A 53.18±0.89 A 54.54±0.80 B 55.24±0.70 BC 55.56±0.97 C <0.01 0.18 a* 11.80 ±0.70 A 11.30±7.67 AB 9.65±1.57 C 10.39±1.04 BC 10.54±0.54 BC <0.01 0.18 b* 12.19±0.55 A 14.24±0.83 B 15.19±0.82 C 15.49±0.37 C 16.44±0.41 D <0.01 0.22 ΔE - 2.53±0.93 A 4.33±1.63 B 4.29±0.95 B 5.13±0.91 B <0.01 0.23 pH 5.73±0.03 5.68±0.04 5.71±0.03 5.68±0.07 5.71±0.10 0.39 0.01 Moisture (%) 70.19±1.44 68.03±2.25 66.85±2.27 66.90±1.28 68.69±0.71 0.07 0.44 Protein (%) 26.37±1.06 27.82±2.35 28.10±0.92 28.49±1.62 26.19±0.64 0.14 0.35 Fat (%) 3.43±0.65 4.14±0.66 5.04±1.66 4.07±0.67 5.11±0.12 0.10 0.23 Belly L* 59.27±6.95 A 59.90±5.86 A 65.62±2.72 B 66.01±6.05 B 68.08±5.20 B 0.01 0.93 a* 9.38±2.60 7.66±2.76 9.91±2.26 9.55±1.82 8.19±1.58 0.14 0.33 b* 13.42±1.16 A 14.58±1.06 B 14.91±1.10 BC 15.63±0.64 C 16.82±1.09 D <0.01 0.22 ΔE - 5.06±2.97 7.24±3.76 7.73±3.08 9.43+4.62 0.08 0.61 pH 5.99±0.10 B 5.81±0.28 A 5.97±0.09 B 5.96±0.13 B 6.01±0.07 B 0.05 0.02 Moisture (%) 60.39±0.96 57.92±5.97 55.85±1.24 56.01±3.16 55.06±4.62 0.46 0.93 Protein (%) 14.45±1.30 15.34±7.13 15.96±2.86 15.94±4.02 15.10±5.11 0.99 0.99 Fat (%) 26.15±1.01 26.73±1.79 28.19±3.48 28.04±4.39 29.84±1.68 0.46 0.65 Orthogonal Contrast L* a* b* pH Moisture (%) Protein (%) Fat (%) Loin vs Belly P-value <0.001 <0.001 0.031 <0.001 <0.001 <0.001 <0.001 SEM 0.68 0.20 0.15 0.01 1.04 1.10 1.94 Polynomial Contrasts Loin L C L NS NS NS NS P-Value <001 0.02 <0.001 0.22 0.07 0.13 0.10 SEM 0.21 0.17 0.22 0.01 0.44 0.35 0.22 Belly L C L C NS NS NS P-Value <0.01 0.04 <0.01 0.02 0.13 0.66 0.31 SEM 0.95 0.32 0.21 0.02 0.93 0.99 0.65 A– D Different superscripts within the same column indicate significant differences (p<0.05). F-T cycle = freeze thaw cycle; L=linear; C=cubic; NS=no significant Table 2. Effect of freeze-thaw cycles on thawing loss in the loin and belly of pork F-T cycle 1 F-T cycle 2 F-T cycle 3 F-T cycle 4 P value SEM Loin thaw loss (%) 9.20±6.01 C 4.47±2.10 B 2.34±0.95 AB 1.39±0.54 A <0.01 0.69 Belly thaw loss (%) 0.98±0.38 1.02±0.50 0.82±1.02 0.58±0.63 0.47 0.11 Orthogonal contrast Loin thaw loss vs Belly thaw loss <0.01 0.39 Polynomial contrasts Loin thaw loss (%) L <0.01 0.68 Belly thaw loss (%) NS 0.16 0.11 A–C Different superscripts within the same column indicate significant differences (p<0.05). F-T cycle = freeze thaw cycle; L=linear; NS=no significant Table 3. Effect of freeze-thaw Cycles on cooking loss in the loin and belly of pork Fresh meat F-T cycle 4 P value SEM Cook loss loin (%) 33.01±1.34 27.82±1.49 <0.01 0.67 Cook loss belly (%) 13.23±3.20 14.23±3.22 0.50 0.71 P value <0.01 <0.01 SEM 2.33 1.65 F-T cycle = freeze thaw cycle Table 4 Effect of freeze-thaw cycles on muscle characteristics in the loin and belly of pork Fresh meat F-T cycle 1 F-T cycle 2 F-T cycle 3 F-T cycle 4 P value SEM Loin Muscle fiber diameter (μm) 48.59±12.19 55.77±3.93 46.39±6.21 51.98±8.75 47.21±8.16 0.44 1.74 Endomysium thickness (μm) 14.56±1.85 BC 14.44±2.81 BC 17.02±0.94 C 10.87±2.49 AB 8.24±3.20 A 0.01 0.90 Perimysium thickness (μm) 71.19±30.99 87.11±12.96 80.48±27.56 72.44±25.61 70.57±39.49 0.90 5.88 Belly Muscle fiber diameter (μm) 45.33±6.59 AB 53.50±4.59 B 44.16±10.47 AB 39.88±5.15 A 39.52±2.49 A 0.05 1.73 Endomysium thickness (μm) 14.67±1.85 B 14.43±2.81 B 13.66±1.20 B 12.69±2.76 A 9.84±1.40 A 0.03 0.58 Perimysium thickness (μm) 72.20±23.31 77.03±21.84 66.45±14.59 63.78±19.47 98.26±37.01 0.33 5.60 Orthogonal Contrast: Loin vs Belly Muscle fiber diameter (μm) 0.02 1.28 Endomysium thickness (μm) 0.87 0.53 Perimysium thickness (μm) 0.92 4.01 Polynomial Contrasts: F-T cycles vs Fiber characteristics Loin: Muscle fiber diameter (μm) NS 0.96 1.73 Loin: Endomysium thickness (μm) NS 0.22 0.89 Loin: Perimysium thickness (μm) NS 0.96 5.88 Belly: Muscle fiber diameter (μm) NS 0.09 1.72 Belly: Endomysium thickness (μm) NS 0.17 0.58 Belly: Perimysium thickness (μm) NS 0.52 5.60 A–C Different superscripts within the same column indicate significant differences (p<0.05). F-T cycle = freeze thaw cycle; NS=no significant Additional Declarations No competing interests reported. Supplementary Files Supplementaryfile.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6850843","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":479360146,"identity":"2bcb39d6-f0db-46b3-af23-d345f6763f7b","order_by":0,"name":"Kannika Umpuch","email":"","orcid":"","institution":"Valaya Alongkorn Rajabhat University Under the Royal Patronage","correspondingAuthor":false,"prefix":"","firstName":"Kannika","middleName":"","lastName":"Umpuch","suffix":""},{"id":479360147,"identity":"a1bcd0e5-1c07-4788-99e3-091451bae375","order_by":1,"name":"Siriporn Namted","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIiWNgGAWjYDACZgaGA3DOBxiDsYFILYwzYKyD+LSgaOchRot8O+/DwwUV9/IYpJufbrZtu5fYwH74AfPHHbi1GBxmNzg840xxMYPMMbPbuW3FiQ08aQYMB8/g0cLMxnCYty0hsUEiwex2zhkggyEH6LA2PA5rhmtJ/3bbAqSF/w1+LQyH4VpyzG4zVIAZ+LUYgLTMABreJpFTdrOnIsG4TeKZwYGz+BzWf4z5cwHQ8H6J9G03fhgkyPbzJz98UInPYQzg2GRgYIPxQIwD+DVAtYyCUTAKRsEowAkAvalQ7oI4DTYAAAAASUVORK5CYII=","orcid":"","institution":"Valaya Alongkorn Rajabhat University Under the Royal Patronage","correspondingAuthor":true,"prefix":"","firstName":"Siriporn","middleName":"","lastName":"Namted","suffix":""}],"badges":[],"createdAt":"2025-06-09 05:23:57","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6850843/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6850843/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85928639,"identity":"15bc5f4b-04f5-49de-9b10-1fe4d15195fc","added_by":"auto","created_at":"2025-07-03 09:04:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":285490,"visible":true,"origin":"","legend":"\u003cp\u003eThe muscle fiber characteristics of loin samples (fresh (A), freeze-thawed 1 cycle (B), freeze-thawed 2 cycle (C), freeze-thawed 3 cycle (D), freeze-thawed 4 cycle (E))\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6850843/v1/cf2aab5c8ed64b5ee45e65b9.png"},{"id":85928622,"identity":"8dd53b8a-dbea-414f-930b-fccc0afca94a","added_by":"auto","created_at":"2025-07-03 09:04:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":218199,"visible":true,"origin":"","legend":"\u003cp\u003eThe muscle fiber characteristics of belly samples. fresh (A1, A2), freeze-thawed 1 cycle (B1, B2), freeze-thawed 2 cycle (C1, C2), freeze-thawed 3 cycle (D1, D2), freeze-thawed 4 cycle (E1, E2)\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6850843/v1/9c562a37b87e2b94358948b8.png"},{"id":99789070,"identity":"7dd0ab2f-dca9-411c-a0e4-444d7823b3f5","added_by":"auto","created_at":"2026-01-08 12:48:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1277972,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6850843/v1/974b9bf6-5e23-4c18-9d12-dd17d9a48e85.pdf"},{"id":85929718,"identity":"7994fd1d-9889-46a0-a4fb-bb3a34da2e39","added_by":"auto","created_at":"2025-07-03 09:12:30","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":46115,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-6850843/v1/c88548d4278626c34b681efa.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparing Freeze-Thaw Cycle Effects on Pork Loin and Belly Quality and Muscle Characteristics","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRetail prices for pork belly and loin are projected at baht/kg and 185\u0026ndash;190 baht/kg, respectively. Pork belly accounts for 9.62% of the whole carcass, while loin comprises 6.28% [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Pork belly contains 16.00\u0026ndash;16.95% protein and 27.72\u0026ndash;31.91% fat, compared to pork loin's 20.65\u0026ndash;23.65% protein and 1.89\u0026ndash;2.91% fat [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePork belly is a prized ingredient in Thai cuisine, valued for its balance of fat and lean muscle, which contributes to its flavor and tenderness. It features traditional dishes and street foods. Due to its high fat content, pork belly is both desirable and economically significant. According to KResearch [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], it is in strong demand domestically and internationally, particularly in regions where it is used in products such as bacon. In Thailand, the quantity and quality of pork belly are key determinants of its market value. Therefore, it is crucial to monitor pricing trends for both pork belly and loin, especially concerning processing and storage conditions.\u003c/p\u003e \u003cp\u003eMeat is highly perishable, and its quality is influenced by processing and storage conditions. Freezing is a commonly used preservation technique that extends shelf life and ensures food safety. Meat contains 50\u0026ndash;75% water, which freezes during chilling [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, repeated F-T cycles can lead to significant degradation of meat quality, affecting its physicochemical properties, protein structure, water-holding capacity, and texture [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The formation of ice crystals during freezing disrupts muscle microstructure, resulting in cell membrane rupture, protein denaturation, and moisture loss [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Although previous studies have explored the impact of repeated freeze-thaw (F-T) cycles on various meat types [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], their specific effects on the muscle characteristics and quality of pork loin and belly remain underexplored.\u003c/p\u003e \u003cp\u003eThis study examines the effects of repeated F-T cycles on the quality and muscle characteristics of pork loin and belly, aiming to optimize preservation techniques for high-value pork products.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eFunding Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was partially funded by the Department of Agriculture, Faculty of Agricultural Technology, Valaya Alongkron Rajabhat University, Thailand. The remaining resources were supported by the authors without external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not involve any experiments on humans or animals, and therefore, no ethics approval or consent was required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMuscle Sampling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA Total of fifty muscle samples were collected from commercial pigs and were randomly selected from a local meat distributor in Thailand. All pork samples were placed in an icebox and transported to the laboratory. Visible fat and connective tissue on the surface were carefully removed, after which the pork samples were cut into 2.5 cm-thick pieces perpendicular to the fiber direction, with each piece weighing 75.00 \u0026plusmn; 5.00 g.\u003c/p\u003e\n\u003cp\u003eThe samples were then frozen and stored at \u0026minus;18 \u0026plusmn; 1 \u0026deg;C for 4.5 days, followed by thawing at 4 \u0026plusmn; 0.5 \u0026deg;C for 24 h, representing one F-T cycle [10]. All loin and belly pork samples were individually packed and randomly divided into five groups corresponding to 0, 1, 2, 3, and 4 F-T cycles.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThawing Loss and Cooking Loss Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThawing loss was calculated as a percentage of weight loss in pork samples subjected to different F-T cycles, following the method described by Tippala et al. [11]. Briefly, the pork samples were weighed prior to freezing (M1). After thawing, surface water was removed using paper towels, and the samples were weighed again, with the weight recorded as M2. The thawing loss was calculated using the following formula:\u003c/p\u003e\n\u003cp\u003eThawing Loss (%) = ((M1 \u0026minus; M2) / M1) \u0026times;100%\u003c/p\u003e\n\u003cp\u003eThe samples were then placed in cooking bags and immersed in a 72\u0026deg;C water bath until the core temperature reached 70\u0026deg;C. After reaching the target temperature, the samples were cooled to room temperature by immersion in water and subsequently weighed again. Cooking loss was calculated using the following formula:\u003c/p\u003e\n\u003cp\u003eCooking Loss (%) = ((M1 \u0026minus; M2) / M1) \u0026times;100%\u003c/p\u003e\n\u003cp\u003ewhere M1 is the weight before cooking, and M2 is the weight after cooking.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003epH and Meat Color Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe pH of the samples was determined using a pH meter (Orion 2 Star, Thermo Scientific, USA), which was standardized with reference buffers of pH 4.01 and 7.00, both allowed to stabilize at 25 \u0026deg;C prior to measurement [12].\u003c/p\u003e\n\u003cp\u003eMeat color characteristics (CIE L*, a*, and b*) were evaluated on the muscle surface using a Minolta Colorimeter (CR-300, Minolta Co., Tokyo, Japan). The instrument was calibrated with a white reference standard (Y = 93.5, x = 0.3132, y = 0.3198). Color measurements for both fresh and thawed samples were taken on freshly exposed surfaces after permitting the meat to bloom for 30 minutes [12]. Three measurements were recorded for each sample to ensure accuracy. The total color difference (\u0026Delta;E) was calculated using the following equation:\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"156\" height=\"27\"\u003e\u003c/p\u003e\n\u003cp\u003ewhere \u003cimg src=\"data:image/png;base64,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\" width=\"289\" height=\"21\"\u003e, represent the lightness, redness/greenness, and yellowness/blueness values of fresh pork meat and F-T pork meat, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMoisture Protein and Fat Content\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMoisture and protein content were determined using a procedure from AOAC [13-14]. The total moisture content of 3 g of samples placed in aluminum moisture pans was calculated from their pre-dried and dried weights (dried in an air oven at 104\u0026deg;C for 24 hours) and expressed as a percentage of the pre-dried weight and grams of water per gram of dry weight. Moisture content was measured in triplicate for each sample. Fat was extracted from 5 g of meat using chloroform/methanol (2:1), following the procedure outlined by Folch et al. [15].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHistochemical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHistological evaluation was carried out on the porcine longissimus dorsi muscle from fresh meat, F-T 1 cycle, F-T 2 cycles, F-T 3 cycles, and F-T 4 cycles. The samples were cut into pieces measuring 0.5 \u0026times; 0.5 \u0026times; 1.0 cm and promptly fixed in a 10% buffered neutral formalin solution for 24 hours. Following fixation, the specimens were dehydrated with alcohol, cleared with xylene, infiltrated, and subsequently embedded in paraffin. Thin sections were cut to a thickness of 3 \u0026mu;m and stained with hematoxylin and eosin for general microscopic examination.\u003c/p\u003e\n\u003cp\u003eStained cross-sections were captured using a light microscope (Olympus FSX100, Tokyo, Japan) equipped with a 10\u0026times; objective lens and a 10\u0026times; eyepiece. Five images of distinct cross-sections from each muscle were captured. The samples were analyzed using Image-J software (National Institute of Mental Health, Bethesda, MD, USA).\u003c/p\u003e\n\u003cp\u003eApproximately 300 fibers from five randomly selected fields in each muscle were measured to determine fiber diameters (\u0026mu;m). The thickness of the endomysium and perimysium was evaluated for each sample. Structural components were measured within a fiber bundle area, with 40 measurements taken for the endomysium thickness (\u0026mu;m) and 10 measurements for the perimysium thickness (\u0026mu;m) per image. The mean thickness was calculated based on the collected measurements [11,16].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003eThe experiment was designed as a completely randomized design (CRD) with multiple F-T cycles as the main treatment factor. Data were analyzed using analysis of variance (ANOVA) with the General Linear Model (GLM) procedure in SAS statistical software (ver. 6.4; SAS Institute, Cary, NC, USA). Differences among treatment means were determined using Duncan\u0026rsquo;s multiple range test (p \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eyij\u003c/em\u003e = \u003cem\u003e\u0026mu;\u0026nbsp;\u003c/em\u003e+ \u003cem\u003e\u0026tau;i\u0026nbsp;\u003c/em\u003e+ \u003cem\u003eϵij\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003ewhere \u003cem\u003e\u0026mu;\u003c/em\u003e = overall mean, \u003cem\u003e\u0026tau;i\u003c/em\u003e = treatment effect of the \u003cem\u003ei\u003c/em\u003e-th F-T cycle, and \u003cem\u003eϵij\u003c/em\u003e = random error.\u003c/p\u003e\n\u003cp\u003eTo evaluate the effects of repeated F-T cycles on pork quality attributes and muscle characteristics, polynomial contrast analysis was performed to assess linear, quadratic, and cubic trends in response to increasing F-T cycles. Additionally, orthogonal contrast analysis was employed to compare differences between pork loin and belly samples across measured variables, particularly focusing on thawing loss, color attributes, and muscle fiber characteristics. All statistical analyses were conducted at a significance level of p \u0026lt; 0.05, and results were reported as means \u0026plusmn; standard error.\u003c/p\u003e"},{"header":"Results and Discussions","content":"\u003cp\u003e\u003cstrong\u003eEffect of Pork Type on Color, pH and Chemical Composition\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePork Loin\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe lightness (L*) of loin samples significantly increased with successive F-T cycles. Fresh meat had the lowest CIE L* value (53.10), while the 4th F-T cycle recorded the highest (55.56), with significant differences (p \u0026lt; 0.01). Redness (a*) decreased after the 1st F-T cycle, reaching its lowest value (9.65) in the 2nd cycle. Significant differences were observed across cycles (p \u0026lt; 0.01). Yellowness (b*) in fresh meat increased from 12.19 in fresh meat to 16.44 in the 4th F-T cycle (p \u0026lt; 0.01). Total color difference (\u0026Delta;E) was significantly higher in repeated F-T cycles than in fresh meat (p \u0026lt; 0.01) (Table 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003epH values remained stable between 5.68 and 5.73 (p = 0.39). Moisture content decreased slightly with each F-T cycle, with fresh meat showing the highest value (70.19%), though this change was not statistically significant (p = 0.07). Protein and fat contents were not significantly impacted by the F-T cycles (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePork Belly\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe lightness (L*) of belly samples significantly increased with successive F-T cycles (p = 0.01), with fresh meat having the lowest L* value (59.90), while the highest values were observed in the third (68.08) and fourth cycles (65.62). Redness (a*) showed no significant differences. Yellowness (b*) in fresh meat increased from 13.42 in fresh meat to 16.82 in the fourth cycle (p \u0026lt; 0.01). Total color difference (\u0026Delta;E) tended to increase with repeated F-T cycles (p = 0.08) (Table 1).\u003c/p\u003e\n\u003cp\u003eThe pH values exhibited a borderline significant difference (p = 0.05), with the lowest in the 1st F-T cycle (5.81) and higher values in fresh meat and later cycles (5.96\u0026ndash;6.01). Moisture and protein content were unaffected by F-T cycles. Fat content showed a tendency to change (p = 0.08), decreasing in the 1st and 2nd cycles before slightly increasing from 26.73% to 29.84% in the 4th cycle (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eComparison\u003c/em\u003e\u003cem\u003eB\u003c/em\u003e\u003cem\u003eetween Pork Loin and Belly\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA comparative analysis of the effects of F-T cycles on the color and chemical composition of pork loin and belly is presented in Table 1. Pork type significantly affected (p \u0026lt; 0.001) the CIE L*, CIE a*, and pH values. Pork belly exhibited higher CIE L* (p \u0026lt; 0.01), lower CIE a* (p \u0026lt; 0.01), and higher CIE b* (p = 0.03) values, suggesting a lighter and less red appearance compared to pork loin. Additionally, pork loin showed significantly lower pH values than pork belly (p \u0026lt; 0.01).\u003c/p\u003e\n\u003cp\u003ePolynomial contrast analysis revealed that F-T cycles significantly affected the color parameters of both loin and belly. CIE L* and CIE b* values increased linearly in both cuts (P \u0026lt; 0.01), with pH and CIE a* following a cubic trend in belly (p \u0026lt; 0.05). No significant changes were observed in moisture, protein, or fat content (p \u0026gt; 0.05).\u003c/p\u003e\n\u003cp\u003ePork loin had higher moisture and protein content but lower fat content than pork belly. The color differences in pork are linked to its chemical composition, including protein, fat, and water content. Pork belly typically contains more fat than loin, which explains its higher\u0026nbsp;CIE L* and CIE b* values. The higher protein content in pork loin may contribute to a lower pH and increased drip loss. According to Huff-Lonergan and Lonergan [17], meat with higher protein and water content tends to have lower pH and higher drip loss. However, Medić et al. [12] found that frozen storage for 6\u0026ndash;18 months increased meat pH, likely due to proteolysis releasing amino acids and dipeptides [18]. Unexpectedly, in this study, the F-T cycle had no effect on pork loin pH, while belly pH followed a cubic trend.\u003c/p\u003e\n\u003cp\u003eRepeated F-T cycles disrupt muscle structures, releasing pro-oxidants like non-heme iron, which accelerate lipid oxidation [19]. Ice crystal formation during thawing further damages cells by expanding within muscle fibers, promoting oxidative deterioration, increasing water loss, and worsening meat color [20]. In this study, CIE L* and CIE b* values of both pork loin and belly increased significantly and linearly with each F-T cycle, while CIE a* followed a cubic trend. The increase in CIE L* and CIE b* values is likely due to structural damage from repeated F-T cycles, leading to moisture loss and greater surface reflectivity, making the meat appear lighter and more yellow [21]. The cubic trend in CIE a* suggests that initial myoglobin oxidation darkens the meat temporarily, but continued F-T cycles accelerate oxidative degradation, reducing redness [22]. After four cycles, water loss increases, and hemoglobin degradation appears to stabilize.\u003c/p\u003e\n\u003cp\u003eRepeated F-T cycles significantly accelerate lipid oxidation, often resulting in the degradation of unsaturated fatty acids [23]. Qi et al. [24] reported reductions in saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), and individual free fatty acids following the first F-T cycle, likely due to the loss of compounds in the drip during thawing. Consistent with these findings, the present study observed a similar trend, with a noticeable decrease in fat content. Moreover, Han et al. [25] emphasized that repeated F-T cycles reduce moisture content, further exacerbating quality deterioration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffect of Pork Types and F-T Cycle on Thawing Loss\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOrthogonal contrast analysis revealed a significant difference in thawing loss between pork loin and belly (P \u0026lt; 0.01), with loin samples exhibiting greater water loss. Thaw loss in pork loin significantly decreased across F-T cycles (P \u0026lt; 0.01), from 9.20% in the first cycle to 1.39% in the fourth cycle. In contrast, thaw loss in pork belly showed minimal variation (P = 0.47) (Table 2).\u003c/p\u003e\n\u003cp\u003ePolynomial contrast analysis indicated a significant linear trend (P \u0026lt; 0.01) for pork loin, with a continuous reduction in thawing loss as the number of F-T cycles increased. However, belly samples exhibited no significant trend (P \u0026gt; 0.05), suggesting that repeated F-T cycles had minimal effect on moisture loss in pork belly muscle (Table 2).\u003c/p\u003e\n\u003cp\u003eRepeated F-T cycles typically decrease water-holding capacity (WHC) due to muscle fiber damage caused by ice crystal formation [5]. Wachirasiri et al. [26] also observed significant reductions in WHC with repeated F-T cycles, leading to deterioration in texture and sensory properties [6,17,27]. While the higher fat content in pork belly may help mitigate WHC loss, protein denaturation remains a significant factor affecting moisture retention [2,8]. This study suggests that the higher fat and lower protein content of pork belly enhance moisture retention and reduce thawing loss compared to pork loin.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffect of Pork Types and F-T Cycle on Cooking Loss\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCooking loss differed significantly between pork loin and belly (Table 3), with loin exhibiting greater loss (33.01%) than belly (13.23%) (p \u0026lt; 0.01). In loin, cooking loss decreased significantly after the 4th F-T cycle, from 33.01% in fresh meat to 27.82% (p \u0026lt; 0.05). However, in pork belly, no significant change was observed between fresh (13.23%) and 4th F-T cycle samples (14.23%) (P = 0.50).\u003c/p\u003e\n\u003cp\u003ePork belly exhibited significantly lower cooking loss than loin, likely due to its higher fat and lower protein content, which may mitigate muscle protein degradation during cooking. Medić et al. [12] reported that the highest cooking loss occurred in fresh meat, whereas storage at \u0026minus;18\u0026deg;C for 3\u0026ndash;6 months reduced this effect. Repeated freezing and thawing promotes water exudation, leading to a decline in moisture content over time [28]. Consequently, freeze-thawed meat retains less water, reducing the volume available for release during cooking. This aligns with Schulte et al. [29], who demonstrated that freezing alters muscle water retention. In the present study, F-T cycles had no significant impact on pork belly cooking loss.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffect of Pork Types and F-T Cycle on Muscle Fiber Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe effects of pork type and F-T cycles on muscle fiber characteristics are shown in Table 4. Orthogonal contrast analysis identified a significant difference in muscle fiber diameter (p = 0.02), with belly muscle exhibiting larger fibers than loin. There were no significant differences in endomysium and perimysium thickness between the loin and belly (p = 0.873 and p = 0.923, respectively).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEndomysium thickness in the loin significantly decreased with repeated F-T cycles, peaking at 17.02 \u0026micro;m in the second cycle and reaching its lowest value of 8.24 \u0026micro;m in the fourth cycle (p = 0.01) (Fig. 1 and 2). Additionally, muscle fiber diameter in the belly tended to be smaller in the third and fourth cycles compared to the first cycle (p = 0.05), indicating a possible trend of fiber shrinkage with repeated F-T cycles, with these cycles also exhibiting lower endomysium thickness than the other groups (p = 0.03). However, polynomial contrast analysis revealed no significant impact of F-T cycles on muscle fiber diameter, endomysium and perimysium thickness.\u003c/p\u003e\n\u003cp\u003eThis study reveals that pork belly has a larger muscle diameter than pork loin. Huff-Lonergan and Lonergan [17] suggest that muscle fiber size and structure are key factors influencing meat quality, with the more active loin containing smaller fibers and the less active, fattier belly containing larger fibers. While polynomial contrast analysis showed no significant effect of F-T cycles on muscle fiber characteristics, the third and fourth F-T cycles significantly reduced endomysium thickness in both pork loin and belly.\u003c/p\u003e\n\u003cp\u003eRepeated F-T cycles disrupt the endomysium, creating gaps between muscle fibers, as observed by Qi et al. [24]. These cycles exacerbate mechanical damage by causing the melting and recrystallization of ice crystals, which disrupt lysosomal integrity and release enzymes that contribute to the partial degradation of myofibrillar proteins [19]. This degradation can further compromise meat quality [30]. Therefore, our findings indicate that repeated F-T cycles may contribute to muscle tissue damage and potential deterioration of meat quality. These effects appeared more prominent after three cycles and may vary depending on the pork cut. Therefore, limiting the number of F-T cycles to fewer than three could help preserve meat texture and overall quality, particularly in pork loin, which showed greater sensitivity compared to pork belly.\u003c/p\u003e"},{"header":"Conclusion ","content":"\u003cp\u003ePork loin and belly differed in color, pH, and chemical composition, with both affected by F-T cycles. Pork belly showed better water retention, with less thaw and cooking loss, while loin experienced reduced muscle fiber size and endomysium thickness. Limiting F-T cycles to fewer than three may help maintain quality in both cuts.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study evaluated only pork loin and belly under laboratory-controlled F-T cycles, which may differ from commercial conditions. External factors such as packaging methods, freezing rates as well as extended storage durations were not assessed. Additionally, sensory characteristics and oxidative stability were not evaluated, which could further inform consumer acceptance and shelf-life implications.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics Declaration\u003c/h2\u003e \u003cp\u003eThis study did not involve any experiments on humans or animals, and therefore, no ethics approval or consent was required.\u003c/p\u003e \u003ch2\u003eFunding Statement\u003c/h2\u003e \u003cp\u003eThis research was partially funded by the Department of Agriculture, Faculty of Agricultural Technology, Valaya Alongkron Rajabhat University, Thailand. The remaining resources were supported by the authors without external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eS.N. and K.U. wrote the main manuscript text and S.N. prepared table aand figures. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript or supplementary information files.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKim GW, Kim HY. Comparison of physicochemical properties between standard and sow pork. Korean J Food Sci Anim Resour. 2018;38:1120-1130. https://doi.org/10.5851/kosfa.2018.e45.\u003c/li\u003e\n\u003cli\u003eHoa VB, Seol K, Seo H, Kang S, Kim Y, Seong P, Moon S, Kim J, Cho S. Investigation of physicochemical and sensory quality differences in pork belly and shoulder butt cuts with different quality grades. Food Sci Anim Resour. 2021;41:224-236. https://doi.org/10.5851/kosfa.2020.e91.\u003c/li\u003e\n\u003cli\u003eKResearch. The trend of pork prices in Thailand in 2023. In: Kasikorn Research Center. 2023. https://www.kasikornresearch.com/en/analysis/k-social-media/Pages/Pig-Price-FB-18-08-2023.aspx. Accessed 23 Apr 2025.\u003c/li\u003e\n\u003cli\u003eHeinz G, Hautzinger P. Meat processing technology: for small-to medium scale producers. Bangkok: Food and Agriculture Organization of the United Nations, Regional Office for Asia and the Pacific; 2007.\u003c/li\u003e\n\u003cli\u003eLeygonie C, Britz TJ, Hoffman LC. Impact of freezing and thawing on the quality of meat: review. Meat Sci. 2012;91:93-98.\u003c/li\u003e\n\u003cli\u003eZhang B, Cao HJ, Lin HM, Deng SG, Wu H. Insights into ice-growth inhibition by trehalose and alginate oligosaccharides in peeled Pacific white shrimp (\u003cem\u003eLitopenaeus vannamei\u003c/em\u003e) during frozen storage. Food Chem. 2019;278:482\u0026ndash;490.\u003c/li\u003e\n\u003cli\u003eKiani H, Sun DW. Water crystallization and its importance to freezing of foods: a review. Trends Food Sci Technol. 2011;22:407\u0026ndash;426.\u003c/li\u003e\n\u003cli\u003eAli S, Zhang WG, Rajput N, Khan MA, Li CB, Zhou GH. 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Mechanisms of water-holding capacity of meat: The role of postmortem biochemical and structural changes. Meat Sci. 2005;71:194-204.\u003c/li\u003e\n\u003cli\u003eZhang R, Yoo MJY, Farouk MM. Oxidative stability, proteolysis, and in vitro digestibility of fresh and long-term frozen stored in-bag dry-aged lean beef. Food Chem. 2021;344:128601.\u003c/li\u003e\n\u003cli\u003eBenjakul S, Bauer F. Physicochemical and enzymatic changes of cod muscle proteins subjected to different freeze-thaw cycles. J Sci Food Agric. 2000;80:1143-1150.\u003c/li\u003e\n\u003cli\u003eIm C, Song S, Cheng H, Park J, Kim GD. Changes in meat quality and muscle fiber characteristics of beef striploin (\u003cem\u003eM longissimus lumborum\u003c/em\u003e) with different intramuscular fat contents following freeze-thawing. LWT. 2024;198:116081.\u003c/li\u003e\n\u003cli\u003eJeong JY, Kim GD, Yang HS, Joo ST. Effect of freeze-thaw cycles on physicochemical properties and color stability of beef semimembranosus muscle. Food Res Int. 2011;44:3222-3228.\u003c/li\u003e\n\u003cli\u003eRehman SU, Seo JK, Romanyk M, Shin DJ, Kim YHB. Effects of aging and repeated freeze-thaw cycles on quality attributes, physicochemical and biochemical properties, and sensory characteristics of beef sirloins. Appl Food Res. 2024;4:100612.\u003c/li\u003e\n\u003cli\u003eShang X, Du J, Zhao Y, Tian J, Jiang S. Effect of multiple freeze-thaw cycles on lipid degradation and lipid oxidation of grass carp surimi containing different amounts of pork back fat. Food Sci Anim Resour. 2021;41:923-935. doi:10.5851/kosfa.2021.e46.\u003c/li\u003e\n\u003cli\u003eQi J, Li C, Chen Y, Gao F, Xu X, Zhou G. Changes in meat quality of ovine longissimus dorsi muscle in response to repeated freeze and thaw. Meat Sci. 2012;92:619-626.\u003c/li\u003e\n\u003cli\u003eHan J, Sun Y, Sun R, Zhang T, Wang C, Jiang N. Effects of freeze-thaw cycles on physicochemical properties and structure of cooked crayfish (Procambarus clarkii). Food Prod Process Nutr. 2022;4:25.\u003c/li\u003e\n\u003cli\u003eWachirasiri K, Wanlapa S, Uttapap D, Puttanlek C, Rungsardthong V. Effects of multiple freeze-thaw cycles on biochemical and physical quality changes of white shrimp (\u003cem\u003ePenaeus vannamei\u003c/em\u003e) treated with lysine and sodium bicarbonate. J Food Sci. 2019;84:1784-1790.\u003c/li\u003e\n\u003cli\u003eRahman MH, Hossain MM, Rahman SM, Hashem MA, Oh DH. Effect of repeated freeze-thaw cycles on beef quality and safety. Korean J Food Sci Anim Resour. 2014;34:482-495. https://doi.org/10.5851/kosfa.2014.34.4.482.\u003c/li\u003e\n\u003cli\u003eYu Q, Liu S, Liu Q, Wen R, Sun C. Meat exudate metabolomics reveals the impact of freeze-thaw cycles on meat quality in pork loins. Food Chem X. 2024;24:101804.\u003c/li\u003e\n\u003cli\u003eSchulte MD, Johnson LG, Zuber EA, Patterson BM, Outhouse AC, Fedler CA, Steadham EM, King DA, Prusa KJ, Huff-Lonergan E, Lonergan SM. Influence of postmortem aging and post-aging freezing on pork loin quality attributes. Meat Muscle Biol. 2019;3. https://doi.org/10.22175/mmb2019.05.0015\u003c/li\u003e\n\u003cli\u003eLi CB, Li J, Zhou GH, Lametsch R, Ertbjerg P, Br\u0026uuml;ggemann DA, Huang HG, Karlsson AH, Hviid M, Lundstr\u0026ouml;m K. Electrical stimulation affects metabolic enzyme phosphorylation, protease activation, and meat tenderization in beef. J Anim Sci. 2012;90:1638.1649. https://doi.org/10.2527/jas.2011-4514\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Effect of freeze-thaw cycles on meat quality in the loin and belly of pork\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eFresh meat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eF-T cycle 1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eF-T cycle 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eF-T cycle 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eF-T cycle 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003eSEM\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eLoin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eL*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e53.10\u0026plusmn;0.75\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e53.18\u0026plusmn;0.89\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e54.54\u0026plusmn;0.80\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e55.24\u0026plusmn;0.70\u003csup\u003eBC\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e55.56\u0026plusmn;0.97\u003csup\u003eC\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003ea*\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e11.80\u0026nbsp;\u0026plusmn;0.70\u003csup\u003e\u0026nbsp;A\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;11.30\u0026plusmn;7.67\u003csup\u003eAB\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;9.65\u0026plusmn;1.57\u003csup\u003e\u0026nbsp;C\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e10.39\u0026plusmn;1.04\u003csup\u003e\u0026nbsp;BC\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e10.54\u0026plusmn;0.54\u003csup\u003eBC\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eb*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e12.19\u0026plusmn;0.55\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e14.24\u0026plusmn;0.83\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e15.19\u0026plusmn;0.82\u003csup\u003eC\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e15.49\u0026plusmn;0.37\u003csup\u003eC\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e16.44\u0026plusmn;0.41\u003csup\u003eD\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026Delta;E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e2.53\u0026plusmn;0.93\u003csup\u003e\u0026nbsp;A\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e4.33\u0026plusmn;1.63\u003csup\u003e\u0026nbsp;B\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e4.29\u0026plusmn;0.95\u003csup\u003e\u0026nbsp;B\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e5.13\u0026plusmn;0.91\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e5.73\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e5.68\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e5.71\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e5.68\u0026plusmn;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e5.71\u0026plusmn;0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eMoisture (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e70.19\u0026plusmn;1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e68.03\u0026plusmn;2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e66.85\u0026plusmn;2.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e66.90\u0026plusmn;1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e68.69\u0026plusmn;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eProtein (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e26.37\u0026plusmn;1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e27.82\u0026plusmn;2.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e28.10\u0026plusmn;0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e28.49\u0026plusmn;1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e26.19\u0026plusmn;0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eFat (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e3.43\u0026plusmn;0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e4.14\u0026plusmn;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e5.04\u0026plusmn;1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e4.07\u0026plusmn;0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e5.11\u0026plusmn;0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eBelly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eL*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 85px;\"\u003e\n \u003cp\u003e59.27\u0026plusmn;6.95\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 86px;\"\u003e\n \u003cp\u003e59.90\u0026plusmn;5.86\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 88px;\"\u003e\n \u003cp\u003e65.62\u0026plusmn;2.72\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 88px;\"\u003e\n \u003cp\u003e66.01\u0026plusmn;6.05\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 89px;\"\u003e\n \u003cp\u003e68.08\u0026plusmn;5.20\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003ea*\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e9.38\u0026plusmn;2.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e7.66\u0026plusmn;2.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e9.91\u0026plusmn;2.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e9.55\u0026plusmn;1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e8.19\u0026plusmn;1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eb*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 85px;\"\u003e\n \u003cp\u003e13.42\u0026plusmn;1.16\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 86px;\"\u003e\n \u003cp\u003e14.58\u0026plusmn;1.06\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 88px;\"\u003e\n \u003cp\u003e14.91\u0026plusmn;1.10\u003csup\u003eBC\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 88px;\"\u003e\n \u003cp\u003e15.63\u0026plusmn;0.64\u003csup\u003eC\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 89px;\"\u003e\n \u003cp\u003e16.82\u0026plusmn;1.09\u003csup\u003eD\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026Delta;E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 86px;\"\u003e\n \u003cp\u003e5.06\u0026plusmn;2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 88px;\"\u003e\n \u003cp\u003e7.24\u0026plusmn;3.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 88px;\"\u003e\n \u003cp\u003e7.73\u0026plusmn;3.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 89px;\"\u003e\n \u003cp\u003e9.43+4.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 85px;\"\u003e\n \u003cp\u003e5.99\u0026plusmn;0.10\u003csup\u003e\u0026nbsp;B\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 86px;\"\u003e\n \u003cp\u003e5.81\u0026plusmn;0.28\u003csup\u003e\u0026nbsp;A\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 88px;\"\u003e\n \u003cp\u003e5.97\u0026plusmn;0.09\u003csup\u003e\u0026nbsp;B\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 88px;\"\u003e\n \u003cp\u003e5.96\u0026plusmn;0.13\u003csup\u003e\u0026nbsp;B\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 89px;\"\u003e\n \u003cp\u003e6.01\u0026plusmn;0.07\u003csup\u003e\u0026nbsp;B\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eMoisture (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e60.39\u0026plusmn;0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e57.92\u0026plusmn;5.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e55.85\u0026plusmn;1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e56.01\u0026plusmn;3.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e55.06\u0026plusmn;4.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eProtein (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e14.45\u0026plusmn;1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e15.34\u0026plusmn;7.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e15.96\u0026plusmn;2.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e15.94\u0026plusmn;4.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e15.10\u0026plusmn;5.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eFat (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e26.15\u0026plusmn;1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e26.73\u0026plusmn;1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e28.19\u0026plusmn;3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e28.04\u0026plusmn;4.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e29.84\u0026plusmn;1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"15\" valign=\"top\" style=\"width: 602px;\"\u003e\n \u003cp\u003eOrthogonal Contrast\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eL*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003ea*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eb*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003eMoisture (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eProtein (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eFat (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eLoin vs Belly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eSEM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"15\" valign=\"top\" style=\"width: 602px;\"\u003e\n \u003cp\u003ePolynomial Contrasts\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eLoin\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eL\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eP-Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026lt;001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eSEM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eBelly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003eL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eP-Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eSEM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003eA\u0026ndash;\u003c/sup\u003e\u003csup\u003eD\u003c/sup\u003e Different superscripts within the same column indicate significant differences (p\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eF-T cycle = freeze thaw cycle; L=linear; C=cubic; NS=no significant\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. Effect of freeze-thaw cycles on thawing loss in the loin and belly of pork\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003eF-T cycle 1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003eF-T cycle 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003eF-T cycle 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003eF-T cycle 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003eSEM\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eLoin thaw\u0026nbsp;loss (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e9.20\u0026plusmn;6.01\u003csup\u003e\u0026nbsp;C\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e4.47\u0026plusmn;2.10\u003csup\u003e\u0026nbsp;B\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e2.34\u0026plusmn;0.95 \u003csup\u003eAB\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e1.39\u0026plusmn;0.54\u003csup\u003e\u0026nbsp;A\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eBelly thaw\u0026nbsp;loss (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e0.98\u0026plusmn;0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e1.02\u0026plusmn;0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e0.82\u0026plusmn;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e0.58\u0026plusmn;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003eOrthogonal contrast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 47px;\"\u003e\n \u003cp\u003eLoin thaw loss vs Belly thaw loss\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 100px;\"\u003e\n \u003cp\u003ePolynomial contrasts\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003eLoin thaw loss (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 47px;\"\u003e\n \u003cp\u003eL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003eBelly thaw loss (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 47px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003eA\u0026ndash;C\u003c/sup\u003e Different superscripts within the same column indicate significant differences (p\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eF-T cycle = freeze thaw cycle; L=linear; NS=no significant\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3. Effect of freeze-thaw Cycles on cooking loss in the loin and belly of pork\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eFresh meat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003eF-T cycle 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eSEM\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003eCook loss loin (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e33.01\u0026plusmn;1.34\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e27.82\u0026plusmn;1.49\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003eCook loss belly (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e13.23\u0026plusmn;3.20\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e14.23\u0026plusmn;3.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003eP\u0026nbsp;value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003eSEM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e2.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e1.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eF-T cycle = freeze thaw cycle\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4 Effect of freeze-thaw cycles on muscle characteristics in the loin and belly of pork\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eFresh meat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eF-T cycle 1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eF-T cycle 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eF-T cycle 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eF-T cycle 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003eSEM\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eLoin\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eMuscle fiber diameter (\u0026mu;m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e48.59\u0026plusmn;12.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 85px;\"\u003e\n \u003cp\u003e55.77\u0026plusmn;3.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e46.39\u0026plusmn;6.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e51.98\u0026plusmn;8.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e47.21\u0026plusmn;8.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eEndomysium thickness\u0026nbsp;(\u0026mu;m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e14.56\u0026plusmn;1.85\u003csup\u003e\u0026nbsp;BC\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 85px;\"\u003e\n \u003cp\u003e14.44\u0026plusmn;2.81\u003csup\u003e\u0026nbsp;BC\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e17.02\u0026plusmn;0.94\u003csup\u003e\u0026nbsp;C\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e10.87\u0026plusmn;2.49\u003csup\u003e\u0026nbsp;AB\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e8.24\u0026plusmn;3.20\u003csup\u003e\u0026nbsp;A\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003ePerimysium thickness (\u0026mu;m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e71.19\u0026plusmn;30.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 85px;\"\u003e\n \u003cp\u003e87.11\u0026plusmn;12.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e80.48\u0026plusmn;27.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e72.44\u0026plusmn;25.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e70.57\u0026plusmn;39.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e5.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eBelly\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eMuscle fiber diameter (\u0026mu;m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e45.33\u0026plusmn;6.59\u003csup\u003e\u0026nbsp;AB\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 85px;\"\u003e\n \u003cp\u003e53.50\u0026plusmn;4.59\u003csup\u003e\u0026nbsp;B\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e44.16\u0026plusmn;10.47\u003csup\u003e\u0026nbsp;AB\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e39.88\u0026plusmn;5.15\u003csup\u003e\u0026nbsp;A\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e39.52\u0026plusmn;2.49\u003csup\u003e\u0026nbsp;A\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e1.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eEndomysium thickness\u0026nbsp;(\u0026mu;m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e14.67\u0026plusmn;1.85\u003csup\u003e\u0026nbsp;B\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 85px;\"\u003e\n \u003cp\u003e14.43\u0026plusmn;2.81\u003csup\u003e\u0026nbsp;B\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e13.66\u0026plusmn;1.20\u003csup\u003e\u0026nbsp;B\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e12.69\u0026plusmn;2.76\u003csup\u003e\u0026nbsp;A\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e9.84\u0026plusmn;1.40\u003csup\u003e\u0026nbsp;A\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003ePerimysium thickness (\u0026mu;m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e72.20\u0026plusmn;23.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 85px;\"\u003e\n \u003cp\u003e77.03\u0026plusmn;21.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e66.45\u0026plusmn;14.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e63.78\u0026plusmn;19.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e98.26\u0026plusmn;37.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e5.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 601px;\"\u003e\n \u003cp\u003eOrthogonal Contrast: Loin vs Belly\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 512px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Muscle fiber diameter (\u0026mu;m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 512px;\"\u003e\n \u003cp\u003e\u0026nbsp; Endomysium thickness (\u0026mu;m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 512px;\"\u003e\n \u003cp\u003e\u0026nbsp; Perimysium thickness (\u0026mu;m)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e4.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 601px;\"\u003e\n \u003cp\u003ePolynomial Contrasts: F-T cycles vs Fiber characteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003eLoin: Muscle fiber diameter (\u0026mu;m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 311px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e1.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003eLoin: Endomysium thickness (\u0026mu;m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 311px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003eLoin: Perimysium thickness (\u0026mu;m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 311px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e5.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003eBelly: Muscle fiber diameter (\u0026mu;m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 311px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003eBelly: Endomysium thickness (\u0026mu;m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 311px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003eBelly: Perimysium thickness (\u0026mu;m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 311px;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e5.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003eA\u0026ndash;C\u003c/sup\u003e Different superscripts within the same column indicate significant differences (p\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eF-T cycle = freeze thaw cycle; NS=no significant\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"freeze-thaw cycle, pork loin, pork belly, meat quality, muscle characteristics","lastPublishedDoi":"10.21203/rs.3.rs-6850843/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6850843/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study examined the effects of repeated freeze-thaw (F-T) cycles on pork loin and belly, two economically important cuts in Thai cuisine. Fifty samples underwent 0\u0026ndash;4 F-T cycles, with evaluations of thawing and cooking loss, pH, color (CIE L*, CIE a*, CIE b*), chemical composition, and histological structure. Pork belly showed significantly higher CIE L* and CIE b* values and lower CIE a* than loin (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). F-T cycles led to linear increases in CIE L* and CIE b* (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while CIE a* and pH in belly exhibited cubic trends (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Thawing loss decreased linearly in loin (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) but remained unchanged in belly (p\u0026thinsp;=\u0026thinsp;0.47). Cooking loss was lower in belly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), likely due to higher fat content. Histological analysis revealed progressive fiber disruption and reduced endomysium thickness (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Pork belly exhibited greater resilience to F-T cycles, with better moisture and structural retention. Limiting F-T cycles to fewer than three is recommended to maintain pork quality.\u003c/p\u003e","manuscriptTitle":"Comparing Freeze-Thaw Cycle Effects on Pork Loin and Belly Quality and Muscle Characteristics","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-03 09:04:24","doi":"10.21203/rs.3.rs-6850843/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"12d8f4cd-b766-48bf-a0d0-b3503bdd9a82","owner":[],"postedDate":"July 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":50898142,"name":"Biological sciences/Physiology"},{"id":50898143,"name":"Biological sciences/Zoology"}],"tags":[],"updatedAt":"2026-01-01T08:38:54+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-03 09:04:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6850843","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6850843","identity":"rs-6850843","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}