Abstract:The objective was to characterize ham and loin quality of carcasses ranging from 78 to 145 kg (average ∼119 kg). Hot carcass weight (HCW), back fat depth, and loin depth was measured on 666 carcasses. Loin pH, instrumental and visual color and iodine value of clear plate fat (all 3 layers) was measured on approximately 90% of the population. Quality measurements of the ham, 14 d aged loin and chop, and loin chop shear force (SSF) were evaluated on approximately 30% of the population. Myosin heavy chain fiber t… Show more
“…Moreover, it is important to note that carcass composition traits are typically less affected by environmental variations when compared with other heritable traits like reproduction and growth performance ( Akanno et al, 2013 ). These data along with other recent heavy weight pork carcass data (notably Price et al, 2019 ) indicate that the relationships between carcass weight and leanness parameters are highly variable at all weights of pigs, and that allometric growth (and composition) is likely not being significantly altered in heavier pigs.…”
Section: Resultssupporting
confidence: 59%
“…Once pigs have reached homeostasis and energy is no longer required for skeletal and muscle growth, it is theorized that fat is first deposited in the form of subcutaneous fat, followed by intermuscular fat, and then intramuscular fat ( De Smet et al, 2004 ). Therefore, genetics companies have shifted their efforts to pigs with a greater mature size and an increasing number of pork processors have begun to focus on the greater slaughter weight, which in turn yields a leaner product while maintaining an acceptable level of fat ( Strzelecki et al, 1998 ; Price et al, 2019 ).…”
Section: Resultsmentioning
confidence: 99%
“…Several recent studies and market assessments have indicated that the weight of pork carcasses is expected to increase in upcoming years ( Morin et al, 2015 ; Harsh et al, 2017 ; Rice et al, 2018 ; Gilleland et al, 2019 ; Price et al, 2019 ). Harsh et al (2017) goes as far as to state predictions for carcass weights in the future, which were stated as 104 kg in 2030, 111 kg in 2040, and 118 kg in 2050.…”
Section: Resultsmentioning
confidence: 99%
“…Thus, fat depth, muscle depth, and predicted leanness are often the only carcass leanness parameters evaluated in commercial pigs. Several research studies have characterized the correlation between pork carcass weight and leanness parameters ( Kure, 1997 ; Ohlmann and Jones, 2011 ; Plà-aragonés et al, 2013 ; Rodríguez et al, 2014 ; Price et al, 2019 ). However, there still exist many misunderstandings among the relationship of pork carcass weight and leanness parameters, particularly in commercially representative pigs marketed under current times and conditions.…”
This study aimed to examine the correlation of carcass weight, fat depth, muscle depth, and predicted lean yield in commercial pigs. Data were collected on 850,819 pork carcasses from the same pork processing facility between October 2017 and September 2018. Hot carcass weight was reported following slaughter as a head-on weight; while fat and muscle depth were measured with a Destron PG-100 probe and used for the calculation of predicted lean yield based on the Canadian Lean Yield (CLY) equation [CLY (%) = 68.1863 − (0.7833 × fat depth) + (0.0689 × muscle depth) + (0.0080 × fat depth2) − (0.0002 × muscle depth2) + (0.0006 × fat depth × muscle depth)]. Descriptive statistics, regression equations including coefficients of determination, and Pearson product moment correlation coefficients (when assumptions for linearity were met) and Spearman’s rank-order correlation coefficients (when assumptions for linearity were not met) were calculated for attributes using SigmaPlot, version 11 (Systat Software, Inc., San Jose, CA). Weak positive correlation was observed between hot carcass weight and fat depth (r = 0.289; P < 0.0001), and between hot carcass weight and muscle depth (r = 0.176; P < 0.0001). Weak negative correlations were observed between hot carcass weight and predicted lean yield (r = −0.235; P < 0.0001), and between fat depth and muscle depth (r = −0.148; P < 0.0001). Upon investigation of relationships between fat depth and predicted lean yield, and between muscle depth and predicted lean yield using scatter plots, it was determined that these relationships were not linear and therefore the assumptions of Pearson product moment correlation were not met. Thus, these relationships were expressed as nonlinear functions and Spearman’s rank-order correlation coefficients were used. A strong negative correlation was observed between fat depth and predicted lean yield (r = −0.960; P < 0.0001), and a moderate positive correlation was observed between muscle depth and predicted lean yield (r = 0.406; P < 0.0001). Results from this dataset revealed that hot carcass weight was generally weakly correlated (r < |0.35|) with fat depth, muscle depth, and predicted lean yield. Therefore, it was concluded that there were no consistent weight thresholds where pigs were fatter or heavier muscled.
“…Moreover, it is important to note that carcass composition traits are typically less affected by environmental variations when compared with other heritable traits like reproduction and growth performance ( Akanno et al, 2013 ). These data along with other recent heavy weight pork carcass data (notably Price et al, 2019 ) indicate that the relationships between carcass weight and leanness parameters are highly variable at all weights of pigs, and that allometric growth (and composition) is likely not being significantly altered in heavier pigs.…”
Section: Resultssupporting
confidence: 59%
“…Once pigs have reached homeostasis and energy is no longer required for skeletal and muscle growth, it is theorized that fat is first deposited in the form of subcutaneous fat, followed by intermuscular fat, and then intramuscular fat ( De Smet et al, 2004 ). Therefore, genetics companies have shifted their efforts to pigs with a greater mature size and an increasing number of pork processors have begun to focus on the greater slaughter weight, which in turn yields a leaner product while maintaining an acceptable level of fat ( Strzelecki et al, 1998 ; Price et al, 2019 ).…”
Section: Resultsmentioning
confidence: 99%
“…Several recent studies and market assessments have indicated that the weight of pork carcasses is expected to increase in upcoming years ( Morin et al, 2015 ; Harsh et al, 2017 ; Rice et al, 2018 ; Gilleland et al, 2019 ; Price et al, 2019 ). Harsh et al (2017) goes as far as to state predictions for carcass weights in the future, which were stated as 104 kg in 2030, 111 kg in 2040, and 118 kg in 2050.…”
Section: Resultsmentioning
confidence: 99%
“…Thus, fat depth, muscle depth, and predicted leanness are often the only carcass leanness parameters evaluated in commercial pigs. Several research studies have characterized the correlation between pork carcass weight and leanness parameters ( Kure, 1997 ; Ohlmann and Jones, 2011 ; Plà-aragonés et al, 2013 ; Rodríguez et al, 2014 ; Price et al, 2019 ). However, there still exist many misunderstandings among the relationship of pork carcass weight and leanness parameters, particularly in commercially representative pigs marketed under current times and conditions.…”
This study aimed to examine the correlation of carcass weight, fat depth, muscle depth, and predicted lean yield in commercial pigs. Data were collected on 850,819 pork carcasses from the same pork processing facility between October 2017 and September 2018. Hot carcass weight was reported following slaughter as a head-on weight; while fat and muscle depth were measured with a Destron PG-100 probe and used for the calculation of predicted lean yield based on the Canadian Lean Yield (CLY) equation [CLY (%) = 68.1863 − (0.7833 × fat depth) + (0.0689 × muscle depth) + (0.0080 × fat depth2) − (0.0002 × muscle depth2) + (0.0006 × fat depth × muscle depth)]. Descriptive statistics, regression equations including coefficients of determination, and Pearson product moment correlation coefficients (when assumptions for linearity were met) and Spearman’s rank-order correlation coefficients (when assumptions for linearity were not met) were calculated for attributes using SigmaPlot, version 11 (Systat Software, Inc., San Jose, CA). Weak positive correlation was observed between hot carcass weight and fat depth (r = 0.289; P < 0.0001), and between hot carcass weight and muscle depth (r = 0.176; P < 0.0001). Weak negative correlations were observed between hot carcass weight and predicted lean yield (r = −0.235; P < 0.0001), and between fat depth and muscle depth (r = −0.148; P < 0.0001). Upon investigation of relationships between fat depth and predicted lean yield, and between muscle depth and predicted lean yield using scatter plots, it was determined that these relationships were not linear and therefore the assumptions of Pearson product moment correlation were not met. Thus, these relationships were expressed as nonlinear functions and Spearman’s rank-order correlation coefficients were used. A strong negative correlation was observed between fat depth and predicted lean yield (r = −0.960; P < 0.0001), and a moderate positive correlation was observed between muscle depth and predicted lean yield (r = 0.406; P < 0.0001). Results from this dataset revealed that hot carcass weight was generally weakly correlated (r < |0.35|) with fat depth, muscle depth, and predicted lean yield. Therefore, it was concluded that there were no consistent weight thresholds where pigs were fatter or heavier muscled.
“…This increase is driven by both the dilution of fixed production cost over more weight per pig and the improvement of genetic selection of lean-type pigs [ 4 ]. Several studies evaluated the effects of greater slaughter weights on profitability, carcass quality, primal cuts yield, and pork quality (e.g., [ 5 , 6 , 7 , 8 , 9 , 10 ]); however, only in a few studies the slaughter weight considerably exceeded 125 kg [ 5 , 10 ]. This framework results in a pronounced lack of knowledge concerning the quality of the fresh meat of heavy pigs, and in particular on how pork quality of this productive category may be affected by pre-slaughter stressors under conventional conditions.…”
This study focused on loin quality in Italian heavy pigs intended for the production of PDOs (Protected Designation of Origin) products, and investigated the pre-slaughter factors which negatively affect the quality of fresh meat. Data were collected on 44 shipments (loads) of pigs. Shipments were carried out under commercial conditions. Several pre-slaughter parameters were recorded within the entire process (on-farm, during transport, and at the slaughterhouse). On a subset of pigs (10 animals from every load, N = 440), serum cortisol and creatine kinase were measured and loin samples were analyzed for pH, instrumental color, drip loss, cooking loss, shear force, and sensory quality. Cluster analysis of the instrumentally-assessed meat quality parameters allowed the categorization of the shipments into two clusters: lower quality (LQ) and higher quality (HQ). Our results showed that the factors with significant differences between the two clusters were journey duration, ambient temperature, distance traveled, and irregular behaviors (slipping, falling, and overlapping) at unloading (all greater in LQ, p < 0.05). The pre-slaughter conditions associated with lower loin quality were ambient temperatures above 22 °C, distance traveled above 26 km, travel duration between 38–66 min, more than 5.9% of animals showing irregular behaviors at unloading.
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