Evaluation of alternative techniques to determine pork carcass value

The impact of feeding diets of high or low energy concentration on carcass measurements and the weight of primal and subprimal lean cuts

Pigs from four sire lines were allocated to a series of low energy (LE, 3.15 to 3.21 Mcal ME/kg) corn-soybean meal-based diets with 16% wheat midds or high energy diets (HE, 3.41 to 3.45 Mcal ME/kg) with 4.5 to 4.95% choice white grease. All diets contained 6% DDGS. The HE and LE diets of each of the four phases were formulated to have equal lysine:Mcal ME ratios. Barrows (N = 2,178) and gilts (N = 2,274) were fed either high energy (HE) or low energy (LE) diets from 27 kg BW to target BWs of 118, 127, 131.5 and 140.6 kg. Carcass primal and subprimal cut weights were collected. The cut weights and carcass measurements were fitted to allometric functions (Y = A CW(B)) of carcass weight. The significance of diet, sex or sire line with A and B was evaluated by linearizing the equations by log to log transformation. The effect of diet on A and B did not interact with sex or sire line. Thus, the final model was (B)) where Diet = -0.5 for the LE and 0.5 for HE diets and A and B are sire line-sex specific parameters. cut weight = (1+bD(Diet)) A(CW Diet had no affect on loin, Boston butt, picnic, baby back rib, or sparerib weights (p>0.10, bD = -0.003, -0.0029, 0.0002, 0.0047, -0.0025, respectively). Diet affected ham weight (bD = -0.0046, p = 0.01), belly weight (bD = 0.0188, p = 0.001) three-muscle ham weight (bD = -0.014, p = 0.001), boneless loin weight (bD = -0.010, p = 0.001), tenderloin weight (bD = -0.023, p = 0.001), sirloin weight (bD = -0.009, p = 0.034), and fat-free lean mass (bD = -0.0145, p = 0.001). Overall, feeding the LE diets had little impact on primal cut weight except to decrease belly weight. Feeding LE diets increased the weight of lean trimmed cuts by 1 to 2 percent at the same carcass weight.

Temporal growth and development of body tissues of pigs as assessed by X-ray computed tomography

Data from 54 hybrid (mainly Large White × Landrace) pigs, comprising 18 male, 18 female and 18 castrated pigs, were used to quantify and mathematically describe the temporal growth and development of body tissues of live pigs. The pigs were 31.1 ± 3.6 kg liveweight (LW) and 70 ± 1 day of age (mean ± s.d.) at the start of the study, were individually penned, fed ad libitum and were weighed weekly. Computed tomography (CT) imaging was used to determine the weights of lean, fat and bone tissues of each pig at five different times during the study, which corresponded to ~30, 60, 90, 120 and 150 kg LW. The highest age and LW achieved by a pig were 31.4 weeks and 166.6 kg, respectively. A nonlinear mixed effects model of Gompertz function with sigmoidal behaviour was fitted to the data for each of the three sexes (male, female and castrate) to study the temporal growth and development of CT LW and the body tissues (lean, fat and bone). The estimate for CT LW at maturity was 237.5, 198.6 and 210.1 kg for males, females and castrates, respectively, and the corresponding prediction for the point of inflection (maximum growth rate) was 87.4, 73.1 and 77.3 kg. The predicted point of inflection for lean tissue was 47.0, 37.5 and 34.3 kg for males, females and castrates, respectively. In general, male pigs were the leanest, and castrates were the fattest, with females in between. Within sex, the ages at the point of inflection for lean tissue and bone tissue were lower than those for CT LW, whereas those for fat tissue were higher than those for CT LW. The percentage of bone tissue in the body generally remained stable with age (e.g. castrates had 9.2 and 9.0% at 14 and 26 weeks of age, respectively), whereas the percentage of lean tissue decreased with age (e.g. castrates had 61.3 and 50.4% at 14 and 26 weeks of age, respectively), and that of fat tissue increased with age (e.g. castrates had 16.8 and 25.8% at 14 and 26 weeks of age, respectively). Accurate mathematical models are required to develop management strategies to optimise pig production. The results of this study indicate that serial data on live pigs generated by CT imaging technology can be used to describe temporal growth and development of LW and body tissues of pigs using sigmoidal growth functions.

Measures of growth and feed efficiency and their relationships with body composition and carcass traits of growing pigs

Data from 53 hybrid (mainly Large White × Landrace) pigs, comprising 18 males, 18 females and 17 castrates, were used to examine the relationships among growth and feed efficiency traits measured in the growing animal, and their relationships with body composition and carcass traits at two target liveweight (90 and 120 kg) endpoints. The data were from individually penned pigs involved in a longitudinal experiment that started when the pigs were 32.4 ± 3.2 kg liveweight and 70 ± 1 days of age (mean ± s.d.). Weekly feed intake and liveweight, and body components data measured at 60, 90 and 120 kg by computed tomography scanning were used. Growth traits studied were: start of test liveweight, average daily gain (ADG), Kleiber ratio and relative growth rate. The feed efficiency traits were daily feed intake (DFI), feed conversion ratio (FCR) and residual feed intake. Body components and carcass traits were the weight of the body components (lean, fat, bone and skin tissues) and their percentages relative to liveweight. Three models were used for residual feed intake. The standard model (RFIstd) had metabolic weight and ADG as explanatory variables for feed intake, RFIadg had only ADG as explanatory variable, and the other (RFIfat) had percentage fat at 60 kg target liveweight included in the standard model. The RFIadg model resulted in R2 values of 36.9, 72.1 and 19.1% for males, females and castrates, respectively. The corresponding R2 values for the RFIstd model were 63.7, 72.1 and 37.1%, and those for the RFIfat model were 86.1, 80.0 and 71.9%. These results indicate that RFIfat may be a better trait to use for efficiency of feed utilisation, especially in castrates. There were significant interrelationships among growth traits (r = –0.46 to 0.98), and also among feed efficiency traits (r = 0.44 to 0.76). Of the feed efficiency traits studied, only FCR was significantly correlated with all the growth traits (r = 0.33 to –0.61), and DFI was correlated with start liveweight (r = 0.43) and ADG (r = 0.57). Growth traits per se were not correlated with body composition and carcass traits at each of the weight-constant target endpoints; however, feed intake was. High DFI was associated with high percentage fat (r = 0.39 to 0.49) and low percentage lean (r = –0.40 to –0.52) at both 90 and 120 kg target liveweights. As with DFI, high FCR, RFIadg and RFIstd were associated with high percentage fat and low percentage lean at both 90 and 120 kg target liveweights. There were no significant correlations between RFIfat and the body components and carcass traits. These results will enable the development of programs aimed at reducing feed costs and improving the economic value of the pig carcass.

Developments of carcass cuts, organs, body tissues and chemical body composition during growth of pigs

A serial slaughter trial was carried out to examine the developmental change of physical and chemical body composition in pigs highly selected for lean content. A total of 48 pigs (17 females and 31 castrated males) were serially slaughtered and chemically analysed. Eight pigs were slaughtered at 20, 30, 60, 90, 120 and 140 kg live weight, (LW) respectively. The carcass was chilled and the left carcass side was dissected into the primal carcass cuts ham, loin, shoulder, belly and neck. Each primal carcass cut was further dissected into lean tissue, bones and rind. Additionally, the physical and chemical body composition was obtained for the total empty body as well as for the three fractions soft tissue, bones and viscera. Viscera included the organs, blood, empty intestinal tract and leaf fat. The relationship between physical or chemical body composition and empty body weight (EBWT) at slaughter was assessed using allometric equations (log10y=log10a+blog10EBWT). Dressing percentage increased from 69·4 to 85·2% at 20 to 120 kg and then decreased to 83·1% at 140 kg LW, whereas percentage of soft tissue, bones and viscera changed from 23·5 to 33·0%, 10·1 to 6·3% and 14·7 to 10·3%, respectively, during the entire growth period. Substantial changes in proportional weights of carcass cuts on the left carcass side were obtained for loin (10·5 to 17·5%) and belly (11·3 to 13·8%) during growth from 20 to 140 kg. Soft tissue fraction showed an allometric coefficient above 1 (b=1·14) reflecting higher growth rate in relation to the total empty body. The coefficients for the fractions bones and viscera were substantially below 1 with b=0·77 and 0·79, respectively, indicating substantial lower growth relative to growth of the total empty body. Lean tissue allometric growth rate of different primal cuts ranged fromb=1·02 (neck) to 1·28 (belly), whereas rates of components associated with fat tissue growth rate ranged fromb=0·62 (rind of belly) to 1·79 (backfat). For organs, allometric growth rate ranged fromb=0·61 (liver) to 0·90 (spleen). For the entire empty body, allometric accretion rate was 1·01, 1·75, 1·02 and 0·85 for protein, lipid, ash and water, respectively. Extreme increase in lipid deposition was obtained during growth from 120 to 140 kg growth. This was strongly associated with an increase in backfat and leaf fat in this period. Interestingly, breeds selected for high leanness such as Piétrain sired progeny showed an extreme increase in lipid accretion at a range of LW from 120 to 140 kg, which indicates that selection has only postponed the lipid deposition to an higher weight compared with the normally used final weight of 100 kg on the performance test. The estimates obtained for allometric growth rates of primal carcass cuts, body tissue and chemical body composition can be used to predict changes in weight of carcass cuts, determine selection goals concerning lean tissue growth, food intake capacity, etc. and generally as input parameters for pig growth models that can be used to improve the efficiency of the entire pig production system for pigs highly selected for lean content.

Allometric association betweenin vivoestimation of body composition during growth using deuterium dilution technique and chemical analysis of serial slaughtered pigs

The objective of this study was to develop accurate mathematical-statistical functions to estimate body composition of live pigs between 20 and 140 kg weight from total body water (TBWA) determined by the deuterium dilution technique. Chemical body compositions during the growth period are essential input parameters for biological pig growth models, which are used to estimated the nutrient requirements, improve the entire production system, determine optimal slaughter weight, optimize selection for food intake, etc. In the present study, 48 pigs (17 female and 31 castrated males) were used in an experimental station to obtain protein, lipid, ash and water content at 20, 30, 60, 90, 120 and 140 kg live weight. At each target weight, body water of the animals was determined by the deuterium dilution technique. Eight pigs of each live-weight group were slaughtered and chemically analysed. Water content of the empty body decreased from 74 to 53%, whereas lipid content rose from 7 to 30%. Between 20 and 30 kg body weight, protein content increased from 16 to 17% and thereafter decreased to 16%. Ash content was constant at 3%. To estimate body composition of the remaining animals from TBWA (%) determined by deuterium dilution technique, two sets of exponential prediction functions were used to describe the relationship between chemically analysed body components and TBWA (%). The first set of prediction functions fitted one intercept for the entire growth period and the second set of prediction functions fitted a different intercept for each weight class. Correlation coefficients between estimated and chemically determined empty body water, lipid, protein and ash for the first set of functions were 0·93, 0·86, 0·83 and 0·65, respectively. The second set of prediction functions showed higher accuracy (2 to 10%), but had the disadvantage of non-continuous estimates over the entire growth period. In contrast, by using the first set of prediction functions, a continuous accurate estimation of body composition of live pigs was obtained over a large range of growth (20 to 140 kg) based on deuterium dilution space.

Ractopamine treatment biases in the prediction of pork carcass composition

Carcass and live measurements of 45 barrows were used to evaluate the magnitude of ractopamine (RAC) treatment prediction biases for measures of carcass composition. Barrows (body weight = 69.6 kg) were allotted by weight to three dietary treatments and fed to an average body weight of 114 kg. Treatments were: 1) 16% crude protein, 0.82% lysine control diet (CON); 2) control diet + 20 ppm RAC (RAC16); 3) a phase feeding sequence with 20 ppm RAC (RAC-P) consisting of 18% crude protein (1.08% lysine) during wk 1 and 4, 20% crude protein (1.22% lysine) during wk 2 and 3, 16% crude protein (0.94% lysine) during wk 6, and 16% crude protein (0.82% lysine) during wk 6. The four lean cuts from the right side of the carcasses (n = 15/treatment) were dissected into lean and fat tissue. The other cut soft tissue was collected from the jowl, ribs, and belly. Proximate analyses were completed on these three tissue pools and a sample of fat tissue from the other cut soft tissue. Prediction equations were developed for each of five measures of carcass composition: fat-free lean, lipid-free soft tissue, dissected lean in the four lean cuts, total carcass fat tissue, and soft-tissue lipid mass. Ractopamine treatment biases were found for equations in which midline backfat, ribbed carcass, and live ultrasonic measures were used as single technology sets of measurements. Prediction equations from live or carcass measurements underpredicted the lean mass of the RAC-P pigs and underpredicted the lean mass of the CON pigs. Only 20 to 50% of the true difference in fat-free lean mass or lipid-free soft-tissue mass between the control pigs and pigs fed RAC was predicted from equations including standard carcass measurements. The soft-tissue lipid and total carcass fat mass of RAC-P pigs was overpredicted from the carcass and live ultrasound measurements. Prediction equations including standard carcass measurements with dissected ham lean alone or with dissected loin lean reduced the residual standard deviation and magnitude of biases for the three measures of carcass leanmass. Prediction equations including the percentage of lipid of the other cut soft tissue improved residual standard deviation and reduced the magnitude of biases for total carcass fat mass and soft-tissue lipid. Prediction equations for easily obtained carcass or live ultrasound measures will only partially predict the true effect of RAC to increase carcass leanness. Accurate prediction of the carcass composition of RAC-fed pigs requires some partial dissection, chemical analysis, or alternative technologies.

Objectives and strategies in pig improvement: an applied perspective

Largely because of the influence of Charles Smith, simple performance testing of pigs over the previous 30 yr has been highly successful. With larger production units, current genetic objectives can be divided into two components: 1) to raise genetic potential for production traits and 2) to maximize the probability that this potential can be realized in practice. Faster improvement through increased accuracy and a more flexible nucleus structure are offered by BLUP methodology. Electronic measures of feed intake permit selection based on feeding behavior and the shape of the feed intake curve. After the elimination of the halothane gene, the next limiting factor for meat quality could be intramuscular fat. With more than 1500 mapped genes, the main constraints on marker-assisted selection are the high costs of DNA testing and the relatively small effects of this selection on performance. A combination of the possible effects of BLUP, the Meishan breed, and the ESR gene could give genetic improvements totaling 4 liveborn piglets per litter over the next 10 yr. There appear to be no limits on future improvement of lean growth, but risks are adverse changes in reproduction and disease resistance. Existing quantitative methods of improvement are very cost effective. The greatest challenge for molecular technologies may be the genetics of the immune system.