Search

A total of 736 pigs was used in a study with a 2 x 2 x 2 factorial arrangement to investigate the effects of and interactions between sire line (Line A vs. B), floor space (unrestricted vs. restricted), and gender (barrow vs. gilt) on growth performance, BW, and protein and estimated lipid accretion curves from 40 to 120 kg of BW. Pigs were by eight Line-A and nine Line-B sires mated with PIC C22 dams. Line A was of Pietrain ancestry and Line B was a synthetic line. The unrestricted floor space treatment consisted of small groups (four pigs) with 0.93 m2/pig of floor space for the entire grow-finish period. Pigs in the restricted floor space were in larger groups (12 pigs) with 0.37 and 0.56 m2/pig of floor space for the grower and finisher phases, respectively. Pigs were given ad libitum access to a three-phase dietary program, and one and three nipple waterers were available in the groups of 4 and 12 pigs, respectively. No sire line x floor space interactions were found for any of the traits measured. Line A pigs grew more slowly (50 g/d, P0.05), took longer (4.1 d, P0.05) to reach harvest weight (120.3 kg), and had similar feed intakes, but a lower gain:feed ratio (2.8%, P0.05) than Line B pigs. Line A pigs had greater longissimus muscle depth (P0.05) and estimated protein accretion rate (P0.05) than Line B pigs, but Line A and Line B pigs had a similar estimated percentage of lipid-free soft tissue. Pigs reared in the restricted floor space grew more slowly (105 g/d, P0.05) and consumed less feed (280 g/d, P0.05) but had a similar (P0.05) gain:feed ratio to pigs reared in the unrestricted floor space. Pigs reared in the unrestricted floor space had greater (P0.05) predicted protein and lipid accretion rates throughout the growth period than pigs reared in the restricted floor space. Differences between genders for growth traits and carcass measurements were in agreement with previous research. The differences in growth performance, carcass measures, and compositional growth curves between these two sire lines were similar in the two floor spaces.

The objectives of this study were to examine the effects of ractopamine (RAC) on the behavior and physiology of pigs during handling and transport. Twenty-four groups of three gilts were randomly assigned to one of two treatments 4 wk before slaughter: finishing feed plus RAC (10 ppm) or finishing feed alone. Pigs were housed in the same building in adjacent pens with fully slatted floors and ad libitum access to feed and water. Behavioral time budgets were determined in six pens per treatment over a single 24-h period during each week. Behavioral responses of these pigs to routine handling and weighing were determined at the start of the trial and at the end of each week. Heart-rate responses to unfamiliar human presence were measured in all pigs and blood samples were taken from a single pig in each pen on different days during wk 4. At the end of wk 4, all pigs were transported for 22 min to processing. Heart rate was recorded from at least one pig per pen during transport and a postmortem blood sample was taken from those pigs that were previously sampled. During wk 1 and 2, RAC pigs spent more time active (P0.05), more time alert (P0.05), and less time lying in lateral recumbency (P0.05). They also spent more time at the feeder in wk 1 (P0.05). At the start of the trial, there were no differences in behavioral responses to handling. However, over each of the next 4 wk, fewer RAC pigs exited the home pen voluntarily, they took longer to remove from the home pen, longer to handle into the weighing scale and needed more pats, slaps, and pushes from the handler to enter the scales. At the end of wk 4, RAC pigs had higher heart rates in the presence of an unfamiliar human (P0.05) and during transport (P0.05), but not during loading and unloading. Also at the end of wk 4, RAC pigs had higher circulating catecholamine concentrations (P0.05) than control pigs. Circulating cortisol concentrations and cortisol responses to transport did not differ between treatments. The results show that ractopamine affected behavior, heart rate, and catecholamine profile of finishing pigs and made them more difficult to handle and potentially more susceptible to handling and transport stress.

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.

An experiment was conducted to evaluate the use of two real-time ultrasound data-collection methods to develop a dynamic assessment of live weight growth, protein and lipid accretions, and lysine requirement curves on two commercial swine operations. For the first method, pigs (40 barrows and 40 gilts) were weighed (ranging from 18 to 121 kg) and scanned ultrasonically to collect backfat depth and longissimus muscle area measurements every 3 wk in the finishing facility on two farms (serial method). For the second method, pigs (200 gilts and 200 barrows) of similar corresponding ages on the same two farms were weighed and scanned on 1 d (mass scan) at three different times (February, April, and May). Thirty-two pigs/sex were measured at approximately the same ages as with the serial scans. Pigs on farm 1 grew faster and had smaller backfat depths and larger longissimus muscle areas (P0.01) than those on farm 2, irrespective of method. These measurements were used to predict empty-body protein and lipid contents using nonlinear functions, which then were converted to accretion rates and lysine requirements at each BW. Protein accretion (g/d) and daily lysine requirements increased and then decreased for each sex on each farm and were higher on farm 1 than on farm 2. Data from the individual mass scans had larger standard errors for modeled live weight growth than data from the serial scans. Combining data from the three mass scans yielded growth curves with standard errors similar to those for the curves from the serial scans. For the protein accretion curves, the standard errors of the combined mass scans were approximately 20% lower than the standard errors of the serial scans. The standard errors for the modeled lysine:calorie ratio requirement from the serial scans were approximately 1% of the requirement at each BW. These results indicated that either the serial or mass scan data-collection method is a practical means of determining on-farm growth and daily protein and lipid accretion rates, which can be used to determine the farm-specific lysine requirements of growing-finishing pigs.

Two experiments were conducted to evaluate the effect of betaine supplementation of finishing diets on growth performance and carcass characteristics of swine. Experiment 1 included 288 pigs in a 2 x 2 x 3 factorial arrangement of treatments consisting of barrows and gilts of two genetic populations fed diets with 1.25 g/kg supplemental betaine from either 83 or 104 kg to 116 kg and control pigs fed betaine-devoid diets. Pigs were housed three pigs per pen with eight replicate pens per treatment. Diets were corn-soybean meal-based with 300 ppm added choline. Genetic populations differed (P < 0.05) in fat depth (2.24 vs 2.93 cm) and longissimus muscle depth (53.8 vs 49.1 mm) at 116 kg. Betaine reduced feed intake (P < 0.05); however, real-time ultrasound measurements were not affected. In Exp. 2, 400 pigs were used in a 2 x 2 x 2 factorial arrangement of treatments to evaluate the effect of sex (barrow or gilts), betaine (0 or 1 g/kg of diet), and crude protein (CP) (0.70% lysine = 12.7% CP or 0.85% lysine = 15.0% CP) when fed from 60 to 110 kg live weight. Pigs had been assigned to either a high- or low-protein feeding regimen at an average initial weight of 11.3 kg and were maintained on their respective protein levels throughout the experiment. For a 56-d period from 61.7 kg to 113.6 kg, pigs were fed diets with 300 ppm added choline. Within each protein level, pigs were randomly assigned to diets containing 0 or 1 g/kg betaine. Pigs were group-housed (four to five pigs per pen). Pig weight and feed intake were recorded every 28 d. Real-time ultrasound measurements were recorded initially and at d 28 on 64 pigs, and on all pigs prior to slaughter. Growth rate was fastest and feed intake greatest for barrows (P < 0.05) and for pigs receiving 12.7% crude protein. A crude protein x betaine interaction (P < 0.05) was observed from d 28 to 56 with pigs fed the 15% CP diet growing fastest when supplemented with 1 g/kg betaine, and pigs receiving the 12.7% CP diet growing fastest when the diets contained 0 g/kg betaine. Gilts more efficiently (P < 0.05) converted feed into body weight gain, as did pigs receiving the 12.7% CP diet (P < 0.05). Longissimus muscle area and fat measurements were unaffected by betaine or dietary protein on d 28. However, by d 56 betaine reduced average fat depth in barrows (P < 0.05; 3.21 vs 3.40 cm), but not in gilts. Betaine may be more effective at altering body composition in barrows than in gilts.

A study of the effects of conjugated linoleic acid (CLA) on the belly firmness and fatty acid composition of genetically lean pigs was conducted. From 75 to 120 kg live weight, 30 gilts were allowed ad libitum access to a corn-soybean meal diet supplemented with either 1% CLA oil (CLA-60) or 1% sunflower oil (SFO) or were fed the sunflower oil-supplemented diet restricted to the amount consumed by pigs fed the CLA-60 diet (RSFO). Conjugated linoleic acid oil consists of 60% positional and geometric isomers of CLA. Pigs fed SFO exhibited higher average daily gains (0.98 vs 0.80 kg/d, P0.01) than RSFO-fed pigs, but there were no effects of dietary treatment on feed intake or feed efficiency. Dietary treatment did not affect (P0.05) backfat thickness or longissimus muscle area. Bellies of gilts fed CLA-60 were subjectively evaluated to be firmer (2.91 vs 2.43 or 2.07 +/- 0.13, P0.01) than those of SFO- or RSFO-fed gilts, respectively. The longissimus muscle of gilts fed CLA-60 contained more saturated fatty acids (39.77 vs. 36.04 or 36.73 +/- 0.74%, P0.001) and less unsaturated fatty acids (60.23 vs 63.96 or 63.27 +/- 0.74%, P0.001) than that of gilts fed SFO or RSFO, respectively. The belly fat of gilts fed CLA-60 contained more saturated fatty acids (44.45 vs. 37.50 or 36.60 +/- 0.46%, P0.001) and less unsaturated fatty acids (54.78 vs. 61.75 or 62.47 +/- 0.46%, P0.001), resulting in lower iodine values (57.69 vs 66.37 or 65.62 +/- 0.91, P0.001) than that of gilts fed SFO or RSFO, respectively. Gilts fed CLA-60 accumulated more CLA in the longissimus muscle (0.55 vs 0.09 or 0.09 +/- 0.03%, P0.01) and belly fat (1.56 vs. 0.13 or 0.13 +/- 0.15%, P0.001) than did gilts fed SFO or RSFO, respectively. Dietary treatment did not affect (P0.05) 24-h pH, drip loss or subjective quality evaluations of the longissimus muscle. The effect of supplemental CLA to improve belly firmness is of practical significance and may provide a nutritional solution to carcass fat and belly firmness problems, thereby enhancing the overall value of extremely lean carcasses.

Carcass and live measurements of 203 pigs representing seven genetic populations and four target live weights (100, 114, 128, and 152 kg) were used to evaluate alternative measures of carcass composition. Measures of carcass lean (fat tissue-free lean, FFLM; lipid-free soft tissue, LFSTIS; and dissected lean in the four lean cuts, DL), fat (total carcass fat tissue, TOFAT), and lipid mass (soft tissue lipid, STLIP) were evaluated. Overall, LFSTIS was 22.8% greater than FFLM (47.8 vs 38.9 kg) and TOFAT was 30% greater than STLIP (38.5 vs 29.6 kg). The allometric growth coefficients relative to carcass weight were different for the measures: b = 0.776, 0.828, 0.794, 1.37, and 1.49 for FFLM, LFSTIS, DL, TOFAT, and STLIP, respectively. At 90 kg carcass weight, the predicted growth of FFLM, LFSTIS, TOFAT, and STLIP was 0.314, 0.420, 0.553, and 0.446 kg/kg increase in carcass weight. The difference between FFLM and LFSTIS, representing nonlipid components of the carcass fat tissue, was greater for barrows than for gilts (9.2 vs 8.6 kg). Lipid-free soft tissue mass was predicted more accurately from carcass or live animal measurements than FFLM with smaller relative RSD (4.6 vs 6.5% of their mean values). The alternative measures of carcass composition were evaluated as predictors of empty body protein (MTPRO) and lipid (MTLIP) mass. Empty body protein was predicted with similar accuracy (R 2 = 0.74 to 0.81) from either DL, FFLM, LFSTIS, or ribbed carcass measurements. Empty body lipid was predicted more accurately from TOFAT (R 2 = 0.92) or STLIP (R 2 = 0.93) than ribbed carcass measurements (R 2 = 0.88). Although the alternative measures of lean mass (LFSTIS vs FFLM) and lipid mass (TOFAT vs STLIP) were highly related to each other (r = 0.93 to 0.98), they had different relative growth rates (allometric coefficients) and thus cannot be predicted as linear functions of the similar alternative variable without significant weight group biases. From the 100- to 152-kg target weight groups, gilts gained 12.9% greater FFLM and 12.1% greater MTPRO but only 4.4% greater LFSTIS than barrows. Fat-free lean mass is more precise as a measure of muscle growth and as a predictor of lysine requirements. Lipid-free soft tissue can be obtained more quickly and predicted more accurately from carcass or live animal measurements.

The objective of this study was to determine the impact of myosin heavy chain (MyHC) isoforms (I, IIB, IIA and IIX) on pork quality traits of halothane (HAL)-negative (NN) and halothane-carrier (Nn) pigs. Gilts (n=32) were assigned to a 2×2 factorial of genetic population (GP) and slaughter weight (WT; 120 and 135 kg). Classical meat quality characteristics were collected and MyHC content was determined on muscle samples. Regression equations for pork quality and carcass composition traits were determined. Only I/IIB accounted for variation in drip loss of NN gilts (R(2)=0.18), while GP related to drip loss in Nn gilts (R(2)=0.70). Type I MyHC content explained variation in ultimate (24 h) muscle pH of NN gilts (R(2)=0.09), while I/IIB, I/IIX and IIB/IIX were significant for Nn gilts (R(2)=0.99). I/IIA, I/IIX, IIB/IIX and GP accounted for variation in Hunter Color a (redness) values of NN gilts (R(2)=0.69), while IIB, IIA, IIB/IIA and GP were significant for Nn gilts (R(2)=0.97). Overall, fiber type composition accounts for a larger proportion of variation in the quality traits of Nn compared to NN gilts.

Several transcription factors are involved in regulating lipid metabolism in various tissues of animals. Adipocyte determination and differentiation-dependent factor 1 (ADD1), peroxisome proliferator activated receptor alpha (PPAR alpha), and peroxisome proliferator activated receptor gamma (PPAR gamma) regulate both lipogenesis and fatty acid oxidation. We determined the tissue distribution and genetic difference in mRNA concentrations of these transcription factors in two genetic populations of pigs (Newsham XL-sired Newsham Landrace x Large White Duroc and Duroc-sired US Yorkshire x Duroc-Landrace). We also determined the tissue distribution and genetic difference in the mRNA concentration of fatty acid synthase (FAS) and acyl-CoA oxidase (ACO). Our data showed that ADD1 was highly expressed in adipose tissue and liver and that mRNA concentrations of ADD1 were similar between the two genotypes. The PPAR alpha mRNA concentration was high in adipose tissue and was similar between the two genotypes. In both populations, PPAR gamma mRNA was detected only in adipose tissue. There was no difference between the two genotypes in PPAR gamma mRNA concentration. The ACO mRNA was expressed in adipose tissue, skeletal muscle, and liver with no difference between genotypes. The FAS mRNA concentration in adipose tissue was seven times higher than that in the liver. There was no detectable FAS mRNA in skeletal muscle. These data support the concept that pig adipose tissue has considerable capability for fatty acid oxidation and synthesis. The uniqueness of expression patterns for FAS and ADD1 mRNA further indicates that adipose tissue is significantly involved in fatty acid and triacylglycerol synthesis in pigs.

Carcass and live measurements of 165 market hogs that represented seven genotypes were used to investigate genotype and sex biases associated with the prediction of fat-free lean mass (FFLM) and carcass value. Carcass value was determined as the sum of the product of weight of individual cuts and their average unit prices adjusted for slaughter and processing costs. Independent variables used in the prediction equations included carcass measurements, such as optical probe, midline ruler, ribbed carcass measurements, and electromagnetic scanning (EMSCAN), and live animal ultrasonic scanning. The effect of including subpopulation mean values of independent variables in the prediction equations for FFLM and carcass value was also investigated. Genotype and sex biases were found in equations in which midline backfat, ribbed carcass, EMSCAN, and live ultrasonic scanning were used as single technology sets of measurements. The prediction equations generally undervalued genotypes with above-average carcass value. Biases were reduced when measurements of combined technologies and mean adjusted variables were used. The FFLM and carcass value of gilts were underestimated, and they were overestimated of barrows. Equations that combined OP and EMSCAN technologies were the most accurate and least biased for both FFLM and carcass value. Equations that included carcass weight and midline last-rib backfat thickness measurements were the least accurate and most biased. Genotype and sex biases must be considered when predicting FFLM and carcass value.

Swine growth models have the potential to evaluate alternative management decisions and optimize production systems. However, the lack of economical, yet accurate methods to obtain the growth parameters required to characterize pig genotypes, and which are required by growth models, limits their widespread implementation. The four primary parameters required are 1) daily whole-body protein accretion potential, 2) partitioning of energy, intake over maintenance between protein and lipid accretion, 3) maintenance requirements for energy, and 4) daily feed intake. Estimation of daily protein accretion rates requires that serial estimates of composition and growth be fitted to flexible nonlinear functions. Serial dissection and chemical analysis are too expensive to be routinely conducted on an adequate number of pigs for precise daily protein accretion rates at different live weights. Three alternate methods include 1) serial slaughter and double sampling; 2) use of serial live measurements to estimate composition, i.e., serial ultrasonic measurements; and 3) use of generalized functions that estimate daily protein accretion as a function of mean daily fat-free lean gain over a specified weight interval. The energy partitioning between lipid and protein accretion can be expressed as two interchangeable measurements, either as the slope of protein accretion or the change in the lipid: protein gain ratio as a function of energy intake at each live weight. Both methods require serial estimates of composition and scale feeding of pigs to specified energy intake levels. Maintenance requirements for energy are better expressed as a function of protein mass than body weight. However, differences in body protein mass do not fully explain difference in maintenance requirements between various pig genotypes. Daily feed intakes at each live weight can be estimated by accurately collecting feed intake data at least three live weight ranges and fitting the data to nonlinear functions. An alternative method to estimate daily feed intake is to develop daily lipid and protein accretion curves. On the basis of their energetic costs of lipid and protein deposition and assumed maintenance requirements, daily energy intakes can be estimated. Genetic selection changes the underlying growth parameters. The selection criteria and testing environment direct the relative genetic change for each growth parameter. The different sexes may also be affected differently by selection. For this reason, each closed uniformly selected population must be evaluated for each parameter for each sex.

Dissected and predicted wholesale and lean boneless values for 154 pork carcasses representing seven genotypes with substantial variation in carcass composition and percentage of lean were determined. Dissected carcass value was determined using a component pricing model, and four alternative models were specified to predict that value. The models included measurements from a ruler (RULER) and two carcass evaluation technologies, Hennessy probe (PROBE) and electromagnetic scanner (EMS1). A combination of the PROBE and EMS1 models (EMS2) was also used. For wholesale value, R 2 were .40, .70, .59, and .74, and the RSD were 8.18, 5.77, 6.76, and 5.38 ($/100 kg of carcass value) for RULER, PROBE, EMS1, and EMS2, respectively. For lean boneless value, the R 2 were .41, .73, .59, and .74, and the RSD were 8.34, 5.67, 6.99, and 5.51 ($/100 kg of carcass value) for RULER, PROBE, EMS1, and EMS2, respectively. The results indicate that a combination of probe and electromagnetic scanner measurements provided the best fit to dissected value

This paper presents a method of estimating the lean and fat composition in pork ham from cross-sectional area measurements using image processing technology. The relationship between the quantity of ham lean and fat mass with the ham lean and fat areas was studied. The prediction equations for pork ham composition based on the ham cross-sectional area measurements were developed. The results show that ham lean weight was related to the ham lean area (r equals .75, P < .0001) while ham fat weight was related tot the ham fat area (r equals .79, P equals .0001). Ham lean weight was highly related to the product of ham total weight times percentage ham lean area (r equals .96, P < .0001). Ham fat weight was highly related to the product of ham total weight times percentage ham fat area (r equals .88, P < .0001). The best combination of independent variables for estimating ham lean weight was trimmed wholesale ham weight and percentage ham fat area with a coefficient of determination of 92%. The best combination of independent variables for estimating ham fat weight was trimmed wholesale ham weight and percentage ham fat area with a coefficient of determination of 78%. Prediction equations with either two or three independent variables did not significantly increase the accuracy of prediction. The results of this study indicate that the weight of ham lean and fat could be predicted from ham cross-sectional area measurements using image analysis in combination with wholesale ham weight.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

An experiment was conducted to determine the effect of ractopamine, energy intake, dietary fat level, and sex on performance and carcass composition in finishing pigs. Three hundred six barrows and gilts were used in a factorial arrangement of treatments replicated over three seasons. Treatments consisted of two ractopamine levels (0 vs 44.7 mg/d), two sexes (barrows and gilts), two levels of fat addition (0 vs 5% added fat), and four energy intake levels (8.3, 8.9, 9.5, and 10.1 Mcal of ME/d for barrows and 7.7, 8.3, 8.9, and 9.5 Mcal of ME/d for gilts). Diets were formulated to maintain an equal lysine (28.5 g/d) intake at each feeding level through cornstarch dilution of the basal (7.7 Mcal of ME/d) diets. Pigs were fed daily based on a standard feed intake curve and prior weekly body weights. At slaughter (104 kg), carcass measurements and TOBEC HA-1 scanner measurements were recorded. Dietary fat addition improved live weight and lean efficiency (grams of carcass lean gain/kilogram of feed, P.05). Dietary fat addition did not affect growth rate or carcass composition. Increasing energy intake resulted in a linear increase in average daily gain for both barrows and gilts (P.01). Dietary ractopamine influenced the response of lean tissue accretion, lean tissue accretion efficiency, and fat tissue accretion to energy intake. Pigs with no added ractopamine demonstrated increased lean tissue accretion and improved efficiency and decreased fat tissue accretion with increasing energy intake (up to 9.5 Mcal of ME intake for barrows and 8.9 Mcal of ME intake for gilts). In contrast, pigs with added ractopamine did not respond to increasing energy intake and demonstrated increased fat tissue accretion with increasing energy intake. The response to ractopamine for growth was greatest from d 6 to 22 on test or during the test gain period of 7 to 18 kg. After d 22, the response of ractopamine declined linearly. These results indicate that ractopamine increases growth rapidly at the onset of feeding until a plateau is reached, after which there is a linear decline in growth response.

Three hog genotypes are simulated to determine how producer profits, economically optimal slaughter weights, and carcass component weights change under three pricing modeIs, Live weight pricing pays more for the fatter barrows whereas a three component (separate payments for fat, lean, and byproducts) and six component (separate payments for major primal cuts, other lean, fat, and byproducts) pricing system pay more for the leaner gilts. Implications for selection of genetic stock and pricing system are presented. Crop farmers in most regions of the United States cannot grow crops in the winter months and must harvest when the crop is ready in the fall. Pork producers raising animals in confinement buildings are not constrained by seasonal weather, and thus, have completely flexible starting and ending production points. Consequently, in order to remain profitable, pork producers need to maintain full facilities, and the opportunity cost of facilities is an important determinant of economically optimal slaughter weights. As a result, it may be shown that producers market their hogs where marginal profit per unit of time is equal to average profit per unit of time (Dillon and Anderson). Equivalently, producers seek to maximize average profit per unit of time. Previous research on the optimal slaughter weight of livestock has focused on feeding strategies, These strategies have examined the price of feed and live weight market prices (Crabtree), the length of the feeding period (Kennedy et al.), and decision rules for determining optimal rations and optimal slaughter weight (Heady, Sonka, and Dahm). Feed prices and the cost of replacing the animal has been shown to be important in determining optimal slaughter weight (Chavas, Kliebenstein, and Crenshaw). Historically, pork producers have been paid using a live weight pricing system for hogs, Generally, the heavier the hog, the more revenue a producer received, although discounts were employed by packers to deduct for heavy hogs (which were often breeding stock) and light weight hogs. Consumer demand for leaner pork products has forced packers and producers to change their buying and selling strategies, respectively (Grisdale

An image processing algorithm was developed to measure ham cross-sectional areas to predicate ham composition. The fat, lean muscle and skin areas were measured from the cross section of wholesale trimmed hamsusing image processing techniques. The algorithm was first designed to enhance the ham image using a convolutionoperation, followed by a gray level normalization operation. Then, a binary image representing ham fat area was obtained after a segmentation operation. Finally the fat, lean muscle and skin areas were measured fromcorresponding binary images. The results indicate that fat and lean can be detected and measured using image processing techniques based on the difference of light reflectance of fat and lean in the visible wavelength of theelectromagnetic spectrum.1. INTRODUCTIONHam is an important product in the meat market. Currently, estimates of ham composition mainly rely on the human visual inspection based on the perception of the fat and lean muscle area at the ham cutting faces. Thisinspection method is inconsistent due to many factors, such as inspection environment, human bias and lack of

Carcasses of 181 barrows, representing five genotypes, 1) H x HD, 2) SYN, 3) HD x L[YD], 4) L x YD, and 5) Y x L (H = Hampshire, D = Duroc, SYN = synthetic terminal sire line, L = Landrace, and Y = Yorkshire), and two levels of ractopamine (RAC) treatment (0 and 20 ppm) were completely dissected and the data were used to examine genotype and treatment (RAC) biases in estimation of fat-standardized lean weight and to evaluate accuracies and precisions realized by use of equations based on variables derived from different technologies. Independent variables used to establish regression equations represented technologies of direct carcass measurements, optical probe data, TOBEC (total body electrical conductivity) readings, and dissected (DHMLN) and fat-standardized (FSHMLN) ham lean. Genotype bias existed when any equation from a single technology was used and was minimized by combining FSHMLN with one TOBEC reading, carcass length, and the probe measurement of 10th rib fat depth. Large RAC biases appeared when equations from direct carcass measurements or optical probe data were used and were minimized by an equation using either DHMLN or FSHMLN. A practical equation with relatively high R2 value and small genotype and RAC biases were developed by combining TOBEC readings with direct carcass measurements of 10th rib fat depth and warm carcass weight.

A replicated factorial experiment using 183 individually fed crossbred barrows was conducted. The pigs were fed an 18.5% CP (.95% lysine) diet with 3,594 kcal of mg. ?he effects of five genotypes (GT): 1) Hampshire (H) x (H x Duroc PI), 2) synthetic terminal sire line, 3) (H x D) x (Landrace b] x workshire (Y) x D]), 4) L x (Y x D), and 5) Y x L; two levels of ractopamine WC) treatment: 0 and 20 ppm; and three treatment weight periods 0: 1) 59 to 100,2) 73 to 114, and 3) 86 to 127 kg live weight on ADG of dissected lean (ADLG) and fat standardized lean adjusted to 10% fat content (ADSLG) and feed efficiency of ADLG (LFE) and ADSLG (SLFE) were evaluated. Initial carcass lean quantity of each individual animal was determined by a regression equation (R2 = .95) generated from 30 additional barrows (six per GT) slaughtered at 59 kg and 30 (six per GT) untreated pigs slaughtered at 100 kg average live weight. Logarithmic and reciprocal transformations of dependent variables were used to stabilize heterogeneous variances and to improve noFality of the residuals. Ractopamine increased (P c .OO01) ADLG, ADSLG, LFE, and SLFE, respectively, by 19.5, 25.0, 19.6, and 25.5%. Differences (P < .001) were observed among genotypes for all traits, showing that considerable variation existed in the data and indicating that genetic improvement can be realized through the identification and selection of superior genotypes. For ADLG and ADSLG, a RAC x GT interaction (P < .05) was observed, demonstrating greater responses to RAC in leaner genotypes. Pigs achieved greatest lean growth rate in the 73 to 114-kg period among the three. growth phases and likely reached a plateau in lean growth rate at 70 to 90 kg. Lean feed efficiency declined as BW increased. These results clearly indicate that greater benefits can be expected if pigs from leaner genotypes are treated with ractopamine and slaughtered at or before 114 kg live weight.

Eighty barrows were used in a 2 x 2 x 4 factorial experiment to examine the effects of genetic line (Hampshire x Yorkshire, H x Y, and Yorkshire x Landrace, Y x L), somatotropin (dose, 0 and 5 mg/d) and energy intake (ad libitum, 93%, 86% and 80%) on growth performance and energy requirements for lean gain over the finishing phase of growth. Four diets were formulated to maintain equal intakes of protein, vitamins and minerals at different energy intakes. Somatotropin increased growth rate 30 to 35% across diets despite an 8 to 12% reduction in ad libitum feed intake. Lean growth rate (kg/d) was increased preferentially by ST in the faster-growing H x Y barrows, which showed a 2.8-fold greater maximum rate increase than the slower-growing Y x L barrows. In control barrows, 10% reductions in energy intake had no effect on lean gain and improved feed/lean gain about 10%. In somatotropin-treated barrows, lean gain was reduced with each energy restriction in H x Y; energy intake had no effect on lean gain in Y x L barrows. Feed/lean gain was improved 22% in Y x L barrows at the lowest energy intake. Data indicate that somatotropin accentuates breed differences in lean gain and energy requirements. Pigs with low lean-growth potential will benefit from restricted feeding, whereas strategies to increase energy intake in pigs with high lean-growth potential may be desirable.

A. P. Schinckel and C. H. Kuei Three hundred sixty-one market-weight barrow and gilt carcasses were physically dissected into bone, skin, fat and muscle. A three-variable multiple linear regression equation containing the same independent variables (warm carcass weight, loth rib loin muscle area and loth rib fat depth) used (U.S.) to determine pork carcass lean weight was found to be the most practical means for predicting weight of muscle standardized to 10% fat. Multiple linear regression equations containing more than three independent variables produced only slight improvements in R2 values; however, the standard deviation about the regression line was not greatly improved by the addition of more independent variables to this threeindependent-variable regression model. A single multiple linear regression equation using the three independent variables above may not be adequate to describe variation over the entire live-weight range for all hogs marketed in the U. S. For most accurate muscle weight prediction, different equations should be used for weight subclasses with one equation for carcasses under 100 kg and another for those heavier than 100 kg. A single prediction equation for muscle weight was adequate for carcasses of both barrows and gilts. (Key Words: Pork, Carcass Composition, Muscle Weight.) J. Anim. Sci. 1990. 68:3987-3997

The objective of this research was to use recent ractopamine research data to develop an updated mathematical model to describe the daily compositional growth of pigs fed ractopamine. Mean increases of 18.2, 23.1, and 25.0% for daily protein accretion were assumed for 5, 10, and 20 ppm of ractopamine for an overall gain of 40 kg of BW gain during the feeding period. The relative effect of ractopamine described the rapid increase and subsequent decrease in the effect of ractopamine as a function of BW gain or days on test and ractopamine concentration (RC, ppm). The reduction in ME intake produced by ractopamine was described as 0.036 x (RC/20) 0.7 multiplied by the ME intake for the first 20 kg of BW gain, and then increasing to 0.078 x (RC/20) 0.7 at 40 kg of BW gain feeding period. The ratio of fat-free muscle gain to protein accretion increased by 14 to 16% with the feeding of ractopamine, depending on the dietary lysine/essential AA levels. The ratio of carcass fat gain to empty body lipid gain was increased when lysine and essential AA requirements were met. Daily protein accretion and fat-free lean growth were described as functions of dietary lysine/essential AA intakes. The percentage of lysine in protein accretion increased with the feeding of ractopamine from 6.80 to 7.15%, depending on ractopamine concentration. Equations predicting carcass measurements, such as fat and longissimus muscle depths from carcass weight and composition, were modified to incorporate prediction biases produced by ractopamine. For the four concentrations of ractopamine (0, 5, 10, and 20 ppm, respectively) during a 78 to 110 kg of BW feeding period, the model predicted performance levels for ADG (1.03, 1.15, 1.16, and 1.16 kg/d), gain:feed (kg of ADG/kg of ADFI; 0.360, 0.401, 0.412, and 0.425), dressing percentage (75.1, 76.0, 76.3, and 76.4), percentage fat-free lean (48.7, 51.0, 51.5, and 52.2), longissimus muscle area (38.8, 41.8, 42.5, and 43.5 cm 2 ), 10th-rib fat depth (22.1, 19.8, 19.3, and 18.7 mm), and fat-free lean gain (321, 446, 467, and 495 g/d), comparable to recent research data. The model allows the effect of ractopamine to be added to farm specific pig growth curves. It can be used to evaluate ways to optimize the use of ractopamine, including duration of ractopamine feeding, concentration of ractopamine, and dietary lysine concentration.

An experiment was conducted to determine the efficacy of dietary conjugated linoleic acid (CLA) as a growth promotant in weanling swine. Weanling pigs (n = 192; 7.6 kg and 29 d of age) were randomly assigned to four treatments that were arranged as a 2 x 2 factorial. Concentrations of dietary CLA (0 or 0.6%) and antibiotics (+/-) constituted the main effect variables. Dietary CLA treatments consisted of a 1% addition of an oil containing 60% CLA isomers or 1% soybean oil, and dietary antibiotic treatments were antibiotics or no antibiotics. The experimental diets were fed for 9 wk in four phases (1, wk 1; 2, wk 2 and 3; 3, wk 4 through 6; and 4, wk 7 through 9), after which all pigs were fed identical medicated diets for the duration of the finishing phase. Live weights were recorded at wk 17 postweaning and at marketing to determine any residual effects of dietary treatments on finisher ADG and days to market. Medicated diets fed during phases 1 and 2 contained 55 mg carbadox/kg; during phase 3 contained 299 mg tilmicosin/kg; and during phase 4 contained 110 mg tylosin and 110 mg sulfamethazine/ kg. Pigs fed medicated diets had higher overall ADG than pigs fed unmedicated diets for wk 0 through 9 (P < 0.03). Gain:feed (G:F) was greater for pigs fed medicated diets than for pigs fed unmedicated diets during phase 1 (P < 0.03) and for the duration of the nursery phase (P < 0.03). There were no effects of CLA on ADG, ADFI, or G:F. There were no residual effects of nursery CLA or antibiotics on finisher ADG and days to market. Blood samples collected from a subset of pigs (n = 72) at the completion of phases 2, 3, and 4 were assayed for serum IGF-I and antibody concentrations to porcine reproductive and respiratory syndrome virus (PRRS-V) and Mycoplasma hyopneumoniae. There was a tendency for pigs fed medicated diets to have greater IGF-I concentrations than pigs fed unmedicated diets at the completion of phase 4 (P < 0.06). Pigs fed CLA had greater antibody titers (P < 0.02) to Mycoplasma hyopneumoniae at d 63 than pigs fed diets without CLA. These results indicate that feeding 0.6% dietary CLA did not enhance growth performance in weanling swine and that the use of dietary antibiotics can increase production efficiency in nursery pigs. Furthermore, there were no interactions between CLA and dietary antibiotics on the variables addressed in this study.

This study was conducted to model the growth of carcass, viscera, and empty body components and component composition of pigs. Quantitative tissue and chemical composition of 319 swine, representative of barrows and gilts from five commercial genetic populations, was determined at eight stages of growth between 25 and 152 kg. After whole body grinding and carcass dissection, proximate analyses were performed to calculate concentrations of protein, lipid, moisture, and ash of carcass, viscera, empty body, carcass lean, and carcass fat. Linear and nonlinear equations were developed to investigate the growth patterns of each component. Nonlinear growth functions accounted for the greatest amount of variation in empty body protein, lipid, moisture, and ash mass. Differences (P < .05) existed between barrows and gilts for nearly all components investigated. Carcass lean and fat tissues significantly increased in lipid percentage and decreased in moisture percentage as live weight increased. There were significant changes in the ratio and composition of the tissues of barrows and gilts during growth. Nonlinear models fitted the data better than allometric equations for nearly all of the components investigated.

The objective of this study was to evaluate a method for predicting daily protein accretion rates of various genotypes of pigs reared in different environmental conditions using easily obtained mean daily fat-free growth rates. Data were obtained for seven genotype-environment groups of gilts and nine groups of barrows. Daily empty body protein accretion rates were estimated at 1.0-kg intervals between 20 and 120 kg live weight. The estimates were fitted to a generalized exponential function, PA = A e (B x WT + C/WT + D x WT2) , where WT is kilograms of live weight and A, B, C, and D are estimated parameters for each sex. Nonlinear least squares methods were used to estimate the intercept and regression coefficients expressing each parameter estimate (A, B, C, and D) as a linear function of the mean fat-free lean gain for each sex-genotype-environment group. The mean percentage absolute errors were 3.5% for gilts and 6.1% for barrows. The largest errors occurred between 110 and 120 kg live weight. From 20 to 110 kg, mean percentage errors averaged 2.7% for gilts vs 4.8% for barrows. These results offer encouraging evidence that a generalized equation can be used to predict daily protein accretion rates from mean fat-free lean growth data. Further research, with additional genotype-environment populations, is needed to increase accuracy of the generalized growth functions.