The effect of perch availability during pullet rearing and egg laying on the behavior of caged White Leghorn hens.

Enriched cages, compared with conventional cages, allow egg laying strains of chickens to meet some behavioral needs, including a high motivation to perch. The objective of this study was to determine if perch availability during rearing affected perch use as adults and if perch presence affected eating and drinking in caged White Leghorn hens. Chickens were assigned to 14 cages each with and without 2 round metal perches from hatch to 16.9 wk of age. At 17 wk of age, pullets were assigned to laying cages consisting of 1 of 4 treatments. Treatment 1 chickens never had access to perches (controls). Treatment 2 chickens only had access to 2 round metal perches during the laying phase (17 to 71 wk of age). Treatment 3 chickens only had access to 2 round perches during the pullet phase (0 to 16.9 wk of age). Treatment 4 chickens had access to the perches during both the pullet and laying phase. Each treatment during the adult phase consisted of 9 cages with 9 birds/cage for a total of 36 cages. Automatic infrared cameras were used to monitor behavior of hens in each cage for a 24-h period at 19, 24, 29, 34, 39, 44, 49, 54, 59, 64, and 69 wk of age. Behavior was also recorded twice weekly by an observer in the room where the hens were housed during photophase from 25 to 68 wk of age. Behavioral data were analyzed using ANOVA with repeated measures and the MIXED model procedure. A greater proportion of hens without perches as pullets used the rear perch more during both photophase and scotophase than hens with prior pullet perching experience. Eating and drinking activities of caged adult Leghorns were not impaired by their prior experience to perches as pullets or by the presence of perches in laying cages. It is concluded that providing perches in cages to White Leghorns during pullet rearing did not facilitate use of perches as adults.

The effect of perch availability during pullet rearing and egg laying on musculoskeletal health of caged White Leghorn hens.

A major skeletal problem of conventionally caged hens is increased susceptibility to osteoporosis mainly due to lack of exercise. Osteoporosis is characterized by a progressive decrease in mineralized structural bone. Whereas considerable attention has been given to enriching laying cages, little research has been conducted on providing caged pullets with furnishments, in particular perches. The objective of the current study was to determine if metal perches during all or part of the life cycle of White Leghorns affected hen musculoskeletal health, especially at end of lay. Treatments during the pullet phase (hatch to 16.9 wk) entailed cages with and without perches. Four treatments were used during the laying phase (17 to 71 wk of age). Treatment 1 chickens never had access to perches at any point during their life cycle, typical of egg industry practices in the United States for conventional cages. Treatment 2 chickens had access to perches only during the egg-laying phase, which was from 17 to 71 wk of age. Treatment 3 chickens had access to perches only during the pullet phase (0 to 16.9 wk of age). Treatment 4 chickens had perch access throughout their entire life cycle (0 to 71 wk of age). Musculoskeletal health was assessed by measuring muscle weights, bone mineralization, bone fracture incidence, and keel bone deviations. Muscle deposition of 71-wk-old hens increased when given access to perches as pullets. Bone mineralization of 71-wk-old hens also increased if given perch access as adults. However, the disadvantage of the adult perch was the higher incidence of keel deviations and keel fractures at end of lay. The increase in bone mineralization of the keel bone as a result of perch access during the pullet and laying phases was not great enough to prevent a higher incidence of keel bone fractures at end of lay. Perch redesign and placement of perches within the cage to minimize keel fractures and deviations are possible solutions.

The effect of perches in cages during pullet rearing and egg laying on hen performance, foot health, and plumage.

Enrichment of pullet cages with perches has not been studied. Our objective was to determine if access to metal perches during all or part of the life cycle of caged White Leghorns affected egg traits, foot health, and feather condition. Treatment 1 represented control chickens that never had access to perches during their life cycle. Treatment 2 hens had perches only during the egg laying phase of the life cycle (17 to 71 wk of age), whereas treatment 3 chickens had perches during the pullet phase (0 to 16.9 wk of age). Treatment 4 chickens always had access to perches (0 to 71 wk of age). Comparisons between chickens that always had perches with controls that never had perches showed similar performance relative to egg production, cracked eggs, egg weight, shell weight, % shell, and shell thickness. More dirty eggs occurred in laying cages with perches. Feed usage increased resulting in poorer feed efficiency in hens with perch exposure during the pullet phase with no effect during egg laying. Perches did not affect hyperkeratosis of toes and feet. The back claw at 71 wk of age broke less if hens had prior experience with perches during the pullet phase. In contrast, during egg laying, the back claw at 71 wk of age broke more due to the presence of perches in laying cages. Perches in laying cages resulted in shorter trimmed claws and improved back feather scores, but caused poorer breast and tail feather scores. In conclusion, enriching conventional cages with perches during the entire life cycle resulted in similar hen performance compared with controls. Fewer broken back claws but poorer feed efficiency occurred because of prior experience with perches as pullets. Perch presence during egg laying improved back feather scores with more trimmed nails but caused more dirty eggs, broken back claws, and poorer breast and tail feather scores. Although perches allow chickens to express their natural perching instinct, it was not without causing welfare problems.

Early access to perches in caged White Leghorn pullets.

Osteoporosis, a progressive decrease in mineralized structural bone, causes 20 to 35% of all mortalities in caged White Leghorn hens. Previous research has focused on manipulating the egg laying environment to improve skeletal health, with little research on the pullet. The objective of the current study was to determine the effect of perch access on pullet health, bone mineralization, muscle deposition, and stress in caged White Leghorns. From 0 to 17 wk of age, half of the birds were placed in cages with 2 round metal perches, while the other half did not have perches (controls). Bone mineralization and bone size traits were determined in the tibia, femur, sternum, humerus, ulna, radius, and phalange (III carpometacarpal) using dual energy x-ray absorptiometry. Muscle weights were obtained for the breast and left leg (drum and thigh). A sample of pullets from each cage was evaluated for foot health, BW, right adrenal weight, and packed cell volume. Most measurements were taken at 3, 6, and 12 wk of age. Access to perches did not affect breast muscle weight, percentage breast muscle, percentage leg muscle, bone mineral density, bone length, bone width, adrenal weight, packed cell volume, and hyperkeratosis of the foot-pad and toes. There were no differences in BW, bone mineral content, and leg muscle weight at 3 and 6 wk of age. However, at 12 wk of age, BW (P = 0.025), bone mineral content of the tibia, sternum, and humerus (P = 0.015), and the left leg muscle weight (P = 0.006) increased in pullets with access to perches as compared with controls. These results suggest that perch access has beneficial effects on pullet health by stimulating leg muscle deposition and increasing the mineral content of certain bones without causing a concomitant decrease in bone mineral density.

Daily feed intake, energy intake, growth rate and measures of dietary energy efficiency of pigs from four sire lines fed diets with high or low metabolizable and net energy concentrations.

A TRIAL WAS CONDUCTED TO: i) evaluate the BW growth, energy intakes and energetic efficiency of pigs fed high and low density diets from 27 to 141 kg BW, ii) evaluate sire line and sex differences when fed both diets, and iii) to compare ME to NE as predictor of pig performance. The experiment had a replicated factorial arrangement of treatments including four sire lines, two sexes (2,192 barrows and 2,280 gilts), two dietary energy densities and a light or heavy target BW, 118 and 131.5 kg in replicates 1 to 6 and 127 and 140.6 kg in replicates 7 to 10. Pigs were allocated to a series of low energy (LE, 3.27 Mcal ME/kg) corn-soybean meal based diets with 16% wheat midds or high energy diets (HE, 3.53 to 3.55 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. Pigs were weighed and pen feed intake (11 or 12 pigs/pen) recorded at 28-d intervals. The barrow and gilt daily feed (DFI), ME (MEI) and NE (NEI) intake data were fitted to a Bridges function of BW. The BW data of each sex were fitted to a generalized Michaelis-Menten function of days of age. ME and NE required for maintenance (Mcal/d) were predicted using functions of BW (0.255 and 0.179 BW^0.60 respectively). Pigs fed LE diets had decreased ADG (915 vs. 945 g/d, p<0.001) than pigs fed HE diets. Overall, DFI was greater (p<0.001) for pigs fed the LE diets (2.62 vs. 2.45 kg/d). However, no diet differences were observed for MEI (8.76 vs. 8.78 Mcal/d, p = 0.49) or NEI (6.39 vs. 6.44 Mcal/d, p = 0.13), thereby indicating that the pigs compensated for the decreased energy content of the diet. Overall ADG:DFI (0.362 vs. 0.377) and ADG:Mcal MEI (0.109 vs. 0.113) was less (p<0.001) for pigs fed LE compared to HE diets. Pigs fed HE diets had 3.6% greater ADG:Mcal MEI above maintenance and only 1.3% greater ADG:Mcal NEI (0.152 versus 0.150), therefore NEI is a more accurate predictor of growth and G:F than MEI. Pigs fed HE diets had 3.4% greater ADG:Mcal MEI and 0.11% greater ADG:NEI above maintenance than pigs fed LE diets, again demonstrating that NEI is a better predictor of pig performance than MEI. Pigs fed LE diets had similar daily NEI and MEI but grew slower and less efficiently on both ME and NE basis than pigs fed HE diets. The data suggest that the midds NE value (2.132 Mcal/kg) was too high for this source or that maintenance was increased for pigs fed LE diets.

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.

Evaluation of the prediction of alternative measures of pork carcass composition by three optical probes.

The accuracy of 3 optical probes (HGP4 Hennessey Grading Probe, Destron-Feering PG-100 probe, and Giraldo OPTO-Electronic PG-200 probe) to predict the carcass percentage of 5 alternative measures of carcass composition (fat-tissue-free lean, lipid-free soft tissue, lipid-free lean, total fat tissue, and soft tissue lipid) was evaluated on 203 barrows and gilts of 7 genetic populations. The optical probe backfat depths were more closely correlated (P < 0.001, 0.963 to 0.983) than the LM depths (r = 0.695 to 0.734). The optical probe backfat depths were related to lean percentage (r = -0.82 to -0.88), total fat tissue percentage (r = 0.84 to 0.88), and soft tissue lipid percentage (r = 0.86 to 0.87). Optical probe LM depths were weakly related (P < 0.05; r = 0.23 to 0.34) to measures of carcass lean percentage and total fat tissue percentage (r = -0.16 to -0.26). Fat-free lean percentage was predicted with residual SD (RSD) of 3.7% for equations including last-rib midline backfat thickness, 2.4 to 2.7% for equations including optical probe backfat and LM depth, and 2.3% for ribbed carcass measurements. The RSD for the optical probe equations ranged from 2.1 to 2.4% for lipid-free soft tissue percentage and from 2.0 to 2.3% for lipid-free lean percentage. The RSD for the optical probe equations ranged from 2.9 to 3.3% for total fat tissue percentage and 2.5 to 2.8% for soft tissue lipid percentage. Quadratic and cross-product variables of optical probe fat depth, LM depth, and carcass weight were significant (P < 0.05) and reduced the RSD of the equations. Optical probe backfat and LM measurements can be used to predict alternative measures of carcass composition. The predicted relationships in fat-free lean percentage to backfat depth were nearly identical for each optical probe.

Comparison of reticular and rectal core body temperatures in lactating dairy cows.

The Phase IV Cattle Temperature Monitoring System (CTMS; Phase IV Engineering Inc., Boulder, CO) marketed by MaGiiX (MaGiiX Inc., Post Falls, ID) uses a passive bolus equipped with a temperature sensor, a panel reader placed at a parlor entrance or exit to query the bolus, and a software package to collect, analyze, and view data. The biologically inert bolus resides in the cow's reticulum and is queried each time the cow passes the reader. Reticular temperature (RETT) and rectal temperature (RECT) were recorded simultaneously in the milking parlor exit lane in 4 consecutive milkings in each of 4 seasons, totaling 16 measurements per cow. The RETT were obtained by using the phase IV CTMS, whereas the RECT were obtained manually with a GLA M750 thermometer (GLA Agricultural Electronics, San Luis Obispo, CA). Data were edited to remove RETT likely to have been affected by a recent drinking bout. For the 2,042 observations used in analyses, means (+/-SD) were 39.28 (+/-0.41), 38.83 (+/-0.36), and 0.45 (+/-0.33) for RETT, RECT, and the difference between RETT and RECT, respectively. The RETT and RECT were strongly correlated (r = 0.645). The relationship between RETT and RECT varied by season, milking, housing system, and parity. Because dairy producers and veterinarians are accustomed to viewing rectal temperatures, equations to adjust reticular temperatures to a rectal-based scale may increase the utility of the phase IV CTMS. The resulting conversion equations were RECT = 19.23 + 0.496(RETT) for the a.m. milking and RECT = 15.88 + 0.587(RETT) for the p.m. milking.

Impact of intake water temperatures on reticular temperatures of lactating dairy cows.

Automatic temperature recording may allow early detection of disease, estrus, heat stress, and the onset of calving. The phase IV Cattle Temperature Monitoring System (MaGiiX Inc., Post Falls, ID) utilizes a passive bolus equipped with a temperature sensor, a stationary panel reader to query the bolus, and software to collect, analyze, and display data. One potential limitation to collection of reticular temperatures is the effect of water temperature and consumption on recorded temperatures. Two replicated 3 x 3 Latin square experiments were conducted at the Purdue Dairy Research and Education Center to assess the impact of water intake on reticular temperatures using the Cattle Temperature Monitoring System. Nine high-producing, mid-lactation, second-parity cows with low somatic cell counts were selected. Before administering a water treatment, access to feed and water was restricted for at least 2 h. Baseline reticular temperatures were established from measurements before water intake. In experiment 1, treatments were 25.2 kg of hot water (34.3 degrees C +/- 1.0), warm water (18.2 degrees C +/- 0.4), or cold water (7.6 degrees C +/- 0.4). In experiment 2, treatments were 18.9 kg of body-temperature water (38.9 degrees C +/- 0.2), cold water (5.1 degrees C +/- 0.4), or control (no water). Following water intake, reticular temperatures were collected for 3 h. In experiment 1, an initial dramatic decrease in reticular temperature was observed followed by a gradual increase toward baseline. Least squares means for maximum drop in temperature were 8.5 +/- 0.5, 6.9 +/- 0.5, and 2.2 +/- 0.5 degrees C for cold, warm, and hot water treatments, respectively. Yet at 3 h, reticular temperatures did not return to the baseline. In experiment 2, control cows remained within the baseline confidence interval through the observation period, and cows receiving body temperature water experienced an initial decrease in temperature (0.4 +/- 0.2 degrees C) with a return to within the baseline confidence interval within 15 min. Cows receiving cold water did not return to within the baseline confidence interval after a large decrease of 9.2 +/- 0.2 degrees C during the 3-h observational period. Moreover, a regression analysis of continued ascent in temperatures predicted that temperatures would return to baseline within 3.5 h. These results demonstrate that, when cows consume large quantities of cold water, the effect of water intake is sizable and sustained. The value of reticular temperatures for daily monitoring in a production setting hinges largely on the implications of this impact.

Influence of stressors on normal intestinal microbiota, intestinal morphology, and susceptibility to Salmonella enteritidis colonization in broilers.

In modern poultry production systems, environmental stressors may influence bird performance and susceptibility to pathogens such as Salmonella Enteritidis. Experiments were conducted to determine the influence of 24-h feed withdrawal and 24-h exposure to high temperature (30 degrees C) on intestinal characteristics of broilers. Attachment of Salmonella Enteritidis to ileal tissue was determined using an in vitro ileal loop assay. Changes in commensal intestinal microbial populations were determined using denaturing gradient gel electrophoresis, and alterations in ileal morphology were determined histologically. Ex vivo attachment of Salmonella Enteritidis to ileal tissues increased by 1.5 logs (9.05 log10 vs. 7.59 log (10) Salmonella Enteritidis/g of ileal tissue; P = 0.0006) in broilers fasted for 24 h. Similarly, ileal tissues from birds subjected to 30 degrees C for 24 h had increased ex vivo attachment of Salmonella Enteritidis (8.77 log(10) vs. 8.50 log(10) Salmonella Enteritidis/g of ileum; P = 0.01) compared with birds held at 23 degrees C. Exposure to 30 degrees C for 24 h also altered microbial community structure in the ileum and cecum. Subjecting birds to 30 degrees C for 24 h reduced crypt depth (6.0 vs. 7.8 microm, respectively; P = 0.002), but had no effect on villus height or villus:crypt ratio. This research shows that acute stressors in poultry production systems can cause changes in the normal intestinal microbiota and epithelial structure, which may lead to increased attachment of Salmonella Enteritidis.

Growth of protein, moisture, lipid, and ash of two genetic lines of barrows and gilts from twenty to one hundred twenty-five kilograms of body weight.

Two genetic lines of barrows and gilts with different lean growth rates were used to determine the BW and chemical composition growth from 23 to 125 kg of BW. The experiment was a 2 x 2 x 5 factorial arrangement of treatments in a completely randomized design conducted in 2 replicates. Six pigs from each sex and genetic line were killed at approximately 25-kg intervals from 23 kg to 125 kg of BW. At slaughter, tissues were collected and weighed. All components were ground and frozen until analyzed for water, protein, lipid, and ash. Serial BW data were fitted to alternative functions of day of age. Based on Akaike's information criteria values, the random effects model, BW(i, t) = (1 + c(i))(b(0) + b(1)t + b(2)t(2)), was the best mixed model equation. The chemical component mass data were fitted to alternative functions of BW. The allometric function, chemical component mass = aBW(b), provided the best fit to the data. Daily deposition rates of each chemical component were predicted by using the derivatives of the 2 functions. The overall ADG of the 2 genetic lines were not different. Barrows had 0.052 kg/d greater (P = 0.03) ADG than gilts. Allometric growth coefficients for all 4 chemical components were different (P < 0.01) for each genetic line. Allometric coefficients and predicted relative growth (g/kg of BW gain) for protein and moisture mass were greater (P < 0.01) for the high lean-gain pigs than the low lean-gain pigs. Allometric coefficients for lipid mass were smaller (P = 0.001) for the high lean-gain pigs than the low lean-gain pigs overall. Allometric coefficients and predicted relative growth rates for lipid mass were greater (P < 0.01) and for moisture and protein mass were lesser (P < 0.002) than the gilts. Compared with low lean-gain pigs, high lean-gain pigs had (1) 32.8% lesser predicted daily rates of lipid deposition (200 vs. 305 +/- 80 g/d), with the difference increasing from 23 to 37% from 25 to 125 kg of BW; (2) 12.3% greater daily rates of protein deposition (118.7 vs. 106.0 +/- 3.3 g/d); and (3) 18.8% greater predicted daily moisture accretion rates (423 vs. 356 +/- 9 g/d). Overall, barrows had 21.3% greater lipid deposition (279 vs. 230 +/- 78.2 g/d) than gilts. In this study, barrows and gilts had similar predicted daily moisture, protein, and ash accretion rates.

Evaluation of the impact of errors in the measurement of backfat depth on the prediction of fat-free lean mass.

The development of regression equations to predict carcass composition typically assumes that the independent variables, such as backfat depth, are measured without error. However, technological and operator-specific types of measurement errors do exist. To evaluate the impact of measurement error for backfat depth, Monte Carlo simulation was used to model carcass fat-free lean mass (FFLM) in pigs. In the simulation, FFLM was a linear function of carcass weight and actual backfat depth (ABFD). Carcass weight was assumed to be measured without error, but measurement errors were generated such that the correlation (r(BF)) of the measured backfat depth (BFD) and ABFD ranged from 0.70 to 0.95. Two types of measurement errors were simulated: 1) constant variation that was additive to the variance of ABFD, and 2) variation proportional to the ABFD that was additive to the variance in ABFD. A total of 1,000 replications of 1,000 pigs were simulated. Within each type of measurement error, the absolute values of the regression coefficients and R2 values of the equations decreased as r(BF) decreased. The probability of the backfat depth squared (BFD2) being significant (P < 0.05) in the regression equation was increased when the measurement errors were proportional to ABFD. The occurrence of a significant BFD2 variable was 792 times out of 1,000 replications when r(BF) = 0.95 and increased to 996 times out of 1,000 when r(BF) = 0.85 for BFD with type 2 measurement errors. The inclusion of a CW x BFD variable in the regression equations (P < 0.05) increased (270 to 423 times out of 1,000) as r(BF) decreased from 0.85 to 0.70 for BFD with type 2 errors. Equations developed from BFD with measurement errors resulted in biased predictions of FFLM and changes in FFLM per unit change in BFD. The level and type of measurement errors that exist in the independent variables should be evaluated.

Evaluation of alternative nonlinear mixed effects models of duck growth.

Two nonlinear growth functions were evaluated on 6 groups of 32 ducks. Ducks were randomly assigned to 1 of 6 dietary treatments and weighed weekly from 1 to 43 d of age. The Weibull function had the form: BW(it) = A - (A - B) exp - [(C - 1)/C] (t/IP)**C, where BW(it) is the BW of the ith duck at age t in days and A, B, C, and IP are fixed parameters. The variable A represents mature BW and the variable IP is the age (inflection point) at which maximum average daily gain is achieved. The addition of a single random effect to the Weibull growth function (ip), in which the age to reach the BW at the overall population inflection point of each duck varies, provided a substantially better fit than any other alternative fixed or mixed models. Overall, the Weibull function under-predicted the d-1 BW (46.7 vs. 55.1 g, P < 0.05) and over-predicted the d-8 BW (233.6 vs. 211.7 g, P < 0.05). The predicted BW from d 15 to 43 was very close to the actual mean BW at each age. This model predicts that the between-duck variance in BW increases with age and that the CV increases from 1 to 8 d of age, reaches a plateau from 15 to 22 d of age, and then slowly declines. This mixed effects model predicts the mean age and approximate variation in age that ducks require to reach a specific BW, and is easily adaptable to stochastic modeling.

Development of a model to describe the compositional growth and dietary lysine requirements of pigs fed ractopamine.

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 cm2), 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.

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.

Utilisation of a sperm quality analyser to evaluate sperm quantity and quality of turkey breeders.

1. A relatively new instrument known as a Sperm Quality Analyzer (SQA) offers a rapid assessment of sperm quality and quantity by providing a sperm quality index (SQI). The SQA measures a combination of the intensity of sperm activity and motile concentration by determining the number and amplitude of sperm movements per second in a capillary tube as detected through light beam interference. 2. Because the SQA has not been tested for its potential use in turkeys, the objective was to determine if the SQA could accurately respond to changes in turkey sperm concentration, viability, and motility in semen collected from turkey breeders. 3. The effect of varying concentrations of sperm on SQI values was evaluated by diluting replicate pools of semen from 4 different aged turkey breeder flocks with saline. Results from all 4 flocks showed that semen dilutions greater than 20-fold resulted in a linear decline in SQI values. 4. Additional in vitro analysis evaluated the effects of turkey sperm viability on the SQI under conditions of constant sperm concentration. Incubated, live sperm was mixed in various proportions with thawed, dead sperm to determine changes in viability. Increased proportions of dead sperm caused a decline in the SQI. 5. To assess sperm motility, turkey semen was incubated under either aerobic (motile) or anaerobic (immotile) conditions. Varied amounts of immotile and motile sperm samples were mixed. A linear increase in the SQI was observed as per cent motile sperm increased. 6. These results indicate that the SQA can respond to differences in turkey sperm concentration, viability, and motility using in vitro analyses.

Evaluation of alternative measures of pork carcass composition.

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 (R2 = 0.74 to 0.81) from either DL, FFLM, LFSTIS, or ribbed carcass measurements. Empty body lipid was predicted more accurately from TOFAT (R2 = 0.92) or STLIP (R2 = 0.93) than ribbed carcass measurements (R2 = 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.

Health and growth performance of barrows reared in all-in/all-out or continuous flow facilities with or without a chlortetracycline feed additive.

OBJECTIVE: To compare health and growth performance in barrows reared in all-in/all-out (AIAO) or continuous flow (CF) management systems. ANIMALS: 400 barrows. PROCEDURE: Barrows (approx 2 months old) were allotted to 4 replications (100 barrows each); barrows were housed in AIAO or CF rooms (10 pens/room), and 50 pigs/replicate received chlortetracycline (CTC, 110 mg/kg of feed). Barrows from each pen were slaughtered at 3, 4, 5, and 6 months old. RESULTS: Barrows in the AIAO room had greater total daily gain (TDG) and lean daily gain (LDG) than did barrows in the CF room. Addition of CTC did not improve TDG or LDG in either environment. Barrows in the AIAO room reached body weight of 104.5 kg in 169.7 days, compared with 177.3 days for barrows in the CF room. Feed-to-gain ratio was not affected by management or CTC. Lungs from barrows reared in AIAO facilities had a lower percentage of lesions than did lungs of barrows reared in CF facilities (1.74% vs 9.52%). Addition of CTC did not affect prevalence and extent of lung lesions. Extent of lung lesions was positively correlated with change in serum optical density (OD) to Mycoplasma hyopneumoniae (r = 0.35), but not with change in serum OD to Actinobacillus pleuropneumoniae. Lean growth and serum OD to M. hyopneumoniae and A. pleuropneumoniae were not correlated. CONCLUSIONS: Health and growth performance were better for barrows in an AIAO facility, compared with a CF facility, but addition of CTC to feed failed to enhance health or performance of barrows in either facility.

Prediction of daily protein accretion rates of pigs from estimates of fat-free lean gain between 20 and 120 kilograms live weight.

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.

Relationship to growth performance of pneumonia and atrophic rhinitis lesions detected in pigs at slaughter among four seasons.

A commercial swine herd was selected for study, because pigs at slaughter repeatedly had lung lesions consistent with enzootic pneumonia and had snout lesions typical of atrophic rhinitis. Pigs born during various seasons of the year were allotted to 4 investigations and were evaluated from birth to slaughter. Individual lungs and snouts were identified and collected at the slaughter plant and later examined for gross lesions of bronchopneumonia and atrophic rhinitis, respectively. Each lesion was scored, and the following comparisons were made within investigations: prevalence and mean scores for lung lesions; prevalence and mean grades for snout lesions; correlations between lung lesion scores and growth indicators; correlations between snout lesion grades and growth indicators; and correlations between lung lesion scores and snout grade scores. Included in the growth indicators were average daily gain during the growing phase, average daily gain during the finishing phase, average daily gain during growing and finishing phases, and days to attain 104.5 kg of body weight. Prevalence of lung or snout lesions, mean values for lung lesion scores, mean values for snout lesion grades, and mean values for the various growth indicators were tested for statistical differences among the 4 investigations. Prevalence of lung lesions was highest (96%) for winter-slaughtered and lowest (81%) for autumn-slaughtered pigs. Mean scores for lung lesions were 7% (summer), 5% (autumn), 9% (winter), and 16% (spring). Prevalence of snout lesions was highest (85%) for spring-slaughtered pigs and lowest (42%) for autumn-slaughtered pigs.(ABSTRACT TRUNCATED AT 250 WORDS)