Interest in housing dairy calves in groups is currently growing. Group housing using individual calf hutches, a resource already available in most dairy farms in North America, could provide a novel housing method that can be a simple way to implement group housing on farm. The main objective of this study was to determine whether pair housing dairy calves in hutches outdoors would result in similar weight gain and milk intake compared with individual housing in hutches. The study was designed to avoid competition for resources (including milk and solid feed, teat, bucket, outdoor space, and hutch) to test a setup that has the potential to maximize performance and calf growth. Secondary objectives were to document how calves in both treatments use their environment in terms of time spent and behaviors performed in each area, how paired calves interact, and the time they spend together. Single calves (n = 6/season) were housed in 1 hutch with an attached outdoor environment; paired calves (n = 6 pairs/season) were given twice the resources. Calves were fed up to 16 L/d of milk replacer. Daily milk intake and weekly weight gains were recorded. Behavioral observations were recorded live once per week for 5 (summer) or 4 (winter) nonconsecutive periods. Paired and single calves had similar weight gain (averaging from 1.1 to 1.3 kg/d across trials) and milk intake (averaging from 11.1 to 13.7 kg/d across trials), showing no difference in performance between treatments. Low occurrences of cross sucking (averaging from 0.1 to 0.4 bouts/h of observation per pen across trials) and displacements at the teat (0.8 to 1.4 bouts/h of observation per pen across trials) were found. All calves altered their behavior in some way to accommodate companions; paired calves were seen interacting and spending time together (i.e., lying in the same hutch), and in the summer trial single calves spent less time lying inside the hutch than paired calves, presumably to have visual access to other calves. The solution of mixed indoor and outdoor housing environments tested as part of this study showed that calves make use of all spaces provided to them in winter and in summer conditions while maintaining good performance. Housing calves in pairs using individual hutches can be a suitable alternative to housing calves individually in hutches outdoors.

This study aimed to examine the correlation of carcass weight, fat depth, muscle depth, and predicted lean yield in commercial pigs. Data were collected on 850,819 pork carcasses from the same pork processing facility between October 2017 and September 2018. Hot carcass weight was reported following slaughter as a head-on weight; while fat and muscle depth were measured with a Destron PG-100 probe and used for the calculation of predicted lean yield based on the Canadian Lean Yield (CLY) equation [CLY (%) = 68.1863 − (0.7833 × fat depth) + (0.0689 × muscle depth) + (0.0080 × fat depth2) − (0.0002 × muscle depth2) + (0.0006 × fat depth × muscle depth)]. Descriptive statistics, regression equations including coefficients of determination, and Pearson product moment correlation coefficients (when assumptions for linearity were met) and Spearman’s rank-order correlation coefficients (when assumptions for linearity were not met) were calculated for attributes using SigmaPlot, version 11 (Systat Software, Inc., San Jose, CA). Weak positive correlation was observed between hot carcass weight and fat depth (r = 0.289; P < 0.0001), and between hot carcass weight and muscle depth (r = 0.176; P < 0.0001). Weak negative correlations were observed between hot carcass weight and predicted lean yield (r = −0.235; P < 0.0001), and between fat depth and muscle depth (r = −0.148; P < 0.0001). Upon investigation of relationships between fat depth and predicted lean yield, and between muscle depth and predicted lean yield using scatter plots, it was determined that these relationships were not linear and therefore the assumptions of Pearson product moment correlation were not met. Thus, these relationships were expressed as nonlinear functions and Spearman’s rank-order correlation coefficients were used. A strong negative correlation was observed between fat depth and predicted lean yield (r = −0.960; P < 0.0001), and a moderate positive correlation was observed between muscle depth and predicted lean yield (r = 0.406; P < 0.0001). Results from this dataset revealed that hot carcass weight was generally weakly correlated (r < |0.35|) with fat depth, muscle depth, and predicted lean yield. Therefore, it was concluded that there were no consistent weight thresholds where pigs were fatter or heavier muscled.

This study examined the relationship of iodine value (IV) with carcass weight, fat depth, muscle depth, and predicted lean yield from 37,488 pork carcasses. Five IV categories were formed, which were defined as low (<64.99), medium-low (65.00–69.99), medium (70.00–74.99), medium-high (75.00–79.99), and high (>80.00). Correlation analysis indicated IV was weakly correlated (r ≤ 0.26; P < 0.05) with all carcass traits, however the categorical analysis revealed that greater IV was associated with heavier weight and leaner carcasses. Segregation systems of pork carcasses based on IV should consider the relationships of IV with other carcass parameters before implementation.

This study compared accuracy of two methods for predicting carcass leanness (i.e., predicted lean yield) with fat-free lean yields obtained by manual carcass side cut-out and dissection of lean, fat, and bone components. The two prediction methods evaluated in this study estimated lean yield by measuring fat thickness and muscle depth at one location with an optical grading probe (Destron PG-100) or by scanning the entire carcass with advanced ultrasound technology (AutoFom III). Pork carcasses (166 barrows and 171 gilts; head-on hot carcass weights ranging from 89.4 to 138.0 kg) were selected based on their fit within desired hot carcass weight ranges, their fit within specific backfat thickness ranges, and sex (barrow or gilt). Data (n = 337 carcasses) were analyzed using a 3 × 2 factorial arrangement in a randomized complete block design including the fixed effects of method for predicting lean yield, sex, and their interaction, and random effects of producer (i.e., farm) and slaughter date. Linear regression analysis was then used to examine the accuracy of the Destron PG-100 and AutoFom III data for measuring backfat thickness, muscle depth, and predicted lean yield when compared with fat-free lean yields obtained with manual carcass side cut-out and dissections. Partial least squares (PLS) regression analysis was used to predict the measured traits from image parameters generated by the AutoFom III software. There were method differences (P ˂ 0.01) for determining muscle depth and lean yield with no method differences (P = 0.27) for measuring backfat thickness. Both optical probe and ultrasound technologies strongly predicted backfat thickness (R  2 ≥ 0.81) and lean yield (R  2 ≥ 0.66), but poorly predicted muscle depth (R  2 ≤ 0.33). The AutoFom III improved accuracy [R 2 = 0.77, root mean square error (RMSE) = 1.82] for determination of predicted lean yield versus the Destron PG-100 (R 2 = 0.66, RMSE = 2.22). The AutoFom III was also used to predict bone-in/boneless primal weights, which is not possible with the Destron PG-100. The cross-validated prediction accuracy for the prediction of primal weights ranged from 0.71 to 0.84 for bone-in cuts and 0.59 to 0.82 for boneless cut lean yield. The AutoFom III was moderately (r ≤ 0.67) accurate for the determination of predicted lean yield in the picnic, belly, and ham primal cuts and highly (r ≥ 0.68) accurate for the determination of predicted lean yield in the whole shoulder, butt, and loin primal cuts.