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The value of precise dual energy X-ray absorptiometry (DEXA) cut weight predictions to lamb allocation to cut plans is unknown. Lambs (n = 191) varying in carcase weight (HSCW) and GR (tissue depth over the 12th rib) were DEXA scanned and boned out to weigh retail cuts. Cut weights were predicted using HSCW; HSCW + GR; HSCW + DEXA and HSCW + DEXA image components in GLM models. DEXA improved cut weight predictions in most cuts (P < 0.05). A dataset of 10,000 carcases was then simulated using the associations between HSCW, GR and cut weights, before being truncated to 4500 lambs representing onel day's HSCW distribution. A lamb Carcase Optimisation Tool scenario was developed with 2-3 cut options per carcase section and cut weight thresholds applied to several cuts. Processing costs, market values and actual cut weights were input into the Optimiser to determine carcase allocation to cut options for optimised profits. This scenario was repeated using the predicted cut weights to determine the cut misallocations caused. DEXA-predicted cut weights produced 16.7% and 8.0% less misallocations than HSCW and GR. DEXA produced 20.8% and 14.3% less misallocations than HSCW and GR in shortloins, and 25.5% and 12.9% less in hindquarters. While cut misallocations have little direct impact on total profits, as product is over and under-valued when misallocated, reducing cut misallocations will improve processor compliance when sorting carcases into cut plans- reducing their need to retrim, downgrade and repackage product or the erosion of customer confidence caused by supplying product not meeting market specifications., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Dual energy x-ray absorptiometry (DXA) devices were installed at two Australian abattoirs to predict computed tomography (CT) determined fat % and lean % of lamb carcasses. This study tested three algorithms developed for these devices, termed β1, β2 and β3, and assessed their accuracy and precision in predicting CT composition. Algorithm β3 included the use of a plastic phantom calibration block scanned by both DXA devices to adjust prediction equations, resulting in superior accuracy to the algorithms without phantom calibration (β1 and β2). When compared to the gold-standard CT composition, the bias of the DXA predictions was lowest when using algorithm β3 at the two sites (-1.17%, -0.49% for fat %, 0.11%, -0.37% for lean %). The difference of DXA composition predictions between sites was lowest when using algorithm β3, which demonstrated between site differences of 0.59 CT fat %, and 0.46 CT lean%. In contrast, algorithm β1 and β2 produced differences of 23.7% and 30.8% for CT fat, and 17.3% and 21.9% for CT lean between the two DXA devices. There was a small difference of 0.78% between the fat predictions of the first DXA image compared to the second DXA image for each carcass. The precision of predictions improved slightly using algorithm β3. This work demonstrates that the in-line DXA systems can produce comparable results across sites., Competing Interests: Declaration of competing interest There is no conflict of interest involved in this work, (Copyright © 2024. Published by Elsevier Ltd.)

Skeleton bones, distinguished by trabecular and cortical bone tissue content, exhibit varied growth and composition, in response to modified dietary calcium and phosphorus levels. The study investigated how gilts adapt their individual bone and bone region mineralisation kinetics in response to changing intake of Ca and P. A total of 24 gilts were fed according to a two-phase (Depletion (D) 60-95 and Repletion (R) 95-140 kg BW, respectively). During the D phase, gilts were fed either 60% (D60) or 100% (D100) of the estimated P requirement. Subsequently, during the R phase, half of the gilts from each D diet were fed either 100% (R100) or 160% (R160) of the estimated P requirement according to a 2 × 2 factorial arrangement. Bone mineral content (BMC) was assessed in the whole body, individual bones (femur and lumbar spine L2-L4), and bone regions (head, front legs, trunk, pelvis, femur, and hind legs) every 2 weeks using dual-energy X-ray absorptiometry (DXA). At 95 kg BW, gilts fed D60 showed reduced BMC and BMC/BW ratio in all studied sites compared to those fed D100 (P < 0.001). During the depletion phase, the allometric BW-dependent regressions slopes for BMC of D100 gilts remained close to 1 for all sites and did not differ from each other. In contrast, the slopes were lower in D60 gilts (P < 0.05), with an 18% reduction in the whole body, except for the front and hind legs, femur, and pelvis, which exhibited higher reductions (P < 0.05). At 140 kg BW, BMC and BMC/BW ratio of all studied sites were similar in gilts previously fed D60 and D100, but higher in R160 than in R100 gilts (P < 0.05), except for front and hind legs. During the repletion phase, the allometric BW dependent regressions slopes for BMC were lower (P < 0.05) in R100 than in R160 gilts (for whole body -10%; P < 0.01) except for front and hind legs, femur, and pelvis. In conclusion, bone demineralisation and recovery followed similar trends for all measured body sites. However, the lumbar spine region was most sensitive whereas the hind legs were least sensitive. These data suggest that using bone regions such as the head and forelegs that can be collected easily at the slaughterhouse may be a viable alternative to whole body DXA measurement., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

A prototype, on-line Dual Energy X-ray Absorptiometer (DXA) has shown high precision of the prediction of carcass composition for the purpose of improved sheep meat grading in the Australian lamb supply chain, albeit with small inaccuracies over time. These inaccuracies were present across hours, and more significantly across days, which were unacceptable for any accreditation of this device as an objective carcass measurement tool in Australia. This inaccuracy demanded the creation of a novel image-processing algorithm for the prototype DXA. This DXA was tested for repeatability of predictions of lamb carcass composition over minutes, hours, and days, using two developed image processing algorithms. There was high immediate repeatability for both algorithms when predicting lean muscle % in 40 lamb carcasses, with a maximum CV of 0.65% over five repeated scans. There was a decrease in the CV of the prediction of lean muscle % of 30 lambs scanned three times over a 48-h period from 5.93 to 1.19% when the superior algorithm was used. The inaccuracies of lean muscle % predictions were associated with increases in the unattenuated space pixel values in DXA images. Improvements of the current algorithm are required to demonstrate repeatability over time for the purpose of accreditation within the Australian sheep meat industry, and for possible expansion of this technology into international supply chains., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

An on-line Dual Energy X-ray Absorptiometry (DXA) scanner's tissue composition prediction precision and accuracy was tested across the entire height of the unit's detector, and the hardware was assessed for robustness by measuring X-ray photon intensity throughout production days. There was good precision when predicting the tissue composition of 5 different lamb fat and lean muscle mixtures across 3 different thicknesses (R 2  = 0.93 to 0.98, RMSE = 3.18% to 5.83%), however was less precise at the greatest thickness of 200 mm (R 2  = 0.59, RMSE = 11.4%). There was no significant difference in the prediction of tissue composition at 8 of the 9 detector positions, however the position at the perpendicular of the X-ray photon beam was significantly different, with a fat prediction error of -4%, although no lamb carcass is detected in this position during normal production. A significant upwards drift in X-ray photon intensity was found over the course of production, especially immediately after restarting the DXA scanner following a period of inactivity. This upwards drift may affect tissue composition predictions over the span of a production day if uncorrected., Competing Interests: Declaration of competing interest There is no conflict of interest involved in this work., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Despite the acknowledged significance of nutrition in bone development, effects of methionine (Met) and cysteine (Cys) on bone quality remain under-researched, particularly during Eimeria challenge. We investigated the effects of different supplemental Met to Cys ratios (MCR) on bone quality of broilers under Eimeria challenge. A total of 720 fourteen-day old Cobb500 broilers were allocated into a 5 × 2 factorial arrangement. Five diets with Met and Cys supplemented at MCR of 100:0, 75:25, 50:50, 25:75, and 0:100 were fed to the birds with or without Eimeria challenge. Body composition was measured by dual energy x-ray absorptiometry, and the femur bone characteristics were assessed by microtomography. Data were analyzed by two-way ANOVA and orthogonal polynomial contrast. The results reaffirmed the detrimental effects of Eimeria challenge on bone quality. On 9 d post inoculation (DPI), significant interaction effects were found for whole body bone mineral content (BMC), lean tissue weight, and body weight (P < 0.05); in the nonchallenged group (NCG), these parameters linearly decreased as MCR decreased (P < 0.05). In the challenged group (CG), body weight and lean tissue weight were unaffected by MCR, and BMC linearly increased as MCR decreased (P < 0.05). For the cortical bone of femoral metaphysis on 6 DPI, bone mineral density (BMD) linearly increased as MCR decreased (P < 0.05). Bone volume to tissue volume ratio (BV/TV) in the CG linearly increased as MCR decreased (P < 0.05). On 9 DPI, BMC and TV linearly increased as MCR decreased (P < 0.05) in the NCG. BMD and BV/TV changed quadratically as MCR decreased (P < 0.05). For the trabecular bone of femoral metaphysis on 9 DPI, BV/TV, and trabecular number linearly increased as MCR decreased (P < 0.05) in the NCG. For the femoral diaphysis, BV, TV, BMC on 6 DPI, and BMD on 9 DPI linearly increased as MCR decreased (P < 0.05). In conclusion, this study showed that both Eimeria challenge and varying supplemental MCR could influence bone quality of broilers., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Assessment of body composition is an essential aspect of veterinary canine care, particularly as prevalence of overweight and obesity in dogs is increasing. Few quantitative objective methods for body composition measurement are available for routine clinical use. Bioelectrical impedance analysis is widely used in human medicine and nutritional assessment and although it has shown promise in production animals it has not yet been adopted for companion animals. The present study validated bioimpedance spectroscopy (BIS) against the reference method of dual-energy X-ray absorptiometry. Resistivity coefficients for use in BIS were determined: ρe = 444.8 and ρi = 1477.8 ohm.cm and used to predict fat-free mass (FFM) in a cohort of 35 mixed breed dogs. Overall, FFM was predicted to within 3.5% of reference values. At an individual level, FFM was predicted within 2 standard deviations (95% confidence) of 10%. BIS provides an objective quantitative alternative to the widely used semi-quantitative body condition scoring. In addition, BIS provides estimates of body water volumes (total, extra-and intracellular), information that can be useful in fluid management. BIS is inexpensive, and simple to perform but does require brief (<5 min) sedation of the animal., Competing Interests: Conflict of interest statement Author Ward consults to ImpediMed Ltd. ImpediMed had no involvement in the execution of this study or in the preparation of this manuscript. None of the authors has any other financial or personal relationships that could inappropriately influence or bias the content of the paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Two trials were carried out to develop and validate linear regression equations for body composition prediction using Dual-energy X-ray absorptiometry (DEXA). In Trial 1, 300 Cobb500 male chickens raised from 1 to 42 d of age were scanned in DEXA to estimate total weight, fat mass, soft lean tissue (SLT) mass, bone mineral content (BMC), and fat percentage. DEXA estimates were compared to body ash, crude fat, SLT (sum of protein and water) and scale body weight. The dataset was split, with 70% used for prediction equations development and 30% for testing, and the 5k-fold cross-validation analysis was used to optimize the equations. The R 2 , mean absolute error (MAE), and root-mean-squared error (RMSE) were used as precision and accuracy indicators. A negative correlation (ρ = -0.27) was observed for ash content, while no correlation was observed for protein content (P > 0.05). Predictive linear equations were developed to assess broiler weight (R 2 = 0.999, MAE = 25.12, RMSE = 38.99), fat mass (R 2 = 0.981, MAE = 13.87, RMSE = 21.28), ash mass (R 2 = 0.956, MAE = 3.98, RMSE = 5.61), SLT mass (R 2 = 0.997, MAE = 35.73, RMSE = 52.45), water mass (R 2 = 0.997, MAE = 29.56, RMSE = 43.94), protein mass (R 2 = 0.989, MAE = 12.94, RMSE = 19.05), fat content (R 2 = 0.855, MAE = 0.81, RMSE = 1.05), SLT content (R 2 = 0.658, MAE = 1.01, RMSE = 1.28), and water content (R 2 = 0.678, MAE = 0.99, RMSE = 1.27). All equations passed the test. In Trial 2, 395 Cobb500 male chickens were raised from 1 to 42 d of age and used for validation of prediction equations. The equations developed for weight, fat mass, ash mass, SLT mass, water mass, and protein mass were validated. In conclusion, DEXA was found to be an effective approach for measuring the body composition of broilers when using predictive equations validated in this study for estimate calibration., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)