Live Animal Data Research Articles

Effects of heat stress mitigation strategies on feedlot cattle performance, environmental, and economic outcomes in a hot climate

The increase in average global temperatures presents a challenge for the beef industry, especially in the feedlot sector where heat stress is a major animal welfare and economic concern. Shade is one of the most practical methods to mitigate heat stress in feedlot cattle. An experiment was conducted as a completely randomized design with 1 560 Bos indicus bulls (initial BW=287 kg) where three shade structure types were used to investigate the effects of different heat stress mitigation methods on cattle growth performance, environmental, and economic outcomes using live animal data, and a partial lifecycle assessment using the Integrated Farm System Model. The live animal portion of the experiment was done once a year over a 2-year period with three pen replications per treatment per year (n = 6 per treatment). Four shade structures used were conventional shade (SC; steel shade 1.8 m2 of shade/animal), double conventional shade (DS; steel shade 3.6 m2 of shade/animal), dome structures without fans (DSA; 8.5 m2/animal with 98% solar radiation blocked), and domes with fans (DCA; DSA plus three large sized low-speed fans). Each pen held 65 bulls in an area of 570 m2. Live animal data were analyzed as a completely randomized design using the GLM procedure of SAS (version 9.4) with shade type as fixed effect, pen as the experimental unit, and repetition (year) considered a random effect. Cattle housed under DCA had 22 and 20 kg heavier final body BW (P < 0.05) compared to those housed under SC and DS, respectively. Final BW of DCA and DSA cattle were similar (P > 0.05). Average daily gain, feed efficiency, and hot carcass weight were greater (P < 0.05) for cattle housed under DCA compared to the rest of the shade types. Dry matter intake was not affected (P > 0.05). When treatment results were extrapolated to the annual feedlot turnover of 209,700 animals, cattle in DSA and DCA versus SC and DS had 3–8% reductions in greenhouse gas and ammonia emission intensities. Compared to SC, DCA increased profitability by $29.66/animal, followed by DSA and DS with profit increases of $5.79 and $8.90/animal, respectively. Overall, the implementation of advanced shade structures improved cattle performance and profitability while reducing the environmental impact of beef production.

Deep learning-based material decomposition of iodine and calcium in mobile photon counting detector CT.

Photon-counting detector (PCD)-based computed tomography (CT) offers several advantages over conventional energy-integrating detector-based CT. Among them, the ability to discriminate energy exhibits significant potential for clinical applications because it provides material-specific information. That is, material decomposition (MD) can be achieved through energy discrimination. In this study, deep learning-based material decomposition was performed using live animal data. We propose MD-Unet, which is a deep learning strategy for material decomposition based on an Unet architecture trained with data from three energy bins. To mitigate the data insufficiency, we developed a pretrained model incorporating various simulation data forms and augmentation strategies. Incorporating these approaches into model training results in enhanced precision in material decomposition, thereby enabling the identification of distinct materials at individual pixel locations. The trained network was applied to the acquired animal data to evaluate material decomposition results. Compared with conventional methods, the newly generated MD-Unet demonstrated more accurate material decomposition imaging. Moreover, the network demonstrated an improved material decomposition ability and significantly reduced noise. In addition, they can potentially offer an enhancement level similar to that of a typical contrast agent. This implies that it can acquire images of the same quality with fewer contrast agents administered to patients, thereby demonstrating its significant clinical value.

274 Comparison of Two Ultrasound Systems for Estimation of Carcass Attributes in Feedlot Steers

Abstract Sixty-eight (68) crossbred steers were evaluated using two real-time, B-mode ultrasound units to estimate final carcass attributes. The cattle were ultrasounded at the West Texas A&amp;M research feedlot (Canyon, Texas) and carcass data was collected at the West Texas A&amp;M Meats Laboratory (Canyon, Texas) or Tyson Fresh Meats (Amarillo, Texas). Objectives of the study were 1) to compare ultrasound live animal data to carcass attributes at harvest 2) to evaluate the performance differences between the ALOKA 500 (ALK) and the EVO ultrasound units All ultrasound images were captured by the same Ultrasound Guidelines Council (UGC) certified technician with images being processed at the UltraInsights Laboratory (Pierce, Colorado). The correlations between 12th rib fat thickness of the carcass (FTC) and ultrasound (FTU) were 0.84 for the ALK and 0.85 for the EVO, with no differences being found between the two units (P = 0.15). Correlations between the 12-13th rib carcass ribeye area (REAC) and ultrasound ribeye area (REAU) were 0.69 for the ALK and 0.66 for the EVO. There was no difference in REAU size between the two units. Carcass marbling score (MS) and ultrasound intramuscular fat (IMFU) correlations were 0.78 for the ALK and 0.84 for the EVO. The IMF data were found to be different between the two units, with the EVO measuring a mean IMFU value of 6.03 and the ALK a value of 5.26 with the change of 0.77 being different (P &amp;lt; 0.01). It is concluded that both ultrasound units performed favorably when predicting FTC and marbling score but were not highly correlated for REAU. It was found that the predictions between the two units on FT and REA were the same, though the EVO was higher on both. The IMFU values between the ALK and EVO were different, with the EVO again predicting higher values.

Body Caudal Undulation Measured by Soft Sensors and Emulated by Soft Artificial Muscles.

We propose the use of bio-inspired robotics equipped with soft sensor technologies to gain a better understanding of the mechanics and control of animal movement. Soft robotic systems can be used to generate new hypotheses and uncover fundamental principles underlying animal locomotion and sensory capabilities, which could subsequently be validated using living organisms. Physical models increasingly include lateral body movements, notably back and tail bending, which are necessary for horizontal plane undulation in model systems ranging from fish to amphibians and reptiles. We present a comparative study of the use of physical modeling in conjunction with soft robotics and integrated soft and hyperelastic sensors to monitor local pressures, enabling local feedback control, and discuss issues related to understanding the mechanics and control of undulatory locomotion. A parallel approach combining live animal data with biorobotic physical modeling promises to be beneficial for gaining a better understanding of systems in motion.

Environmental factors and occurrence of horseshoe crabs in the northcentral Gulf of Mexico.

This study provides regional-scale data on drivers of horseshoe crab (Limulus polyphemus) presence along the northcentral Gulf of Mexico coast and has implications for understanding habitat suitability for sparse horseshoe crab populations of conservation concern worldwide. To collect baseline data on the relationship between environmental factors and presence of horseshoe crabs, we surveyed four sites from the Fort Morgan peninsula of Mobile Bay, Alabama (AL) to Horn Island, Mississippi (MS). We documented number, size and sex of live animals, molts, and carcasses as metrics of horseshoe crab presence and demographics for two years. Data were compared to in situ and remotely sensed environmental attributes to assess environmental drivers of occurrence during the time of study. Overall, greater evidence of horseshoe crab presence was found at western sites (Petit Bois and Horn Islands) compared to eastern sites (Dauphin Island, Fort Morgan peninsula), mediated by a combination of distance from areas of high freshwater discharge and interannual variation in weather. Higher sex ratios also were found associated with higher occurrence, west of Mobile Bay. Land cover, particularly Bare Land and Estuarine Emergent Wetland classes that are common to western sites, was most predictive of live animal and to some extent carcass occurrence. Our findings suggest that small-scale variation in habitat quality can affect occurrence of horseshoe crabs in sparse populations where density is not a limiting factor. Data from molts and carcasses were informative to supplement live animal data and may be useful to enhance ecological assessment and support conservation and management in regions with sparse populations.

Role of Drug Anesthesia and Cancer.

Mortality and morbidity rate among cancer patients is at an alarming rate and its ratio of incidence is increasing as a result of its effects of metastasis and recurrence in its patients. Anesthetists are faced with the challenges daily of handling and treating cancer patients, for surgical resection to removal of the primary tumor. Retrospective analyses and studies have proposed a link between anesthetic technique and cancer outcomes. In this mini-review, we will give a summary of some of the available effects of anesthetic and analgesic techniques on cancer metastasis as derived from experimental cell culture and live animal data and also from clinical studies.

Effects of anesthetic and analgesic techniques on cancer metastasis.

The rate of mortality and morbidity among cancer patients is at an alarming rate and its ratio of incidence is increasing as a result of its effects of metastasis and recurrence in its patients. Several factors including anesthetic agents and analgesia techniques have been identified as causative agents for cancer metastasis. In this mini-review, we will summarize some of the available effects of anesthetic and analgesic techniques on cancer metastasis as derived from experimental cell culture and live animal data and also form clinical studies.

A validated method for modeling anthropoid hip abduction in silico.

The ability to reconstruct hip joint mobility from femora and pelves could provide insight into the locomotion and paleobiology of fossil primates. This study presents a method for modeling hip abduction in anthropoids validated with in vivo data. Hip abduction simulations were performed on a large sample of anthropoids. The modeling approach integrates three-dimensional (3D) polygonal models created from laser surface scans of bones, 3D landmark data, and shape analysis software to digitally articulate and manipulate the hip joint. Range of femoral abduction (degrees) and the abducted knee position (distance spanned at the knee during abduction) were compared with published live animal data. The models accurately estimate knee position and (to a lesser extent) angular abduction across broad locomotor groups. They tend to underestimate abduction for acrobatic or suspensory taxa, but overestimate it in more stereotyped taxa. Correspondence between in vivo and in silico data varies at the specific and generic level. Our models broadly correspond to in vivo data on hip abduction, although the relationship between the models and live animal data is less straightforward than hypothesized. The models can predict acrobatic or stereotyped locomotor adaptation for taxa with values near the extremes of the range of abduction ability. Our findings underscore the difficulties associated with modeling complex systems and the importance of validating in silico models. They suggest that models of joint mobility can offer additional insight into the functional abilities of extinct primates when done in consideration of how joints move and function in vivo. Am J Phys Anthropol 160:529-548, 2016. © 2016 Wiley Periodicals, Inc.

Post-mortem prediction of primal and selected retail cut weights of New Zealand lamb from carcass and animal characteristics

Post-mortem measurements (cold weight, grade and external carcass linear dimensions) as well as live animal data (age, breed, sex) were used to predict ovine primal and retail cut weights for 792 lamb carcases. Significant levels of variance could be explained using these predictors. The predictive power of those measurements on primal and retail cut weights was studied by using the results from principal component analysis and the absolute value of the t-statistics of the linear regression model. High prediction accuracy for primal cut weight was achieved (adjusted R2 up to 0.95), as well as moderate accuracy for key retail cut weight: tenderloins (adj-R2=0.60), loin (adj-R2=0.62), French rack (adj-R2=0.76) and rump (adj-R2=0.75). The carcass cold weight had the best predictive power, with the accuracy increasing by around 10% after including the next three most significant variables.

Can anaesthetic and analgesic techniques affect cancer recurrence or metastasis?

Cancer is a leading cause of morbidity and mortality worldwide and the ratio of incidence is increasing. Mortality usually results from recurrence or metastases. Surgical removal of the primary tumour is the mainstay of treatment, but this is associated with inadvertent dispersal of neoplastic cells into the blood and lymphatic systems. The fate of the dispersed cells depends on the balance of perioperative factors promoting tumour survival and growth (including surgery per se, many anaesthetics per se, acute postoperative pain, and opioid analgesics) together with the perioperative immune status of the patient. Available evidence from experimental cell culture and live animal data on these factors are summarized, together with clinical evidence from retrospective studies. Taken together, current data are sufficient only to generate a hypothesis that an anaesthetic technique during primary cancer surgery could affect recurrence or metastases, but a causal link can only be proved by prospective, randomized, clinical trials. Many are ongoing, but definitive results might not emerge for a further 5 yr or longer. Meanwhile, there is no hard evidence to support altering anaesthetic technique in cancer patients, pending the outcome of the ongoing clinical trials.

Prediction of body weight and empty body composition using body size measurements in lactating dairy cows

Body composition and live animal measurements of Holstein–Friesian lactating dairy cows ( n = 146) were obtained from a large herd to represent a range of animal factors including parity, live weight (LW), body condition score (BCS), milk yield and stage of lactation. Live animal measurements were recorded 3 or 4 days prior to slaughter, including LW, BCS, milk yield, heart girth, belly girth, withers height and length. The objective was to develop prediction equations for body weight and component mass from body size measurements and other live animal data. All body size measurements were positively ( P < 0.001) related to LW, empty body (EB) weight (EBW), carcass weight and EB masses (kg) of lipid, CP, DM, water and ash and total GE content (MJ). The correlation coefficients ( r) in these relationships were highest with heart girth (0.62 to 0.88), followed by belly girth (0.52 to 0.88) and length (0.51 to 0.83) and lowest with withers height (0.35 to 0.69). Heart girth was therefore selected as the primary predictor and a number of equations were then developed for prediction of body weight and EB mass, with the effect of parity or stage of lactation removed, where appropriate. All relationships were significant ( P < 0.001) and each predictor had a significant effect on the relationship ( P < 0.05). The adjusted R 2 values in the linear/quadratic relationships of heart girth with body weight and EB masses ranged from 0.53 (lipid mass) to 0.78 (LW). Addition of a range of other live animal variables (belly girth, length and BCS) to support heart girth significantly improved all relationships, with the Cp statistic and RMSPE (root mean square prediction error) values considerably reduced and adjusted R 2 values increased. These equations were evaluated through internal validation, by developing a range of similar new equations from two thirds of the present data and then validating these new equations with the remaining one third of data. The validation revealed a high prediction accuracy for LW, EBW, carcass weight and EB masses of CP, water and DM, a relatively good accuracy for EB lipid mass and total GE content, and a relatively poor accuracy for EB ash mass. In conclusion, body size measurements can be used together with other live animal factors to accurately predict body weight and EB component mass of lactating dairy cows. These equations provide an alternative approach to estimate body weight and component mass of lactating dairy cows.

Prediction of body weight and composition in lactating dairy cows: Prediction of empty body contents of lipid and crude protein

The accurate prediction of body composition of dairy cows is important for developing appropriate nutritional and management regimes. The objective of the present study was to develop prediction equations for empty body (EB) composition of lactating dairy cows using body weight and other live animal data.

Prediction of body weight and composition in lactating dairy cows: Prediction of empty body weight and carcass weight

Empty body (EB) weight (EBW) is used to estimate the energy and protein requirements for maintenance for dairy cattle. It is predicted from live weight (LW), but the prediction can be influenced by a number of factors, e.g., feed and water intake, pregnancy and body condition. The objective of the present study was to develop prediction equations for EBW and carcass weight in lactating dairy cows using LW and other live animal data.

Evaluation of Simmental carcass EPD estimated using live and carcass data1

This study was conducted to compare carcass EPD predicted using yearling live animal data and/or progeny carcass data, and to quantify the association between the carcass phenotype of progeny and the sire EPD. The live data model (L) included scan weight, ultrasound fat thickness, longissimus muscle area, and percentage of intramuscular fat from yearling (369 d of age) Simmental bulls and heifers. The carcass data model (C) included hot carcass weight, fat thickness, longissimus muscle area, and marbling score from Simmental-sired steers and cull heifers (453 d of age). The combined data model (F) included live animal and carcass data as separate but correlated traits. All data and pedigree information on 39,566 animals were obtained from the American Simmental Association, and all EPD were predicted using animal model procedures. The genetic model included fixed effects of contemporary group and a linear covariate for age at measurement, and a random animal genetic effect. The EPD from L had smaller variance and range than those from either C or F. Further, EPD from F had highest average accuracy. Correlations indicated that evaluations from C and F were most similar, and L would significantly (P < 0.05) re-rank sires compared with models including carcass data. Progeny (n = 824) with carcass data collected subsequent to evaluation were used to quantify the association between progeny phenotype and sire EPD using a model including contemporary group, and linear regressions for age at slaughter and the appropriate sire EPD. The regression coefficient was generally improved for sire EPD from L when genetic regression was used to scale EPD to the appropriate carcass trait basis. The EPD from C and F had similar linear associations with progeny phenotype, although EPD from F may be considered optimal because of increased accuracy. These data suggest that carcass EPD based on a combination of live and carcass data predict differences in progeny phenotype at or near theoretical expectation.

Evaluation of Simmental carcass EPD estimated using live and carcass data.

This study was conducted to compare carcass EPD predicted using yearling live animal data and/or progeny carcass data, and to quantify the association between the carcass phenotype of progeny and the sire EPD. The live data model (L) included scan weight, ultrasound fat thickness, longissimus muscle area, and percentage of intramuscular fat from yearling (369 d of age) Simmental bulls and heifers. The carcass data model (C) included hot carcass weight, fat thickness, longissimus muscle area, and marbling score from Simmental-sired steers and cull heifers (453 d of age). The combined data model (F) included live animal and carcass data as separate but correlated traits. All data and pedigree information on 39,566 animals were obtained from the American Simmental Association, and all EPD were predicted using animal model procedures. The genetic model included fixed effects of contemporary group and a linear covariate for age at measurement, and a random animal genetic effect. The EPD from L had smaller variance and range than those from either C or F. Further, EPD from F had highest average accuracy. Correlations indicated that evaluations from C and F were most similar, and L would significantly (P < 0.05) re-rank sires compared with models including carcass data. Progeny (n = 824) with carcass data collected subsequent to evaluation were used to quantify the association between progeny phenotype and sire EPD using a model including contemporary group, and linear regressions for age at slaughter and the appropriate sire EPD. The regression coefficient was generally improved for sire EPD from L when genetic regression was used to scale EPD to the appropriate carcass trait basis. The EPD from C and F had similar linear associations with progeny phenotype, although EPD from F may be considered optimal because of increased accuracy. These data suggest that carcass EPD based on a combination of live and carcass data predict differences in progeny phenotype at or near theoretical expectation.

Genetic parameters for carcass traits and their live animal indicators in Simmental cattle.

The objective of this study was to estimate parameters required for genetic evaluation of Simmental carcass merit using carcass and live animal data. Carcass weight, fat thickness, longissimus muscle area, and marbling score were available from 5,750 steers and 1,504 heifers sired by Simmental bulls. Additionally, yearling ultrasound measurements of fat thickness, longissimus muscle area, and estimated percentage of intramuscular fat were available on Simmental bulls (n = 3,409) and heifers (n = 1,503). An extended pedigree was used to construct the relationship matrix (n = 23,968) linking bulls and heifers with ultrasound data to steers and heifers with carcass data. All data were obtained from the American Simmental Association. No animal had both ultrasound and carcass data. Using an animal model and treating corresponding ultrasound and carcass traits separately, genetic parameters were estimated using restricted maximum likelihood. Heritability estimates for carcass traits were 0.48 +/- 0.06, 0.35 +/- 0.05, 0.46 +/- 0.05, and 0.54 +/- 0.05 for carcass weight, fat thickness, longissimus muscle area, and marbling score, respectively. Heritability estimates for bull (heifer) ultrasound traits were 0.53 +/- 0.07 (0.69 +/- 0.09), 0.37 +/- 0.06 (0.51 +/- 0.09), and 0.47 +/- 0.06 (0.52 +/- 0.09) for fat thickness, longissimus muscle area, and intramuscular fat percentage, respectively. Heritability of weight at scan was 0.47 +/- 0.05. Using a bivariate weight model including scan weight of bulls and heifers with carcass weight of slaughter animals, a genetic correlation of 0.77 +/- 0.10 was obtained. Models for fat thickness, longissimus muscle area, and marbling score were each trivariate, including ultrasound measurements on yearling bulls and heifers, and corresponding carcass traits of slaughter animals. Genetic correlations of carcass fat thickness with bull and heifer ultrasound fat were 0.79 +/- 0.13 and 0.83 +/- 0.12, respectively. Genetic correlations of carcass longissimus muscle area with bull and heifer ultrasound longissimus muscle area were 0.80 +/- 0.11 and 0.54 +/- 0.12, respectively. Genetic correlations of carcass marbling score with bull and heifer ultrasound intramuscular fat percentage were 0.74 +/- 0.11 and 0.69 +/- 0.13, respectively. These results provide the parameter estimates necessary for genetic evaluation of Simmental carcass merit using both data from steer and heifer carcasses, and their ultrasound indicators on yearling bulls and heifers.