Prediction of Carcass Traits of Hair Sheep Lambs Using Body Measurements

Effects of refused melon fruit in Canarana grass ensilage on intake, digestibility, serum biochemistry, performance, carcass characteristics and meat attributes of feedlot lambs

Ensilage of refused fruit with forage is a viable approach to increase resource use in ruminant feed. The objective of this study was to investigate the impact of ensiling refused melon fruit (RMF) with Canarana grass on the intake, apparent digestibility, serum biochemistry, performance, carcass traits, and meat attributes of feedlot lambs. Four distinct silage treatment types were prepared by ensiling RMF at 0 g/kg (control), 70 g/kg, 140 g/kg, and 210 g/kg (as fed) with Canarana grass. Twenty-eight male Santa Inês lambs (7 lambs per treatment), initially weighing 22.3 ± 1.0 kg at 120 days of age, were distributed in a completely randomized design and confined for a total of 96 days, including a 23-day adaptation period and 73 experimental days in a feedlot. The lambs received the treatment-silage in diets as a complete mixture with a roughage: concentrate ratio of 30:70. The inclusion of RMF in Canarana grass ensilage decreased (P < 0.05) the lambs' intake of dry matter, crude protein and metabolisable energy. The inclusion of RMF in ensilage had a quadratic effect (P < 0.05) on the digestibility of non-fibrous carbohydrates. The serum total protein and cholesterol levels decreased (P < 0.05) with the inclusion of RMF in the ensilage, but we observed no effect on the final weight and average daily gain of the lambs. The feed efficiency increased (P < 0.05) by including RMF in the Canarana grass ensilage. The RMF in the ensilage did not influence cold carcass weight and yield. The fat content of the meat decreased (P < 0.05) with the inclusion of RMF in the ensilage. It is recommended the inclusion of up to 210 g/kg of RMF in Canarana grass ensilage to increase feed efficiency and avoid impacts on the performance and carcass attributes of confined lambs.

Using fat thickness and longissimus thoracis traits real-time ultrasound measurements in Black Belly ewe lambs to predict carcass tissue composition through multiresponse multivariate adaptive regression splines algorithm

The main idea of the current study was to estimate carcass tissue composition using fat thickness and longissimus thoracis (LT) traits real-time ultrasound measurements (USM) in Black Belly ewe lambs through multiresponse multivariate adaptive regression splines (MARS) algorithms. Twenty-four hours before slaughter, subcutaneous (SFT) and kidney-fat thickness (KFT), LT depth (LTD), width (LTA, cm) and area (LTMA) were measured in 60 lambs (BW of 26.40 ± 7.01 kg). Information on carcass and non-carcass components was recorded after slaughter. The total carcass muscle (TCM), total carcass bone (TCB), and total carcass fat (TCF) had a low to high correlation (P < 0.01) with BW, cold carcass weight (CCW), and LTD, SFT, KFT, and LDMA. The CCW (%65.58) and SFT (%16.70) were the most effective variables, whilst LTD (%9.57) and LTMA (%8.15) were the lowest variables for determining TCB, TCM, and TCF. The multiresponse MARS algorithm provides an accurate and efficient means of estimating TCF, TCB, and TCM.

Prediction of birth weight using body measurements of local caprine population kids raised in a low-input breeding mode under arid environment

The aim of this study is to establish linear measurements of local goat kids at birth and their factors of variation, as well as their possible correlations with birth weight. Additionally, the study analyses statistical models and barymetric functions to predict birth weight of kids based on their morphometric data. The database includes data on 128 goat kids born to 89 goats and 9 bucks in the experimental goat herd at the El GORDHAB station of IRA. Average BW, withers height (L1), heart girth (L2), rump height (L3), and body length (L4) of all kids were 2.45kg, 32.66cm,30.56cm, 33.41cm, and 31.21cm respectively. Results show that in general, local goat kids are small in size and weight at birth, which varies depending on sex, dam age, and type of birth. Highest and positive correlation coefficient value between birth weight and heart girth were observed (r = 0.95). The coefficient of determination (R2) for heart girth (0.78) was higher than other body measurements in single trait evaluation indicating it as the best trait for the predication of birth weight. The most appropriate combination of body measurements (R2 = 0.82) was observed between height at withers and heart girth for predication of birth weight estimation. Developing a system for recording birth weight based on easily obtainable body measurements could be a useful approach for rural areas. Result join the study objective by conceiving feasible genetic improvement plans for agropastoral herds by establishing individual phenotypes estimation even when the classical animal management does not already allowed.

Prediction models of carcass characteristics from non‑castrated Nellore cattle finished in the feedlot system under tropical conditions

Our objective was to use measures of intake and productive performance to adjust prediction models for the carcass traits of non-castrated Nellore cattle finished in a feedlot. Individual data from 168 non-castrated male Nellore steers finished in feedlot between the years 2016-2021 were used. Descriptive statistical analyzes and Pearson correlation coefficients were performed. The outliers were tested by evaluating the studentized residuals in relation to the values predicted by the equations. Residues that were outside the range of -2.5 to 2.5 were removed. The goodness of fit of the developed equations was evaluated by the coefficients of determination (R2) and root mean square error (RMSE). Models for carcass yield, subcutaneous fat thickness, ribeye area, and shear force were adjusted. Means of 53.5% carcass yield, 4.8 mm subcutaneous fat thickness, 73 cm2 loin eye area, and 8.1 kg shear force were observed. The observed average intakes were 9.9 kg/day of dry matter, 3.3 kg/day of neutral detergent fiber content, 1.5 kg/day of crude protein, and 7.1 kg/day of total digestible nutrients. The average confinement time was 113 days, the average total weight gain was 152.2 kg and the average daily gain was 1.35 kg/day. Intake measures significantly correlated with shear force and subcutaneous fat thickness and ribeye area. Carcass yield was significantly correlated with total weight gain, feedlot time, and hot carcass weight. Measures of nutrient intake, performance, and confinement time can be used as predictors of carcass yield, ribeye area, fat thickness, and shear force of non-castrated Nellore cattle finished in a feedlot. The prediction equations for ribeye area, carcass yield, subcutaneous fat thickness, and shear force showed sufficient precision and accuracy for non-castrated Nellore cattle finished in confinement systems under tropical conditions. All equations can be used with caution to estimate carcass traits of cattle finished in a feedlot using measures of intake and productive performance.

Predicting body weight through biometric measurements in growing hair sheep using data mining and machine learning algorithms

Determination of live weight, which is one of the most important features that determine meat production, is a very important issue for herd management and sustainable livestock. In this context, the necessity of finding alternative methods has emerged, especially in rural conditions, due to the difficulties to be experienced in finding the weighing tool. Especially for conditions with no weighing tool, it has been tried to establish relations between the information obtained from body measurements and live weight. Since these studies will differ from species to species and breed to breed, the need for new studies is extremely high. For this aim, it is to evaluate the body measurement information obtained with the present study using several statistical approaches. To implement this aim, several data mining and machine learning algorithms such as multivariate adaptive regression splines (MARS), classification and regression tree (CART), and support vector machine regression (SVR) algorithms were used for training (70%) and test (30%) sets. To predict final body weight, 280 hair sheep breeds (162 female and 118 male) ranging from 2 months to 3 years were used with different data mining and machine learning approaches. Various goodness-of-fit criteria were used to evaluate the performances of the aforementioned algorithms. Although the MARS and SVR algorithms gave the same and highest results in terms of R2 and r values for both the train and the test sets, the SVR algorithm is one of the methods to be recommended as a result of this study, especially when other goodness-of-fit criteria are evaluated. In conclusion, the usage of SVR algorithms may be a useful tool of machine learning approaches for detecting the hair sheep breed standards and may contribute to increasing the sheep meat quality in Mexico.

Body Composition Estimation in Breeding Ewes Using Live Weight and Body Parameters Utilizing Image Analysis

Farmers are continually looking for new, reliable, objective, and non-invasive methods for evaluating the conditions of ewes. Live weight (LW) and body condition score (BCS) are used by farmers as a basis to determine the condition of the animal. Body composition is an important aspect of monitoring animal condition. The body composition is the amount of fat, muscle, and bone; knowing the amount of each is important because the information can be used for better strategic management interventions. Experiments were conducted to establish the relationship between body composition and body parameters at key life stages (weaning and pre-mating), using measurements automatically determined by an image processing application for 88 Coopworth ewes. Computerized tomography technology was used to determine the body composition. Multivariate linear regression (MLR), artificial neural network (ANN), and regression tree (RT) statistical analysis methods were used to develop a relationship between the body parameters and the body composition. A subset of data was used to validate the predicted model. The results showed a correlation between fat, muscle, and bone determined by CT and the fat, muscle, and bone weight estimated by the live weight and body parameters calculated using the image processing application, with r² values of 0.90 for fat, 0.72 for muscle, and 0.50 for bone using ANN. From these results, farmers can utilize these measurements to enhance nutritional and management practices.

Prediction models of intake and productive performance of non-castrated Nellore cattle finished in the feedlot system under tropical conditions

The objective of this study was to understand and predict the intake and performance of Nellore cattle finished in the feedlot. Individual data from 144 non-castrated male Nellore steers finished in the feedlot between the years 2016 and 2020 were used. Descriptive statistical analyses and Pearson's correlation were performed. The outliers were tested by evaluating the studentized residuals in relation to the values predicted by the equations. Residues that were outside the range of - 2.5 to 2.5 were removed. The goodness of fit of the developed equations was evaluated by the coefficients of determination (r²) and root mean square error (RMSE). The mean dry matter intake (DMI) was 10.2 kg/day, neutral detergent fiber intake (NDFI) was 3.4 kg/day, corresponding to 33.3% of DMI, crude protein intake (CPI) was 1.6 kg/day, and total digestible nutrient intake (TDNI) was 7.1 kg/day. The CPI to ADG ratio was 1.3 kg CPI/kg ADG and the TDNI to CPI ratio was 4.5 kg TDNI/kg CPI. The averages of productive performance were 1.3 kg/day for average daily gain (ADG), 152.6 kg for total weight gain (TWG), and 497.8 kg for final body weight (FBW) in average days in the confinement of 115.7 days. The intake measures correlated significantly with the performance measures, except for carcass yield and days in the feedlot. TWG had a high positive correlation with ADG (r = 0.84), while FBW had a positive correlation (r = 0.86) with hot carcass weight (HCW). Measures of intake, performance, and days in the feedlot can be used as predictors of DMI, FBW, HCW, TWG, and ADG. The prediction equations had satisfactory precision and accuracy for non-castrated Nellore cattle finished in feedlot systems under tropical conditions.

Prediction of weaning weight in Santa Inês lambs using the body volume formula

Weaning weight (WW) is one of the most important information within production systems, as it is a reflection of management during the breastfeeding phase and will influence the performance of animals in subsequent phases. This study aimed to develop and evaluate linear, quadratic, and exponential models to predict WW using the body volume (BV) formula in Santa Inês lambs for meat. Eighty-five lambs at 90 days of age with WW 17.52 ± 3.79 kg and BV 13.29 ± 2.86 dm³ were evaluated. The quality of fit of the models was evaluated using the coefficient of determination (R²), mean squared error (MSE), and root MSE (RMSE). For the external evaluation of the models, an independent dataset from 43 lambs at 90 days of age was used. The first-degree linear model showed the lowest values of MSE (1.02) and RMSE (1.01). In the external evaluation, all models exhibited estimates of mean WW and standard deviation of this weight similar to the external dataset, as well as high values (above 0.89) for the R² of predicted vs. observed data. Concordance correlation coefficient (CCC) analysis also revealed that all models showed accuracy and precision (CCC > 0.90). There was no difference between the models in terms of accuracy (P > 0.05). The comparison in terms of precision indicated that the linear model is more precise than the exponential model and that the quadratic model is as precise as the linear model. The first-degree linear model should be used due to its simplicity of interpretation and ease of estimation.

Prediction of live weight in beef heifers using a body volume formula

ABSTRACT The objective of this study was to develop and evaluate linear, quadratic, and allometric models to predict live weight (LW) using the body volume formula (BV) in crossbred heifers raised in southeastern Mexico. The LW (426.25±117.49kg) and BV (338.05±95.38 dm3) were measured in 360 heifers aged between 3 and 30 months. Linear and non-linear regression were used to construct prediction models. The goodness-of-fit of the models was evaluated using the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), coefficient of determination (R2), mean squared error (MSE), and root MSE (RMSE). In addition, the developed models were evaluated through cross-validation (k-folds). The ability of the fitted models to predict the observed values was evaluated based on the RMSEP, R2, and mean absolute error (MAE). The quadratic model had the lowest values of AIC (2688.39) and BIC (2700.05). On the other hand, the linear model showed the lowest values of MSE (7954.74) and RMSE (89.19), and the highest values of AIC (2709.70) and BIC (2717.51). Despite this, all models presented the same R2 value (0.87). The cross-validation (k-folds) evaluation of fit showed that the quadratic model had better values of MSEP (41.49), R2 (0.85), and MAE (31.95). We recommend the quadratic model to predictive of the crossbred beef heifers' live weight using the body volume as the predictor.

Effects of Dietary Inclusion of Tannin-Rich Sericea Lespedeza Hay on Relationships among Linear Body Measurements, Body Condition Score, Body Mass Indexes, and Performance of Growing Alpine Doelings and Katahdin Ewe Lambs

The objective of this study was to assess the effects of the dietary level of a condensed tannin-rich forage on linear measures, body condition score (BCS), body mass indexes (BMI), and performance and relationships among these variables in growing dairy goats and hair sheep raised for meat. An experiment with a 2 × 3 factorial treatment arrangement was conducted, with two species and three diets. Diets were 25% concentrate and 75% forage, which were alfalfa hay, condensed tannin-containing Sericea lespedeza hay, and a 1:1 mixture of both hay sources. Twenty-four Alpine (ALP) doelings and 24 Katahdin (KAT) ewe lambs were used in the 173-day study, consisting of four measurement periods. Variables included BCS, linear measures, BMI, and performance variables such as average daily gain (ADG) and dry matter intake (DMI, g/day). Linear measures were length from the shoulder point to pin (Pin) and hook (Hook) bones, height at the withers (Wither), circumference from heart girth (Heart), and width at the hook bones (Rump). Different BMI were based on the Wither, Hook, Pin, Heart, and various combinations. Heart, Rump, and all BMI were affected by species, whereas linear measures and BMI based on Wither and the combination of height and length measures were influenced by diet. There were positive (p < 0.05) correlation coefficients (r) between BCS and body weight (BW) and linear measures as well as BMI for both species, and correlations were greater for KAT than for ALP. Body condition score was correlated with BW, ADG, and DMI for KAT (p < 0.05). For ALP, the correlation between BCS and BW (p < 0.015) was much lower than for KAT (0.49 vs. 0.91), and there were only tendencies for relationships between BCS and ADG and DMI (p < 0.10). Body weight and ADG were positively correlated (p < 0.05) with all BMI for both species, and most correlations were greater for KAT than for ALP. Correlations involving BMI based on combinations of two linear measures with BW and ADG were in most instances greater than for BMI calculated from one or three linear measures. For ALP, DMI was related to BMI based on Wither and Pin (r = 0.43), Heart and Hook (r = 0.44), and Heart and Pin (r = 0.61), whereas for KAT, correlations were similar (0.72−0.75) for each of the four BMI based on two linear measures (i.e., Wither and Hook, Wither and Pin, Heart and Hook, and Heart and Pin). Therefore, it appears that each of these four BMI, preferably based on Heart and length, could be appropriate for better livestock management over BCS and in predicting animal performance.

Fortification of diets with omega-3 long-chain polyunsaturated fatty acids enhances feedlot performance, intramuscular fat content, fat melting point, and carcass characteristics of Tattykeel Australian White MARGRA lambs

Meat eating quality indices such as intramuscular fat content (IMF) and fat melting point (FMP) of the Longissimus thoracis et lumborum muscle and the feedlot performance, carcass traits, and commercial wholesale cuts of lot-fed Tattykeel Australian White (TAW) MARGRA lambs as a result of dietary fortification of the diet with omega-3 long-chain polyunsaturated fatty acids (n-3 LC-PUFA) were evaluated. A total of 75 TAW MARGRA lambs at 6 months of age with an average liveweight of 30 ± 1.2 kg were used. The lambs were randomly allocated to the following three dietary treatments of 25 lambs each in a 47-day feeding trial using a completely randomized experimental design: (1) control diet of hay plus pellets without omega-3 oil, (2) hay plus commercial whole grain pellets (MSM) without omega-3 oil, and (3) hay plus pellets fortified with omega-3 oil. It was hypothesized that dietary supplementation with omega-3 fortified pellets will improve feedlot performance, meat-eating quality indices of IMF, FMP, and carcass characteristics. Lot-fed lambs on the MSM whole grain had the highest feed intake of 1.69 kg/day, followed by the control at 1.57 kg/day and the lowest in the omega-3 diet at 1.01 kg/day (p = 0.0001). However, the omega-3 diet had the highest average daily gain of 230 g/head/day (p = 0.0001), indicating the greatest feed efficiency since it had the best growth response with minimal feed intake. Post-slaughter evaluation of the Longissimus thoracis et lumborum muscle revealed significant treatment variations in IMF (p = 0.0001), FMP (p = 0.0001), pH (p = 0.0380), and wholesale French rack primal cut (p = 0.0001). Strong correlations (p < 0.05) between liveweight, temperature, pH, FMP, and IMF were observed. Similarly, significant correlations between carcass characteristics of total saleable meat yield, lean trim, fat trims, bones, and leg shank were evident (p < 0.05). However, there were no treatment differences in the final liveweight, GR fat depth, hot standard carcass weight, or dressing percentage. The findings indicate that feedlot performance, meat-eating quality traits such as IMF and FMP, and commercial wholesale French rack cuts can be further improved during feedlot finishing of TAW MARGRA lambs through dietary supplementation with omega-3 oils, and hence the tested hypothesis of improved meat quality attributes is partially confirmed.

Prediction of live weight in growing hair sheep using the body volume formula

ABSTRACT Due to the conditions in which traditional sheep production systems operate, the evaluation of animal growth from live weight (LW) is limited by the high cost of the livestock scale as well as the sophisticated maintenance required. In this scenario, in recent years, biometric measurements have been investigated as an accurate indirect method to predict the LW of farm animals. Therefore, the present study was undertaken to examine different models for predicting the body weight of growing lambs using the body volume (BV) formula. Body volume, heart girth (HG) and body length (BL) data of 290 lambs aged between two and eight months were recorded. Body volume was calculated from HG and BL data using a formula that calculates the volume of a cylinder. The estimation of LW from the BV formula was achieved through regression equations using three mathematical models (linear, quadratic and exponential). The mean values of LW, HG, BL and BV of the lambs were 29.12±12.04kg, 70.00±11.69cm, 38.40±6.43cm and 23.93±9.90dm3, respectively. The correlation coefficient between LW and BV was r = 0.96 (P<0.001). The quadratic model showed the highest coefficient of determination (0.93) and the lowest prediction error (3.29kg). Under the experimental conditions adopted in this study, it is possible to predict the live weight of growing lambs using the body volume formula.

Estimation of Carcass Tissue Composition from the Neck and Shoulder Composition in Growing Blackbelly Male Lambs

This study was designed to develop predictive equations estimating carcass tissue composition in growing Blackbelly male lambs using as predictor variables for tissue composition of wholesale cuts of low economic value (i.e., neck and shoulder). For that, 40 lambs with 29.9 ± 3.18 kg of body weight were slaughtered and then the left half carcasses were weighed and divided in wholesale cuts, which were dissected to record weights of fat, muscle, and bone from leg, loin, neck, rib, and shoulder. Total weights of muscle (CM), bone (CB) and fat (CF) in carcass were recorded by adding the weights of each tissue from cuts. The CM, CF and CB positively correlated (p < 0.05; 0.36 ≤ r ≤ 0.86), from moderate to high, with most of the shoulder tissue components, but it was less evident (p ≤ 0.05; 0.32≤ r ≤0.63) with the neck tissue composition. In fact, CM did not correlate with neck fat and bone weights. Final models explained (p < 0.01) 94, 92 and 88% of the variation observed for CM, CF and CB, respectively. Overall, results showed that prediction of carcass composition from shoulder (shoulder) tissue composition is a viable option over the more accurate method of analyzing the whole carcass.

Use of spineless cactus associated with legume hay in the feedlot-finishing of lambs in semi-arid regions

The objective of this study were to examine the effects of diets containing spineless cactus associated with hays of different legume species [gliricidia (Gliricidia sepium), “catingueira” (Caesalpinia bracteosa), “sabiá” (Mimosa caesalpiniifolia Benth) and “catanduva” (Piptadenia moniliformis Benth)] on the intake, digestibility, performance and carcass traits of lambs. Twenty-four ½ Santa Inês × ½ Soinga lambs with an average body weight of 21.4 ± 2.53 kg were distributed into four treatments in a completely randomized design. Treatments consisted of diets formulated with the association of spineless cactus (Opuntia ficus-indica Mill) and hay of four legume species, namely, “catanduva”, “sabiá” “catingueira” and gliricidia. The lowest intakes (P<0.05) of dry matter (DM), organic matter (OM), neutral detergent fiber (NDF) and total carbohydrates occurred in the animals that received the diet containing catingueira hay. However, there were no diet effects (P>0.05) on the intakes of crude protein (CP), ether extract and non-fibrous carbohydrates. The diets also did not change (P>0.05) the weight gain (0.197 kg/day) or final weight (33.18 kg) of the lambs or the apparent digestibility coefficients of DM, OM, CP and NDF. Consequently, the parameters of live weight at slaughter (34.10 kg), hot carcass weight (14.81 kg), cold carcass weight (14.66 kg), hot carcass yield (45.60%) and cold carcass yield (45.07%) exhibited the no response to treatment. In addition to these variables, the diets also did not influence subcutaneous fat thickness (2.54 mm), longissimus muscle area (13.34 cm²), morphometric measurements of the carcass, or the proportions of muscle and fat. Therefore, legume hays associated with spineless cactus can be used to feed ½ Santa Inês × ½ Soinga lambs in the feedlot, as this strategy provides heavy animals at the time of slaughter and carcasses with desirable degrees of muscularity and adiposity.

Prediction of Carcass Traits of Santa Inês Lambs Finished in Tropical Pastures through Biometric Measurements

The aim of this study was to predict carcass traits of Santa Inês lambs finished in tropical pastures by using biometric measurements. Data originated from two experiments involving 56 lambs (32 in experiment I and 24 in experiment II). In both experiments, the sheep were finished in that were finished in pastures of Panicum maximum and Brachiaria brizantha, experiment I being conducted in the rainy season and experiment II in the dry season. The following biometric measurements were recorded before slaughter: body length (BL), withers height (WH), rump height (RH), thorax width (TW), rump width (RW), chest width (CW), heart girth (HG), thigh circumference (TC), rump circumference (RC) and leg length (LL), in addition to live weight at slaughter (SW). After slaughter, hot carcass weight (HCW), cold carcass weight (CCW) and the weights of primal cuts (shoulder, neck, loin, leg and rib) were recorded. In the equations generated to predict SW, HCW and CCW, R² ranged from 0.58 to 0.91 and the measurements of WH, TC, CW, HG and RW were the most relevant. In the equations developed to predict the weight of primal cuts, in turn, R² ranged from 0.26 to 0.99. In these models, SW, BL, CW, TC, LL and HG explained most of the variation in the weight of primal cuts. Biometric measurements can be used to accurately and precisely predict HCW, CCW and the weight of primal cuts from the carcass of Santa Inês sheep finished in tropical pastures, since the equations presented R² and correlation coefficient and agreement above 0.8.