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Context: The planting and use of leucaena (Leucaena leucocephala) to fatten cattle is both practical and profitable for smallholder farmers in West Nusa Tenggara, Indonesia. Currently smallholder farmers feed leucaena as the primary component of a cattle fattening diet. However, the high protein content in leucaena could be more effectively used if combined with a fermentable energy source, such as cassava (Manihot utilissima). Aim: An experiment was conducted to determine the ratio of leucaena to cassava corresponding to largest average daily gain and most efficient feed conversion for gain. Methods: Thirty growing male Bali cattle (Bos javanicus) ~18 months of age with an initial live weight of 164 ± 1.8 kg (mean ± s.e.) were allocated to one of six experimental treatments in a randomised block design. Bulls were held in individual stalls and had access to experimental diets and water ad libitum. The diets were 20% rice straw + 80% leucaena hay (A), 20% rice straw + 65% leucaena hay + 15% cassava meal (B), 20% rice straw + 50% leucaena hay + 30% cassava meal (C), 20% rice straw + 35% leucaena hay + 45% cassava meal (D), 20% rice straw + 20% leucaena hay + 60% cassava meal (E) and 20% rice straw + 5% leucaena hay + 75% cassava meal (F). A mineral mix was provided at 1% DM of total diet and urea was added to the cassava meal at 2% DM. In consideration of animal welfare concerns, the trial was concluded on Day 77 due to observations indicating that bulls receiving the highest level of cassava (F) were experiencing significant weight loss. Key results: The optimum level of inclusion of cassava was 29.5% (based on the quadratic response curve) but there was little difference in average daily gain up to 45% inclusion. Feeding a high level of cassava meal (more than 45% of diet) reduced feed intake, average daily gain and income over feed cost. Conclusion: Cassava meal can be successfully and profitably incorporated into leucaena-based rations of Bali bulls for fattening. Implications: Formulating rations with cassava meal and leucaena can be economically beneficial in cattle fattening systems. Supplementing Bali cattle rations in leucaena-based smallholdings with locally available cassava as an energy source, provides an opportunity to increase cattle live weight gain, extend the utilisation of leucaena and increase farmer profitability. Weight gain and profitability were maximised up to 45% cassava, but higher levels reduced feed intake, average daily gain and income over feed costs. Feeding cassava meal to leucaena-based diets is an important strategy to preserve leucaena as well as to increase profitability and meat production nationally. [ABSTRACT FROM AUTHOR]

Simple Summary: Calves should be regularly weighed to monitor their growth, which can be an indication of their health and welfare. Pre-weaned calves are particularly vulnerable to health problems as their immune system is still developing. In addition, knowing the calf's weight can help to provide a more balanced diet and to be more accurate when administering medication. However, there are still many farmers who do not have a scale on their farm or who have limitations in weighing their calves. Therefore, we developed a model using morphometric traits to estimate the weight of Holstein–Friesian pre-weaned calves without the need for a scale, which should be easy to use in most circumstances. Our model used the measurement of heart girth with a simple tape measure and was able to predict the weight of the calf with a mean difference of −1.4 ± 3.24 kg from the actual weight. We did not find any differences between females and males, but we did find differences between farms, which could be due to different genetic lines associated with farm breeding protocols. In addition, a web application was developed to make it easy for farmers to use the developed model. This avoids the use of calibrated weight bands, which are usually calibrated for a wider age range or for beef breeds. Regularly weighing calves helps to assess the efficiency of the rearing period and contributes to animal welfare by allowing more precise feeding and medication application in dairy farming, but many farmers do not weigh their calves regularly. Improving the feasibility of this process is, therefore, important. The use of morphometric measurements has been used to estimate the weight of cattle. However, many studies have focused on adult animals or used a wide age range. As calves experience allometric tissue growth, specific models for certain ranges might be more accurate. Therefore, the aim of this work was to develop a weight estimation model specific for pre-weaned Holstein–Friesian calves using morphometric measurements and to compare the model with another equation previously validated for the same breed with young and adult animals. From four dairy farms, 237 measurements of body weight, heart girth, abdominal girth, hip height, withers height, and body length were taken from Holstein–Friesian male and female calves. Linear and non-linear regression analysis was used to test the relationship between body weight and morphometric measurements, with age, sex, and farm as possible explanatory variables. Selected models were compared with goodness of fit and agreement tests. The final model was able to accurately predict body weight (R2 = 0.96) with a mean difference of −1.4 ± 3.24 kg. Differences in the relationship between body weight and morphometric traits were observed between farms, but not between males and females. The genetics of the animal population at farm level may be responsible for this variability and further studies are needed to understand this variability and improve weight prediction models. The developed model was able to perform better in the agreement tests than the previously validated model for Holstein–Friesian animals, suggesting that different equations should be used depending on the growth phase the animal is in. In addition, a web application has been developed to facilitate the use of the developed model by farmers. This avoids the use of calibrated weight bands, which are usually calibrated for a broader age range or for beef cattle. [ABSTRACT FROM AUTHOR]

The weight of livestock is a crucial metric for evaluating management efficacy, informing policy decisions, and determining the market value of animals. In certain scenarios, conventional methods such as physical weighing and measurement calculations can prove challenging, including the absence of livestock health records or weighing equipment. This research aims to develop a predictive model for estimating the live weight of cattle through visual assessments and metadata, including age and pixel count, utilizing a combination of convolutional neural network (CNN) and artificial neural network (ANN) methodologies. A total of 223 data were obtained from a local farm before augmentation. The model's predictive capability was successfully demonstrated, with its performance quantified by an average mean absolute percentage error (MAPE) of 10% on test data. This study demonstrates that through the combination of CNN and ANN, as well as optimal parameter tuning, efficient prediction of cattle weight can be achieved. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to identify suitable polynomial regression for modeling the average growth trajectory and to estimate the relative development of the rib eye area, scrotal circumference, and morphometric measurements of Guzerat young bulls. Methods: A total of 45 recently weaned males, aged 325.8±28.0 days and weighing 219.9±38.05 kg, were evaluated. The animals were kept on Brachiaria brizantha pastures, received multiple supplementations, and were managed under uniform conditions for 294 days, with evaluations conducted every 56 days. The average growth trajectory was adjusted using ordinary polynomials, Legendre polynomials, and quadratic B-splines. The coefficient of determination, mean absolute deviation, mean square error, the value of the restricted likelihood function, Akaike information criteria, and consistent Akaike information criteria were applied to assess the quality of the fits. For the study of allometric growth, the power model was applied. Results: Ordinary polynomial and Legendre polynomial models of the fifth order provided the best fits. B-splines yielded the best fits in comparing models with the same number of parameters. Based on the restricted likelihood function, Akaike's information criterion, and consistent Akaike's information criterion, the B-splines model with six intervals described the growth trajectory of evaluated animals more smoothly and consistently. In the study of allometric growth, the evaluated traits exhibited negative heterogeneity (b<1) relative to the animals' weight (p<0.01), indicating the precocity of Guzerat cattle for weight gain on pasture. Conclusion: Complementary studies of growth trajectory and allometry can help identify when an animal's weight changes and thus assist in decision-making regarding management practices, nutritional requirements, and genetic selection strategies to optimize growth and animal performance. [ABSTRACT FROM AUTHOR]

Warman AT, Panjono, Fadhilah GT, Atmoko BA, Bintara S, Widi TSM, Baliarti E, Jannah ZN. 2024. The difference between Bali cattle and Limousine-Bali (Limbal) crossed cattle concerning their qualitative characteristics in Lombok Tengah District, Indonesia. Nusantara Bioscience 16: 104-110. Crossbreeding is a potential approach that farmers might employ to improve the productivity of Bali cattle (Bos javanicus d'Alton, 1823). Exotic cattle breeds, such as Limousin cattle (Bos taurus Linnaeus, 1758), are frequently used for crossbreeding. This study aimed to determine the qualitative characteristic differences between Bali cattle and Limousin-Bali (Limbal) crossed cattle in the Lombok Tengah District of West Nusa Tenggara Province, Indonesia. Data sampling was conducted in 2 subdistricts, namely Pringgarata and Jonggat Sub-districts. The research used 80 adult female cattle, consisting of 40 Bali and 40 Limbal cattle. The average age of cattle was 4.24 years, and the average body weight was 236.66 kg for Bali cattle and 367.88 kg for Limbal cattle. Local farmers kept cattle using the same intensive methods. Phenotypic characterization included color and physical characteristics according to the guidelines provided by the Food and Agriculture Organization (FAO) and the Indonesian Institute of Sciences (LIPI). The Data were presented descriptively, and differences across variables were assessed using the chi-square method. The research indicated no significant difference in tail-tip color (P >0.05). The body and eyelid color showed a significant difference (P <0.05). Furthermore, legs color, buttocks color, dorsal line color, vulva color, muzzle color, horn color, face profile, backline profile, horn orientation, and ear orientation differed significantly (P <0.01). Thus, it can be concluded that crossbreeding caused changes in phenotypic characteristics in the next generation. Therefore, phenotypic characterization in the next generation of these crossbreeds must be conducted, and selection criteria must be established to achieve sustainable breeding goals. [ABSTRACT FROM AUTHOR]

Context: Delaying sowing date of maize allows producers to achieve stabilised yield. Delays in the sowing date generate changes in the grain structure, which may affect the ruminal degradability of the maize starch. Aims: The objective of this study was to evaluate the effects of maize sowing date on ruminal starch degradability, and how it is related with grain physical characteristics and source:sink ratio during the grain-filling period. Methods: To study the effects of maize sowing date on grain physical characteristics and on starch in situ effective degradability (ED; 6%/h passage rate from the rumen), eight treatments were defined on the basis of eight different sowing dates in Argentina of a commercial semi-dentate maize hybrid (Dekalb 7210 VT3P), as follows: Treatment 1 (13 October), Treatments 2, 3, and 4 (4, 17 and 26 November respectively), Treatments 5, 6 and 7 (3, 15 and 28 December, respectively) and Treatment 8 (5 January). For each sowing date, three plots of maize were sown in a complete randomised-block design and harvested at grain physiological maturity. Key results: Starch ED of ground (2.0-mm) grains ranged from 631 to 801 g/kg and showed a 'J'-shape response, being lower for the sowing dates from 17 November to 3 December and highest on the sowing date of 5 January. Grain density increased until the sowing date of 17 November, and then decreased. Grain vitreousness and hardness were initially not affected, but started to decline after the sowing date of 17 November. Grain test weight was not affected until the sowing date of 15 December, when it started to decline. The source:sink ratio during the grain-filling period decreased as the sowing date was delayed. Effective starch degradability was negatively correlated with the physical characteristics evaluated and the source:sink ratio. Conclusions: Delaying sowing date affected the maize source:sink ratio during the grain-filling period; this was associated with changes in grain physical characteristics and with an increase in ruminal starch degradability. Implications: Delaying sowing date increases dry matter (DM) and starch effective degradability, and therefore could affect cattle weight gain and feed conversion efficiency. The effects of delaying the sowing date of maize on ruminal starch degradability is presented. The information generated in this work complements and extends the knowledge of previous studies that focused on the effects of corn genotype on ruminal starch degradation. As corn sowing date is delayed, ruminal starch degradability shows a 'J'-shape response. Ruminal starch degradability is negatively correlated with grain physical characteristics and with the source:sink ratio. [ABSTRACT FROM AUTHOR]

The purpose of this experiment was to study the effects of bacterial enzyme additives on the growth performance, nutrient apparent digestibility, rumen fermentation parameters, and economic benefits of Liaoning Heishan cattle. Thirty-six Liaoning Heishan cattle with an average weight of about 273 kg were randomly divided into three groups with four replicates in each group and three cattle in each replicate. The control group was fed with basal diet, the experimental group A was fed with basal diet + 5 g/(head·d) of bacterial enzyme additive, and the experimental group B was fed with basal diet + 10 g/(head·d) of bacterial enzyme additive. The pre-test period was seven days, and the formal test period was 60 days. The results showed that compared with the control group, the final weight and average daily gain of the experimental group B increased significantly ( P<0.05), the feed-to-weight ratio decreased significantly ( P<0.05), and the incidence rate decreased by 63.04%. The incidence rate of the experimental group A decreased by 27.52% ( P>0.05). The apparent digestibility of crude protein, acid detergent fiber, and neutral detergent fiber in the experimental group B was significantly higher than that in control group ( P<0.05). Ammonia nitrogen and the ratio of acetic acid to propionic acid in rumen fluid of the experimental group B were significantly lower than those of the control group ( P<0.05), while the concentrations of propionic acid and microbial protein were significantly higher than those of the control group ( P<0.05). Compared with the control group, the daily net profit of each cow in the experimental group A increased by 1.10 yuan, and the experimental group B increased by 7.27 yuan. The study indicates that adding 10 g/(head·d) microbial enzyme additive to the basal diet can effectively improve the growth performance, nutrient apparent digestibility, improve the rumen fermentation function, reduce the occurrence of diseases, and improve the economic benefits of Liaoning Heishan cattle. [ABSTRACT FROM AUTHOR]

Genome-wide association study (GWAS) was used to detect candidate genes affecting economic traits in livestock. GWAS can detect single nucleotide polymorphisms (SNPs) in all chromosome regions. This study aimed to determine the genetic markers for body weight by GWAS in native cattle breeds of Indonesia. The Illumina Bovine 50K BeadChip was used to determine the candidate genes in three mixed-sex Indonesian cattle breeds of Bali (16 animals), Madura (16 animals), and Ongole grade (13 animals). All animals were raised at the Pasuruan Regency, East Java, Indonesia breeding station. The GWAS was performed in pooled sample of animals (45 animals) with the general linear model (GLM) method using SNP markers with minimum allele frequency (MAF) values more than 0.05 by TASSEL 5.0. software. Therefore, the body weight of cattle at 1 to 3 years of age was collected for each animal for computing Manhattan plot graphics. This research found that SUGT1, SF3A3, and DSCAM genes were detected as potential genetic markers for body weight in cattle breeds of Indonesia. The SUGT1 and DSCAM genes were monomorphic in Bali cattle (Bos javanicus). In addition, both genes were significantly associated (P<0.05) with the body weight of Ongole-grade cattle (Bos indicus) at three years of age. However, the SF3A3 gene was significantly (P<0.05) associated with body weight of Madura cattle (Bos indicus) at 2 and 3 years of age. In conclusion, the GWAS of pool animals reveals three candidate genes significantly associated with body weight in many cattle breeds of Indonesia. Further study to detect SNPs in candidate genes with sequencing method is essential to apply these findings practically. [ABSTRACT FROM AUTHOR]

We used a class of stochastic differential equations (SDE) to model the evolution of cattle weight that, by an appropriate transformation of the weight, resulted in a variant of the Ornstein-Uhlenbeck model. In previous works, we have dealt with estimation, prediction, and optimization issues for this class of models. However, to incorporate individual characteristics of the animals, the average transformed size at maturity parameter α and/or the growth parameter β may vary randomly from animal to animal, which results in SDE mixed models. Obtaining a closed-form expression for the likelihood function to apply the maximum likelihood estimation method is a difficult, sometimes impossible, task. We compared the known Laplace approximation method with the delta method to approximate the integrals involved in the likelihood function. These approaches were adapted to allow the estimation of the parameters even when the requirement of most existing methods, namely having the same age vector of observations for all trajectories, fails, as it did in our real data example. Simulation studies were also performed to assess the performance of these approximation methods. The results show that the approximation methods under study are a very good alternative for the estimation of SDE mixed models. [ABSTRACT FROM AUTHOR]

Cystic echinococcosis is caused by the zoonotic tapeworm Echinococcus granulosus. There has been ongoing controversy over whether it causes weight loss in cattle. Recently implemented recording of comorbidities at processors has provided opportunity to investigate this effect. Using prevalence-based observational data from 1,648,049 adult cattle processed in seven states and territories in Australia (2019–2022), we explored associations between carcase weight, hydatid cysts, comorbidities, sex, age, and region. Linear mixed-effect regression models estimated the effect of cystic echinococcosis on carcase weight, guided by directed acyclic graphs to reduce bias. The highest, previously unreported, prevalence was in the southeast Queensland region. The estimated effect of cystic echinococcosis cysts on carcase weight ranged from a gain of 0.32 kg/carcase (standard error [se] 0.58 kg; two-tooth 2022) to a loss of −5.45 kg/carcase (se 0.63 kg; six-tooth 2019) with most point estimates (11/16) between 0 and −2.5 kg across all cattle grouped by year and dentition. This effect size would be practically undetectable in live cattle which is an important finding; cattle producers are unlikely to observe increased productivity through weight gain from cystic echinococcosis prevention in cattle, and awareness to strengthen prevention in domestic dogs around cattle properties to reduce human risk remains a public health focus. [ABSTRACT FROM AUTHOR]

Simple Summary: The enhanced selection index proposed in the study incorporates new health disorder traits related to udder, claw, and reproduction in addition to the current selection traits. Genetic parameters and breeding values for the traits were evaluated using linear animal models and single-step genomic best linear unbiased prediction (ssGBLUP) methods. The economic weights (EWs) for the new health disorders were calculated using the enhanced bioeconomic model implemented in the computer programme EWDC (i.e., economic weights for dairy cattle), which is versatile and can be applied for various breeds, farm management, and conditions. The use of the enhanced selection index mostly allowed favourable selection progress in terms of the new and current breeding objective traits and could be acceptable for local breeders. The aim of this study was to construct an enhanced selection index using the genomic and economic parameters of new health disorders and current production and functional traits. Genomic evaluation for the incidence of clinical mastitis (CM), three claw disease traits, retained placenta (RET), metritis (MET), and cystic ovaries (CYS) was performed using linear animal models based on producer-recorded data. Good correlations among the health disorders were found, and their heritability estimates did not exceed 7%. Economic weights (EWs) for the health disorders were EUR −132.10 for CM, EUR −128.87 for overall claw diseases, EUR −52.10 for RET, EUR −80.48 for MET, and EUR −16.16 for CYS. These EWs indicate changes in the present value of the annual profit per cow when increasing the incidence of the traits by one case per cow year. Selection using the enhanced index resulted in favourable responses for most of the new health disorders (e.g., −0.001 and −0.006 cases of RET and MET per cow year, respectively), and also in the current breeding objective traits (+49 kg of milk, −0.02% of calf losses). An index contribution of 7% for the new health disorders was assessed as acceptable for the breeders. [ABSTRACT FROM AUTHOR]

In this study, the calcaneus and talus bones of 20 male and female adult Simmental and Angus cattle were used. The age and sex of these animals were recorded before slaughter, and carcass weights were taken after slaughter. Calcaneus and talus morphometric measurements were used to obtain multipliers that allow the estimation of the carcass weight. These multipliers were found to be mean values of 3.346 and 4.642, respectively. Thus, multipliers were obtained that can be used in the evaluation of chronological differences in archaeological cattle size and consequently carcass weight. LSM (Least Square Means) analysis of calcaneus and talus GL values revealed the effect of sex but not of breed. Proportional factors were obtained for calcaneus and talus pairings and associated bone size (GL) estimates. [ABSTRACT FROM AUTHOR]

The economy of livestock production largely depends upon the early growth and reproductive efficiency of the animals. This review was conducted to generate the database about the early growth and reproductive traits of crossbred cattle such as birth weight (BW), age at first service (AFS) and age at first calving (AFC) under Ethiopian conditions. The effort was made to collect and discuss all the published materials in the required areas in order to provide piece of information pertaining to early growth and reproductive traits of crossbred dairy cattle. In order to achieve the best early growth and reproductive performance in dairy animals, it is concluded that management system improvement, including effective heat detection and timely insemination, better health management, genetic improvement of crossbreeding and supplementation of good quality and quantity feed resources, is necessary. [ABSTRACT FROM AUTHOR]

Both the measurement age of a longitudinal trait and the common pre‐sampling procedures used in beef cattle herds may affect the identification of a functional candidate gene (FCG) that is potentially associated with a trait. To identify the FCG that takes part in the genetic control of body weight at five different ages in a beef cattle population with and without sequential sampling, the animals were weighed at different measurement events, around 330, 385, 440, 495 and 550 days old. Genetic parameters were estimated for body weight at each age using a single trait (STM) and a random regression model (RRM). In addition, two different databases were used to estimate the genetic parameters: the first (DB100) was formed by all animals that were weighed in the five measurement events, and the second (DB70) has records of the same population, considering that 70% of the heaviest animals were selected after each measurement event. For DB100, genome‐wide association studies (GWAS) were performed with 21,667 SNP markers to identify genomic windows that explained at least 1% of the genetic variance. Additionally, prioritization analyses were performed and FCGs were selected. We associated seven different FCGs with body weight at different ages. Among them, the gene DUSP10 was suggested as FCG in all five ages evaluated. Genetic parameters estimated for body weight using DB100 were similar when STM and RRM were applied. However, when DB70 was used as phenotypic data, there were differences between the two models. When the STM was applied, there were differences between the genetic parameters estimated for body weight when DB100 or DB70 were used as sources of phenotypes, but not for the estimates obtained with RRM. The importance of each gene for animal growth can change at different ages, and different genes may be more relevant to body weight at each different growth stage for beef cattle. Besides, sequential sampling can affect the GWAS results of a longitudinal trait. The age of the animal when a longitudinal trait is measured and pre‐sampling can also contribute to inconsistencies in GWAS results for body weight in beef cattle, depending on the time when that data were collected, and consequently on the identification of FCG between studies, even when models that consider a covariance structure are used. [ABSTRACT FROM AUTHOR]

We investigate the impact of different data modalities for cattle weight estimation. For this purpose, we collect and present our own cattle dataset representing the data modalities: RGB, depth, combined RGB and depth, segmentation, and combined segmentation and depth information. We explore a recent vision-transformer-based zero-shot model proposed by Meta AI Research for producing the segmentation data modality and for extracting the cattle-only region from the images. For experimental analysis, we consider three baseline deep learning models. The objective is to assess how the integration of diverse data sources influences the accuracy and robustness of the deep learning models considering four different performance metrics: mean absolute error (MAE), root mean squared error (RMSE), mean absolute percentage error (MAPE), and R-squared ( R 2 ). We explore the synergies and challenges associated with each modality and their combined use in enhancing the precision of cattle weight prediction. Through comprehensive experimentation and evaluation, we aim to provide insights into the effectiveness of different data modalities in improving the performance of established deep learning models, facilitating informed decision-making for precision livestock management systems. [ABSTRACT FROM AUTHOR]

This study was designed to evaluate some reproductive indices of the White Fulani Indigenous cattle bulls in Ilorin, Kwara State, Nigeria. Forty apparently healthy bulls of age one to five years were used for this study. The parameters studied included scrotal circumference, scrotal length, chest girth and body weight. These parameters were taken using measuring tapes. The result obtained showed that there was significant (p < 0.05) differences in the scrotal circumference and scrotal length between bulls in the age groups 1, 2 and 3 years old while 4 and 5 years old showed no significant (p > 0.05) difference. There was significant difference (p < 0.05) in the chest girth and body weight of bulls in all the five age groups (1 - 5 years old). This suggests that the age of puberty in the indigenous white Fulani bulls is three years. Veterinarians and farmers can leverage on these reproductive indices (scrotal circumference, scrotal length, chest girth, and body weight) to select bulls with superior breeding potential, ultimately improving herd health and productivity. [ABSTRACT FROM AUTHOR]

In early work we have studied a class of stochastic differential equation (SDE) models, for which the Gompertz and the Bertalanffy-Richards stochastic models are particular cases, to describe individual growth in random environments, and applied it to model cattle weight evolution using real data. We have started to work on these type of models considering that the model parameters are fixed, i.e. the same for all the animals. Aiming to incorporate variability among individuals, we consider that the model parameters can be random variables, resulting in SDE mixed models. In additon, here we consider SDE mixed models, allowing the parameters to be random and propose to incorporate each animal's genetic characteristics considering the transformed animal's weight at maturity to be a function of its genetic values. The main objective is to extend the SDE mixed model to the more realistic case where the individual's genetic value becomes an important component in the estimated growth curve. For the estimation of the model parameters we have used maximum likelihood estimation theory. Estimates and asymptotic confidence intervals of the parameters are presented. A comparison with SDE non-mixed model and SDE mixed model without the inclusion of genetic characteristics is shown with the conclusion that the incorporation of some genetic characteristics in the model parameters improves the estimation of the animal's growth curve. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to develop a method for predicting the body weight of beef cattle using meta-analysis based on digital image processing. Materials and Methods: The meta-analysis process commenced by collecting studies with the keywords "beef cattle," "correlation," "digital image," and "body weight" from Google Scholar and Science Direct. The obtained studies were reviewed papers based on their titles, abstracts, and content, and then categorized by authors, year, country, sample size, and correlation coefficient. A digital image of body measurements used included wither and hip height, chest depth, heart girth, body length, and top view. The statistical analysis was conducted by calculating effect sizes using the correlation coefficient and sample sizes. Results: The results of the meta-analysis, based on 3,017 cattle from 13 selected studies, showed the highest and lowest correlation coefficients for the top view variable and hip height. Based on cattle breed, significant differences (p < 0.05) were observed in the wither height variable with correlation coefficients of 0.94, 0.79, and 0.66 for Hanwoo, Holstein, and Simmental, respectively. Based on sex, significant differences (p < 0.05) were seen in the wither height variable, with correlation coefficients of 0.73 for males and 0.90 for females, while for hip height, the values were 0.70 and 0.87, respectively. Conclusion: In conclusion, to achieve the best accuracy in predicting the body weight of beef cattle based on a digital image, the top view variable can be used. However, for ease of field experimentation, body length or chest depth can also be used while taking breed and sex categories into the model. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to assess the effect of Thai native cattle grazing in the lowland or mountain forest on carcass characteristics, meat quality, sensory palatability, and chemical composition. Methods: Twelve male Thai native cattle with an average weight of 110±10 kg are allowed to be grazing in the lowland or Phu Phan mountain forest during the rainy season in northeastern Thailand. Results: The carcass characteristics, meat pH, and meat color were unaffected by treatment (p>0.05). The boiling loss was lower in the cattle grazing on the mountain forest (p = 0.027). The cattle grazing in the mountain forest had increased shear force (p = 0.039), tenderness (p = 0.011), and flavor intensity (p = 0.003). The protein and fat were higher (p<0.001 and p = 0.035, respectively) in cattle grazing in the mountain forest. The different grazing systems of the cattle had no effect (p>0.05) fatty acids in meat, except for capric acid (C10:0) and lauric acid (C12:0), which were higher (p = 0.046 and p = 0.049, respectively) when the cattle were grazing in the mountain forest. The different grazing systems did not influence (p>0.05) the unsaturated fatty acids in meat. Conclusion: Thai native cattle grazing in the Phu Phan mountain forest in the rainy season improves meat quality, sensory evaluation, and chemical composition. [ABSTRACT FROM AUTHOR]

While genetic markers related to meat production traits have been identified in many other cattle breeds, research on weight in Hanwoo cattle (Korean native cattle) is still insufficient. In this study, we performed expression quantitative trait loci (eQTL) analysis and differential gene expression analysis to detect candidate genes influencing the weight characteristics of 32 castrated Hanwoo cattle across 22 tissues and, we identified variants that affect gene expression levels. In total, we identified a total of 3,298 differentially expressed genes, among which we discovered key genes such as UBD, RGS2, FASN, and SCD that have functions related to adipogenesis, body weight, obesity, and lipid metabolism. Gene-set enrichment analysis revealed that candidate genes in adipose tissue are involved in metabolic pathways linked to obesity-related traits, adipose metabolism, and lipid metabolism. Additionally, we found that decreased expression of TRIM31 contributes to weight gain which can be explained by the associated candidate cis-eQTL genotypes for TRIM31 and their effect on differential gene expression between the lower and higher weight groups. Our findings revealed candidate genes associated with the weight of Hanwoo cattle and perhaps can provide comprehensive insights into the association of weight with various tissues beyond adipose tissue andmuscle, indicating the potential for expanding the focus of livestock trait research. [ABSTRACT FROM AUTHOR]

Context. Wagyu Feeder Check is a genomic-based tool designed to provide genomic estimated breeding values (GEBV) for five feedlot growth and carcase traits. At present, Wagyu Feeder Check is based on a reference population of 8316 genotyped and phenotyped Australian fullblood (FB; N = 2120) Wagyu and Wagyu-crossed (XB; N = 6196) cattle, principally Wagyu × Angus F1 animals. Aims. We provide technical details behind the development of the Wagyu Feeder Check and validate the ability of its GEBV to predict differences in performance of Wagyu cattle in daily weight gain at feedlot, carcase weight, carcase eye muscle area, carcase marbling score and carcase rump fat at the P8 site. Methods. Data supplied from eight commercial supply chains across Australia was used to generate GEBV using mixed-model equations that incorporated a genomic relationship matrix build with 82 504 autosomal markers. The bias, dispersion, and accuracy of the GEBV were evaluated using a four-way cross-validation scheme where, in each turn, the phenotypes from a random 1549 (or 25%) XB cattle were set as missing. Key results. The genomic estimate of the Wagyu content in the FB and XB population averaged 99.12% and 59.55%, respectively, and with most of the non-Wagyu content associated with Angus. The estimates of heritability (± s.e.) were 0.497 ± 0.016, 0.474 ± 0.004, 0.347 ± 0.014, 0.429 ± 0.003 and 0.422 ± 0.003 for daily weight gain at feedlot, carcase weight, eye muscle area, marbling and rump fat, respectively. Averaged across the four XB validation populations, the accuracy of GEBV was 0.624, 0.634, 0.385, 0.620, and 0.526 for the same set of traits. Conclusions. Genomic predictions generated by Wagyu Feeder Check can predict differences in feedlot and carcase performance of Australian Wagyu cattle. Given the large content of Angus in the XB population, further research is required to determine the predictive ability of GEBV in Wagyu × Bos indicus and Wagyu × dairy animals. Implications. Commercial feedlot operators finishing animals with a strong Wagyu breed component will benefit from using Wagyu Feeder Check for decision making. [ABSTRACT FROM AUTHOR]

Morphostructural characterization can be used to identify unique characteristics in different animal breeds and an essential tool for the identification and classification of these breeds. The objective of this study was to characterize four Indonesian goat breeds based on their morphostructural traits. A total of 315 female goats (does) at 2.5 - 3.5 years of age were used currently and consisted of 28 Boer, 118 Boerka, 141 Kacang and 28 Ettawa cross. Total eleven body measurements and ten body conformations were measured to describe the morphostructure of goats. Two statistical methods of canonical discriminant analysis (CDA) and hierarchical cluster analysis (HCA) were used to differentiate goat breeds. Body measurement and body index were able to discriminate goat breeds with canonical correlation (Function 1) of 0.81 and 0.77, respectively. According to HCA of morphostructural traits, Boerka and Kacang does are classified into similar cluster. Body measurement is better for discriminating goat breeds rather than body conformation. [ABSTRACT FROM AUTHOR]

Beef is an indispensable source of protein for humans. The production is increased in recent years with the effect of increasing population. Besides of beef cattle breeds, male calves of dairy breeding and combined productive animals are also been fattened. The aim of the study investigate the carcass yield and characteristics of the some beef cattles. In the study hot carcass weights, carcass characteristics and skin weights of 588 male Holstein, Brown-Swiss, Simmental and Montbeliarde cattle breeds raised in Amasya region were used. For this purpose, the hot carcass weight data was taken at the slaughterhouse shortly after dressing and the weights of mince, cubed meat, steak, tenderloin, ribeye at the chilled carcass and skin weights of the beef cattle raised by the members of the Amasya Cattle Breeders Association were investigated. Slaughtered animals were fed mainly concentrated feed with commercial fattening feed. The hot carcass weights of slaughtered animals in Holstein, Brown-Swiss, Simmental and Montbeliarde cattle breeds were 343.70±3.12 kg, 319.80±15.50 kg, 336.56±3.58 kg and 349.44±6.06 kg respectively. The hot carcass weights of the animals according to age of 13-15 months, 16-18 months, 19-21 months, 22-24 months and +24 months were 316.44±8.20, 337.44±3.18, 342.00±3.62, 339.98±5.48 and 370.35±9.11 kg respectively. While the effect of breed on hot carcass weight was insignificant (p>0.05), the effect of age was significant (p<0.05). The breed and age interaction were significant (p<0.05). The highest skin weight was determined in the Simmental breed, and the lowest in the Holstein breed. While the effect of breed on mince, cubed meat, steak, tenderloin fillet was insignificant (p>0.05) and it was significant on ribeye (p<0.05). However, while the effect of age on mince, cubed meat, steak, tenderloin was significant (p<0.05), it was not significant on ribeye (p>0.05). As a result of the study, it was evaluated that different breeds reached their target slaughter weights in different times, and that breeders determine the target slaughter time according to carcass yield rather than age. [ABSTRACT FROM AUTHOR]

Simple Summary: As precision livestock technology continues to become viable for extensive rangeland systems. it is important to determine which technology has the potential to positively impact grazing management. Utilizing precision weighing systems on rangeland beef cattle provides new and novel insight into individual animal performance throughout grazing periods, which are directly linked to stocking rates (cattle/ha/time), to ensure adequate forage dry matter intake for cattle while avoiding negative environmental impacts. Refining stocking rate estimates using precision body weight measurements and precision system modeling is critical as this management decision is fundamental to rangeland management and livestock productivity across the United States. An essential component required for calculating stocking rates for livestock grazing extensive rangeland is dry matter intake (DMI). Animal unit months are used to simplify this calculation for rangeland systems to determine the rate of forage consumption and the cattle grazing duration. However, there is an opportunity to leverage precision technology deployed on rangeland systems to account for the individual animal variation of DMI and subsequent impacts on herd-level decisions regarding stocking rate. Therefore, the objectives of this study were, first, to build a precision system model (PSM) to predict total DMI (kg) and required pasture area (ha) using precision body weight (BW), and second, to evaluate differences in PSM-predicted stocking rates compared to the traditional herd-level method using initial or estimated mid-season BW. A deterministic model was constructed in both Vensim (version 10.1.2) and Program R (version 4.2.3) to incorporate individual precision BW data into a commonly used rangeland equation using %BW to estimate individual DMI, daily herd DMI, and area (ha) required to meet animal DMI requirements throughout specific grazing periods. Using the PSM, differences in outputs were evaluated using three scenarios: (1) initial BW (business as usual); (2) average mid-season BW; and (3) individual precision BW using data from two precision rangeland experiments conducted at the South Dakota State University Cottonwood Field Station. The data from the two experiments were used to develop PSM case studies. The trial data were collected using precision weight data (SmartScale™) collected from replacement heifers (Case study 1, n = 60) and steers (Case study 2, n = 254) grazing native rangeland. In Case study 1 (heifers), Scenario 1 versus Scenario 3 resulted in an additional 73.41 ha required. Results from Case study 2 indicated an average additional 4.4 ha required per pasture when comparing Scenario 3 versus Scenario 1. Sensitivity analyses resulted in a difference between maximum and minimum simulated values of 27,995 and 4265 kg forage consumed, and 122 and 8.9 pasture ha required for Case studies 1 and 2, respectively. Thus, results from the scenarios indicate an opportunity to identify both under- and over-stocking situations using precision DMI estimates, which helps to identify high-leverage precision tools that have practical applications for enhancing animal and plant productivity and environmental sustainability on extensive rangelands. [ABSTRACT FROM AUTHOR]

Recording complex phenotypes on a large scale is becoming possible with the incorporation of recently developed new technologies. One of these new technologies is the use of 3-dimensional (3D) cameras on commercial farms to measure feed intake and body weight (BW) daily. Residual feed intake (RFI) has been proposed as a proxy for feed efficiency in several species, including cattle, pigs, and poultry. Dry matter intake (DMI) and BW records are required to calculate RFI, and the use of this new technology will help increase the number of individual records more efficiently. The aim of this study was to estimate genetic parameters (including genetic correlations) for DMI and BW obtained by 3D cameras from 6,000 cows in commercial farms from the breeds Danish Holstein, Jersey, and Nordic Red. Additionally, heritabilities per parity and genetic correlations among parities were estimated for DMI and BW in the 3 breeds. Data included 158,000 weekly records of DMI and BW obtained between 2019 and 2022 on 17 commercial farms. Estimated heritability for DMI ranged from 0.17 to 0.25, whereas for BW they ranged from 0.44 to 0.58. The genetic correlations between DMI and BW were moderately positive (0.58–0.65). Genetic correlations among parities in both traits were highly correlated in the 3 breeds, except for DMI between first parity and late parities in Holstein where they were down to 0.62. Based on these results, we conclude that DMI and BW phenotypes measured by 3D cameras are heritable for the 3 dairy breeds and their heritabilities are comparable to those obtained by traditional methods (scales and feed bins). The high heritabilities and correlations of 3D measurements with the true trait in previous studies demonstrate the potential of this new technology for measuring feed intake and BW in real time. In conclusion, 3D camera technology has the potential to become a valuable tool for automatic and continuous recording of feed intake and BW on commercial farms. [ABSTRACT FROM AUTHOR]

The objective of this research was to investigate the diagnostic accuracy of post‐mortem ultrasound in antral follicle count (AFC) determination and compare it with visual AFC in grazing crossbred Holstein cows, at high altitude in Ecuador. Pre‐mortem blood from 80 cows was collected, and AFC and ovarian characteristics were analysed post‐mortem by ultrasound and visual techniques. AFC counts were stratified as high, medium or low by terciles. Mean AMH concentration in pre‐mortem blood was 280.1 ± 15.53 pg/mL. The AFC obtained by visual inspection (26.9 ± 9.49 follicles) was 23.8% higher than by ultrasound (20.5 ± 7.53 follicles) in all ovaries. Body condition score, age and weight of the cattle did not interact with the count technique. In the low AFC group, visual inspection and ultrasound provided similar AFC results. However, in the Medium‐ and High‐AFC groups, AFC by ultrasound was 14.9% lower than AFC by visual inspection. We confirm that ultrasound can be used with great accuracy for AFC >3 mm (close to the resolution limit) in grazing crossbred Holstein cows at high altitude. [ABSTRACT FROM AUTHOR]

The objective of this paper is to evaluate the effects of creep feeding supplementation during the preweaning phase on the growth performance and metabolic characteristics of Nellore heifers. Forty-two female Nellore calves (age = 100 ± 25 d; initial body weight (BW) = 113.4 ± 16.6 kg) were randomly assigned to the following treatments: control, where calves received mineral mix supplementation (n = 21); supplemented in creep feeding, where calves received 6 g/kg BW of a concentrate supplement (n = 21) during a period of 140 d. In the postweaning phase, all heifers received 6 g/kg BW of a concentrate supplement during a period of 210 d. Supplemented heifers had a greater average daily gain (ADG) than control heifers during the preweaning phase and, consequently, were heavier at weaning and at the end of the growing phase (p < 0.05). However, preweaning supplementation did not influence (p > 0.05) the body measurements or BW at the end of the growing period. Greater (p < 0.05) rib fat was observed in supplemented heifers. Concentrations of metabolites were not affected by preweaning supplementation (p > 0.05). Thus, supplementing heifers in the preweaning phase improved growth performance of weaning and body adiposity. [ABSTRACT FROM AUTHOR]

Objective: The aim of the study was to use a meta-analysis to identify the correlation between linear body measurements, including body length (BL), wither height (WH), heart girth (HG), and body volume (BV), and body weight in beef cattle by breed, sex, and age as categories. Materials and Methods: These results can be used as a method for predicting beef cattle body weight. This study used systematic review and meta-analysis guidelines to create a checklist. The first stage was searching for papers relevant to the study objectives. The second stage was searching using the keywords beef cattle, body weight, body measurement, and correlation. The third stage was reviewing the title and abstract. The fourth stage was abstracting information from selected papers, and the last stage was tabulating data. Results: The results from this study were obtained, and 32 papers were eligible for the meta-analysis stage. The correlation between linear body measurement and body weight of beef cattle showed that HG (r = 0.88) and BV (r = 0.97) were significantly (p < 0.05) different compared to BL (r = 0.74) and WH (r = 0.72). The correlation between HG and body weight, and the categorization of cattle breeds showed significantly (p < 0.05) different results. The correlation between BV and body weight of cattle according to breed categories showed results that were not significantly (p > 0.05) different, while age was significantly (p < 0.05). Conclusion: In conclusion, to predict beef cattle body weight, it is necessary to use HG or BV, with breed, sex, and age of cattle as categories. [ABSTRACT FROM AUTHOR]

Accurate weight measurement is critical for monitoring the growth and well-being of cattle. However, the traditional weighing process, which involves physically placing cattle on scales, is labor-intensive and stressful for the animals. Therefore, the development of automated cattle weight prediction techniques assumes critical significance. This study proposes a weight prediction approach for Korean cattle using 3D segmentation-based feature extraction and regression machine learning techniques from incomplete 3D shapes acquired from real farm environments. Firstly, we generated mesh data of 3D Korean cattle shapes using a multiple-camera system. Subsequently, deep learning-based 3D segmentation with the PointNet network model was employed to segment 3D mesh data into two dominant parts: torso and center body. From these segmented parts, the body length, chest girth, and chest width of Korean cattle were extracted. Finally, we implemented five regression machine learning models (CatBoost regression, LightGBM, polynomial regression, random forest regression, and XGBoost regression) for weight prediction. To validate our approach, we captured 270 Korean cattle in various poses, totaling 1190 poses of 270 cattle. The best result was achieved with mean absolute error (MAE) of 25.2 kg and mean absolute percent error (MAPE) of 5.85% using the random forest regression model. [ABSTRACT FROM AUTHOR]

Management and design affect systems' ability to deliver ecosystem services and meet sustainable intensification needs for a growing population. Soil–plant–animal health evaluations at the systems level for conventional and silvopastoral environments are lacking and challenge adoption across temperate regions. Impacts of silvopasture on soil quality, microclimate, cattle heat stress, forage quality and yield, and cattle weight gain were compared to a conventional pasture in the mid-southern US. Here, we illustrate silvopastures have greater soil organic carbon, water content, and overall quality, with lower temperatures (soil and cattle) than conventional pastures. Forage production and cattle weight gains were similar across systems; yet, conventional pasture systems would need approximately four times more land area to yield equivalent net productivity (tree, nuts, forage, and animal weight) of one ha of silvopasture. Temperate silvopastures enhanced delivery of ecosystem services by improving soil quality and promoting animal welfare without productivity losses, thus allowing sustainable production under a changing climate. [ABSTRACT FROM AUTHOR]

Measuring weight during cattle growth is essential for determining their status and adjusting the feed amount. Cattle must be weighed on a scale, which is laborious and stressful and could hinder growth. Therefore, automatically predicting cattle weight could reduce stress on cattle and farm laborers. This study proposes a prediction system to measure the change in weight automatically during growth using three regression models, using environmental factors, feed intake, and weight during the period. The Bayesian inference and likelihood estimation principles estimate parameters that determine the models: the weighted regression model (WRM), Gaussian process regression model (GPRM), and Gaussian process panel model (GPPM). A posterior distribution was derived using these parameters, and a weight prediction system was implemented. An experiment was conducted using image data to evaluate model performance. The GPRM with the squared exponential kernel had the best predictive power. Next, GPRMs with polynomial and rational quadratic kernels, the linear model, and WRM had the next-best predictive power. Finally, the GPRM with the linear kernel, the linear model, and the latent growth curve model, and types of GPPM had the next-best predictive power. GPRM and WRM are statistical probability models that apply predictions to the entire cattle population. These models are expected to be useful for predicting cattle growth on farms at a population level. However, GPPM is a statistical probability model designed for measuring the weight of individual cattle. This model is anticipated to be more efficient when predicting the weight of individual cattle on farms. [ABSTRACT FROM AUTHOR]

BACKGROUND AND OBJECTIVES: Farmer characteristics are recognized in this study. The characteristics, perceptions, willingness to adopt climate change mitigation, and awareness of livestock farmers toward livestock waste management are the main points for determining appropriate climate mitigation rules. METHODS: This study was conducted in Enrekang and Barru Regencies of South Sulawesi. International Business Machines - Statistical Package for the Social Sciences 27 was used for this study. In descriptive statistics, data were compiled, and the age, long husbandry experiences (year), number of family member, number of farming assistant, gender, education, farmer group participation status, side job, type of business, cattle ownership status, number of cattle (head), and weight total of cattle's manure (kilogram per day) were examined qualitatively. A chi-square test was used to compare the experimental results (perception and knowledge of livestock manure management) with practical livestock manure management. FINDINGS: This study found that the average age of farmers in the study area is 45 and 11.2 percent received have high formal education level from a university. Most of the cattle are male at 86.7 percent. Poor manure management system at 76.30 percent manure unmanaged and un-appropriate farmer groups with more than 60 percent of the farmers unjoined farmer's group. Almost 50 percent of the cattle farmers are willing to learn manure management. Nevertheless, this study found that the respondents' knowledge and practical manure management, as well as the respondents' knowledge (0.837) and perception (0.343) of practical manure management, do not have any significant connection. CONCLUSION: This study determines the full condition of cattle farmers in Barru and Enrekang Regencies. Barriers include low level of education, age of farmers, lack of manure management, and lack of willingness to join farmers group. Nevertheless, drivers, such as willingness to adopt manure management and high levels of experience in cattle farming, were also found. Enriching the knowledge and perception of farmers is essential in managing livestock wastes to mitigateof climate change. [ABSTRACT FROM AUTHOR]

Context: Measurement of weight provides the basis of most performance-recording schemes for beef cattle around the world. The limitation of faster growth rate as a breeding objective, without considering changes in mature-cow weight, is the expected increase in cow size and, hence, feed requirements. Aims: To measure the correlated changes in feed intake and efficiency of cows, calves and the cow–calf unit following divergent selection for growth rate. Methods: The cows and their calves came from three lines of Angus cattle selected for either fast weight gain to yearling age (the High-line), slow weight gain (the Low-line), or from an unselected Control-line. Efficiency was evaluated over an annual production cycle. Individual cow weights and feed intakes, and calf growth and feed intake (including milk), were recorded. Milk production, milk composition and body composition were also measured so that correlated changes in efficiency of use of energy and nitrogen could be determined. Key results: The High-line cows were 18% (P < 0.05) heavier than the Low-line cows at the start and consumed 7% (P < 0.05) more feed than did the Low-line cows. Feed efficiency of the cow–calf unit was 12% higher (P < 0.05) in the High-line cows and calves than in the Low-line cows and calves. When compared on the basis of feed used relative to their weight and weight gain there was no difference (P > 0.05) between the selection lines. Divergent selection was accompanied by a change in body composition, with the High-line cows containing proportionally less protein and more fat in their bodies than did the Low-line cows. There was no evidence for change in the efficiency of feed energy use, but there was a 10% (P < 0.05) improvement in nitrogen efficiency of the cow–calf unit in the High-line compared with the Low-line. Conclusions: Divergent selection for weight gain led to a correlated change in cow size and cow feed requirements. Implications: This experiment supported the consensus among earlier reviews that there is little evidence that selection for growth rate or size, without moderating change in mature-cow weight, is associated with improved efficiency of feed energy use in maternal beef breeds. Breeding cattle for faster weight gain is effective in changing the size of animals, but can increase cow size and feed requirements, which may be undesirable. This experiment showed that selection for growth rate increased cow size and feed intake, with improvement in the feed efficiency, but not energy efficiency, of the cow–calf unit. Breeding programs that are accompanied by an increase in cow size need to be cognizant of the increase in cow feed requirement. [ABSTRACT FROM AUTHOR]

The present investigation arose from the current problem in the entire territory of the Department of Atlántico in the Republic of Colombia, in which the livestock sector currently lacks a reliable modernization that contributes to the planning and profitability of meat production, translated into weight gain. The main focus of the study gravitated around the ignorance of the real effect exerted by meteorological and nutritional factors on the weight gain of cattle. As a possible solution, it was proposed to carry out a statistical analysis by means of a multiple linear regression model where cattle weight gain was the dependent variable to study under the influence of the following independent variables: accumulated precipitation for two weeks (mm), average daily precipitation for two weeks (mm), average daily forage height consumed for two weeks (cm), percentage daily average of forage consumed during two weeks (%), average protein percentage of forage consumed during two weeks (%), the average maximum temperature recorded during two weeks (°C), the average minimum temperature recorded during two weeks (°C), average daily temperature variation recorded for two weeks (°C) and average relative humidity recorded for two weeks (%). All independent data values were collected in the field. Once the analysis was carried out, it was concluded that there was statistical evidence to affirm that only the independent variables "accumulated precipitation", "average precipitation", "average minimum temperature" and "relative humidity" significantly influenced the changes observed in profit of cattle weight, being formulated a multiple linear regression model that contained only the mentioned variables, the rest were discarded. On the other hand, for the constructed linear regression model, the coefficient of determination R2 = 89.3691% was obtained, that is, for the significance level α = 0.05 (95% confidence level), this determined that the model of Multiple linear regression (A) explained the behavior of the average monthly cattle weight gain by 89.3691%. It was concluded, therefore, that the present work gives veracity to the determination of previous investigations where it is also concluded that the meteorological variables directly affect the changes associated with the weight of cattle for meat production. [ABSTRACT FROM AUTHOR]

This study aimed to determine the effects of DL-malic acid supplementation in beef cattle rations containing high concentrated feed and dry forage (alfalfa hay and wheat straw) on fattening performance, carcass traits and rumen parameters. In present study, 47 male beef cattle (19 Simmental, 28 Limousine) at the age of 14-16 months were used. Cattle breeds were divided into two groups (0 and 30 g/day of DL-malic acid). In the present study, the differences in live weights, daily live weight gains and carcass weights of the control and DL-malic acid groups were found to be significant in Simmental breed (P<0.05), but insignificant in Limousine breed. The beef cattle body measurements (withers height, chest girth, rump height, body length) did not change with malic acid supplementation (P>0.05).The malic acid addition increased the molarities of acetic, butyric, propionic and total volatile fatty acids (TVFA) and acetic acid/ propionic acid ratio in the rumen fluid (P<0.05).The addition of malic acid had no significant effect on the number of ciliated protozoa (Entodinium, Diplodinium, Isotricha and Dasytricha) and total bacteria count in the rumen fluid (P>0.05). As a result, DL-malic acid supplementation to beef cattle ration varied with cattle breeds in terms of fattening performance, while such supplementations had positive effect on fattening in Simmental breed. Besides, the increase in TVFA and acetic, propionic and butyric acids, which are indicators of fiber and carbohydrate fermentation efficiency in the rumen, shows that malic acid has a positive effect on feed digestion in the rumen. [ABSTRACT FROM AUTHOR]

To forecast and model the weight of cattle, several techniques are used. Nonetheless, no machine algorithm has been utilized to estimate the weight of Bali cattle. This article examines the use of machine learning regression to create models for Bali cattle's body weight prediction. The response variables consist of body weight as the dependent variable and body length, girth circumference, and height at wither of 228 male and 211 female cattle of similar ages (285 days). The descriptive statistics of female Bali cattle in our investigation revealed that the morphological measurements were similar to those documented by other researchers. To predict body weight based on different characteristics, machine learning models such as Random Forest, Support Vector, K-Neighbors, and Extra Tree regressions have been used. Additionally, linear regression was utilized to estimate the body weight for comparison with the traditional approach. The assessment standards used included the determination coefficient, the root mean square error, the average absolute error, and the average absolute percentage error as measures of evaluation efficiency. We found that Linear Regression performs the best among all the regressors for female cattle. Similarly for males, it is about the same as extra tree regression. The machine learning algorithm (MLA) was discovered to furnish a more precise estimate of the weight of the body of cattle, surpassing the conventional algorithm. [ABSTRACT FROM AUTHOR]

Purpose: Corn fodder is often used for fattening beef cattle, which compete for feeding other livestock. However, Sorghum fodder has a nutritional value equivalent to corn fodder. This study aims to determine the effect of substituting of corn fodder with sorghum fodder on the body weight gain of cattle and also the digestibility of nutrients. Research Method: Nine local beef cattle with weights ranging from 139-239 kg were allocated in a completely randomized design with 3 treatments and 3 replications. The treatments given were: R0 = basal ration (30% corn fodder + 70% concentrate); R1 =15% corn fodder +15% sorghum fodder +70% concentrate; and R2 = 30% sorghum fodder + 70% concentrate. The data were analyzed using covariance analysis. Body weight gain; digestibility of dry matter, digestibility of organic matter, digestibility of crude protein, and digestibility of crude fibre were measured. Findings: Based on the analysis of covariance, the study showed that there was no significant difference (P>0.05) between substituted sorghum fodder and ration consumption, body weight gain, ration conversion, and digestibility of feed substances (dry matter, organic matter, crude protein, and crude fibre) in beef cattle. The results showed that body weight gain ranged from 0.63-1.18 kg/head/day, feed conversion ratio ranged from 5.12-9.66, and digestibility of dry matter, organic matter, crude protein, and crude fibre, 76.29%-79.10%; 79.16%-82.16%; 72.47%-76.13%; and 45.46%-46.70% respectively. This study revealed that Tebon corn can be completely (100%) substituted by fodder sorghum in beef cattle rations. Research Limitations: This research was conducted at the farmer level, which causes the diversity of cattle used as experimental material to be quite high. Therefore, in analyzing the data, we used covariance analysis. Originality/Value: This research informs that the use of forage sorghum can replace corn fodder up to a limit of 100%. [ABSTRACT FROM AUTHOR]

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Cattle farming in Indonesia, especially in North Sumatra, is still a secondary livelihood for breeders. Treatment and processing of beef are generally done in the traditional way. The success of the beef cattle business is very dependent on the fulfillment of nutrients that affect livestock health. Therefore, quality and sustainable feed is an important factor in livestock cultivation technology. The purpose of this study was to determine the effect of fermented feed on cattle weight at a small cattle farm in Pondok Rawa Village, Deli Serdang Regency, Sumatera Utara. Fermented feed is formulated by mixing corn ash and palm oil cake (5:1), coarse salt, molasses, and EM4 into chlorine-free water. The feed was stored in PP plastic and incubated for 7 days. Five cows chosen randomly were given fermented feed every day for 1 month while the other 5 cows were only given forage. All test cattle were about 4 years old and weighed weekly and the data were statistically analyzed using ANOVA in JASP 0.16.4. The results showed that the average weight gain of one cattle fed with fermented feed (1.54 kg/week) was higher than forage treatment (0.69 kg/week). This result was validated and substantiated by ANOVA test result showing that value of p < 0.05. [ABSTRACT FROM AUTHOR]

Context: Birth weight can be an important trait in beef cattle through its association with dystocia and increased likelihood of calf and cow mortality. Recording large numbers of birth weights in beef cattle to obtain a suitable genetic evaluation has often been hard to achieve. Aims: We assess if coronet circumference measurements taken at birth and weights and coronet circumference measured post-birth are suitable predictors of birth weight for use in genetic evaluation in northern Australian tropically adapted beef breeds. Methods: Animals were recorded at birth for weight (N = 5352) and coronet circumference (N = 2552), at 3 months of age for the liveweight (N = 2848) and coronet circumference (N = 2855) and liveweight at 6 months (N = 4929). Data were from three tropically adapted beef cattle breeds (viz. Brahman, Droughtmaster and Santa Gertrudis) recorded in two northern Australia herds. Genetic parameters were estimated from a pooled dataset containing all three breeds. Results: Birth weight had an estimated direct and maternal heritability of 0.51 (0.04) and 0.14 (0.02) respectively. Coronet circumference also had high heritabilities, with estimates at birth and 3 months of 0.50 (0.07) and 0.55 (0.06) respectively. The estimated genetic correlation between birth weight and coronet circumference measured at birth was 0.86 (0.03). Birth weight genetic correlations were 0.75 (0.05) with 3-month weight, 0.69 (0.05) with weaning weight and 0.62 (0.05) with coronet circumference at 3 months. Conclusions: Coronet measurements could be used in genetic evaluation as a proxy for birth weight. However, the most useful coronet measure was when it was recorded at birth. This would still require catching the calf at birth, thus greatly reducing the benefit of having an alternative measure. Coronet circumference recorded in the branding cradle at 3 months of age was also a useful predictor of birth weight but added little if post-birth weights were available. Importantly, all post-birth indirect measures of birth weight require adjustment for animal age and, therefore, would need recording of the individual calf's date of birth. Implications: Coronet circumference recorded at birth and 3 months of age does not appear to be a suitable proxy for genetic evaluation of birth weight. Birth weight can be an important trait in beef cattle through its association with dystocia and increased likelihood of calf and cow mortality. Recording birth weight can be difficult, and coronet circumference measures were assessed but found unsuitable as a suitable predictor of birth weight. Therefore, despite being difficult to record, genetic improvement in birth weight still requires birth weight to be recorded. [ABSTRACT FROM AUTHOR]

In cattle breeding, regularly taking the animals to the scale and recording their weight is important for both the performance of the enterprise and the health of the animals. This process, which must be carried out in businesses, is a difficult task. For this reason, it is often not performed regularly or not performed at all. In this study, we attempted to estimate the weights of cattle by using stereo vision and semantic segmentation methods used in the field of computer vision together. Images of 85 animals were taken from different angles with a stereo setup consisting of two identical cameras. The distances of the animals to the camera plane were calculated by stereo distance calculation, and the areas covered by the animals in the images were determined by semantic segmentation methods. Then, using all these data, different artificial neural network models were trained. As a result of the study, it was revealed that when stereo vision and semantic segmentation methods are used together, live animal weights can be predicted successfully. [ABSTRACT FROM AUTHOR]

Background: International evaluations combine data from different countries allowing breeders to have access to larger panels of elite bulls and to increase the accuracy of estimated breeding values (EBV). However, international and national evaluations can use different sources of information to compute EBV (EBVINT and EBVNAT, respectively), leading to differences between them. Choosing one of these EBV results in losing the information that is contained only in the discarded EBV. Our objectives were to define and validate a procedure to integrate publishable sires' EBVINT and their associated reliabilities computed from pedigree-based or single-step international beef cattle evaluations into national evaluations to obtain "blended" EBV. The Italian (ITA) pedigree-based national evaluation was used as a case study to validate the integration procedure. Methods: Publishable sires' international information, i.e. EBVINT and their associated reliabilities, was included in the national evaluation as pseudo-records. Data were available for 444,199 individual age-adjusted weaning weights of Limousin cattle from eight countries and 17,607 genotypes from four countries (ITA excluded). To mimic differences between international and national evaluations, international evaluations included phenotypes (and genotypes) of animals born prior to January 2019, while national evaluations included ITA phenotypes of animals born until April 2019. International evaluations using all available information were considered as reference scenarios. Publishable sires were divided into three groups: sires with ≥ 15, < 15 and no recorded offspring in ITA. Results: Overall, for these three groups, integrating either pedigree-based or single-step international information into national pedigree-based evaluations improved the similarity of the blended EBV with the reference EBV compared to national evaluations without integration. For instance, the correlation with the reference EBV for direct (maternal) EBV went from 0.61 (0.79) for a national evaluation without integration to 0.97 (0.88) when integrating single-step international information, on average across all groups of publishable sires. Conclusions: Our proposed one-animal-at-a-time integration procedure yields blended EBV that are in close agreement with full international EBV for all groups of animals analysed. The procedure can be directly applied by countries since it does not rely on specific software and is computationally inexpensive, allowing straightforward integration of publishable sires' EBVINT from pedigree-based or single-step based international beef cattle evaluations into national evaluations. [ABSTRACT FROM AUTHOR]

Beef cattle body size is an important phenotypic trait for breeding and production. The non-contact automatic calculation of beef cattle body sizes via point cloud data exhibits several disadvantages, such as the inaccurate positioning of measurement points and the sensitivity to postures, heavily restricting commercial applications. To address these issues, an automatic method for key region segmentation, body size calculation, and data calibration to accurately measure the body size parameters of beef cattle in different postures is proposed. Firstly, the body sizes were obtained based on the point cloud data. Then the twelve micro-posture feature parameters were defined and extracted from four categories corresponding to the head, back, torso, and leg regions. Based on those parameters, a Posture-based Measurement Adjustment model was established to reduce the influence of postures on calculation results based on the correlation between measurement errors and micro-posture features. The experimental results show that, after the adjustment model calibration, the average errors of body oblique length, wither height, hip height, chest girth, and abdominal girth were 1.14%, 1.84%, 3.47%, 1.56%, and 2.36%, respectively, whereas the corresponding maximum errors were 4.36%, 8.10%, 11.10%, 7.29%, and 9.26%. The measurement errors of body sizes can be significantly minimised by the adjustment model, which can improve the robustness of different postures. The adjustment model improves the accuracy of the non-contact body size measurement, which could provide guidance and inspirations for future research. • Body size automatic measurement based on beef cattle point clouds was achieved. • Twelve micro-pose features were defined to describe beef cattle postures. • The PMA model was proposed to effectively reduce body size measurement errors. [ABSTRACT FROM AUTHOR]

The genome-wide association study is popularly used to identify markers associated with high economic traits in cattle breeds worldwide. However, this method has never been applied to Bali cattle (Bos javanicus), which are indigenous to Indonesia. Therefore, this study aimed to determine whether the GWAS can also be employed to figure out genomic regions potentially affecting Bali cattle's birth weight trait. In this study, phenotypic and genotypic data of 48 Bali cattle were used to figure out genomic regions which are potentially affecting the birth weight trait of Bali cattle. Those samples were genotyped using an Illumina bead chip array with 53.218 single nucleotide polymorphisms (SNPs). The estimation of the variance proportion explained by each SNP was conducted by a restricted maximum likelihood (REML) approach. The result showed that the birth weight trait in Bali cattle was affected by multiple regions dispersed over the genome, especially chromosomes 20 and 21. This study demonstrated that GWAS can be used effectively and discovered two intriguing regions related to quantitative trait loci and genes, namely STXBP6 and TERT, which previously had been linked to cattle birth weight and growth. These findings are important for developing and refining genomic-based selection programs for Bali cattle in Indonesia. [ABSTRACT FROM AUTHOR]

Simple Summary: Body and carcass weight are important economic characteristics for beef cattle production systems because the value of market cattle is based on weight. The possibility of predicting body and carcass weight through biometric measurements obtained from three-dimensional digital images favor the development of the production system. Predictive approaches, such as artificial neutral network, showed better predictive quality for body weight, while the least absolute shrinkage and selection operator and partial least square models were the most suitable for predicting carcass weight. The objective of this study was to evaluate different methods of predicting body weight (BW) and hot carcass weight (HCW) from biometric measurements obtained through three-dimensional images of Nellore cattle. We collected BW and HCW of 1350 male Nellore cattle (bulls and steers) from four different experiments. Three-dimensional images of each animal were obtained using the Kinect® model 1473 sensor (Microsoft Corporation, Redmond, WA, USA). Models were compared based on root mean square error estimation and concordance correlation coefficient. The predictive quality of the approaches used multiple linear regression (MLR); least absolute shrinkage and selection operator (LASSO); partial least square (PLS), and artificial neutral network (ANN) and was affected not only by the conditions (set) but also by the objective (BW vs. HCW). The most stable for BW was the ANN (Set 1: RMSEP = 19.68; CCC = 0.73; Set 2: RMSEP = 27.22; CCC = 0.66; Set 3: RMSEP = 27.23; CCC = 0.70; Set 4: RMSEP = 33.74; CCC = 0.74), which showed predictive quality regardless of the set analyzed. However, when evaluating predictive quality for HCW, the models obtained by LASSO and PLS showed greater quality over the different sets. Overall, the use of three-dimensional images was able to predict BW and HCW in Nellore cattle. [ABSTRACT FROM AUTHOR]

Beef production drives a significant proportion of Australia's agricultural economy, representing AUD11 billion in agricultural production value annually. The profitability of cattle farms across seasons varies greatly and is particularly influenced by weather and associated uncertainty through pasture growth. Furthermore, producers must be careful in managing stocking rates to avoid overgrazing which has a significant environmental and economic impact. Predictive modelling of pasture and cattle liveweight can help producers to better manage this difficult balancing act. In this paper, we integrate a model for pasture growth and cattle weight gain to formulate predictions of liveweight production volume and pasture biomass. Monte‐Carlo simulation was used to understand the impact of uncertainty in model inputs relating to weather. Through such an approach, a distribution of possible pasture outcomes and beef production is formed which can be inspected to determine, for example expected production volume and risk of overgrazing. The methodology is demonstrated and validated through application to case study data sourced from Australian beef producers. Results demonstrate that it is possible to obtain reasonable predictions of liveweight gain and highlight the importance of considering the associated uncertainty. The accuracy of the proposed models has been examined by calculating statistical parameters MSE, MAE and R2. This approach can provide insight into the distribution of possible production outcomes given the long‐term rainfall outlook. The use of such predictive models and simulations by producers will lead to better‐informed planning of stocking rates, with benefits to productivity and sustainable utilisation of pasture. [ABSTRACT FROM AUTHOR]