Caprine toxoplasmosis in Southern Brazil: a comparative seroepidemiological study between the indirect immunofluorescence assay,the enzyme-linked immunosorbent assay,and the modified agglutination test

Tropical Animal Health and Production - This study investigated the prevalence of caprine toxoplasmosis in goat herds from Southern Brazil by the indirect immunofluorescence assay (IFA), and...     

The effect of life history events on carcass merit and price of cull dairy cows

Cull dairy cows contribute almost 10% of national beef production in the United States. However, different factors throughout the life of dairy cows affect their weight and overall body condition as well as carcass traits, and consequently affect their market price. Therefore, the objectives of this study were: (1) to assess relationships between price ratio and carcass merit of cull dairy cows sold through several sites of an auction market and (2) to investigate the effect of animal life history events and live weight on sale barn price (BP) and price ratio (as a measure of relative price), as an indicator of carcass merit. Data from 4 dairy operations included 3,602 cull dairy cow records during the period of 2015 to 2019. Life history events data were collected from each dairy operation through Dairy Comp software; live weight and price were obtained periodically from the auction market, and the carcass data were provided by a local packing plant. Cow price in dollars per unit of live weight ($/cwt) and price ratio were the 2 outcome variables used in the analyses. Price ratio was created aiming to remove seasonality effects from BP (BP divided by the national average price for its respective month and year of sale). The association between price ratio and carcass merit traits was investigated using canonical correlation analysis, and the effect of life history events on both BP and price ratio was inferred using a multiple linear regression technique. More than 70% of the cows were culled in the first 3 lactations, with an average live weight of 701.5 kg, carcass weight of 325 kg, and dressing percentage of 46.3%. On average, cull cows were sold at $57.0/cwt during the period considered. The canonical correlation between price ratio and carcass merit traits was 0.76, indicating that price ratio reflected carcass merit of cull cows. Later lactations led to lower BP compared with cows culled during the first 2 lactations. Injury, and leg and feet problems negatively affected BP. Productive variables demonstrated that the greater milk production might lead to lower cow prices. A large variation between farms was also noted. In conclusion, price ratio was a good indicator of carcass merit of cull cows, and life history events significantly affected sale BP and carcass merit of cull cows sold through auction markets.     

Effects of vaccination against brucellosis and clostridia on the intake,performance, feeding behavior,blood parameters,and immune responses of dairy heifers calves

The aim of this study was to identify possible effects of different vaccination strategies (concomitantly or not) against brucellosis and clostridia on intake, performance, feeding behavior, blood parameters, and immune responses of dairy heifers calves. Fifty heifers calves were enrolled [38 Gyr (Zebu, Bos taurus indicus) and 12 5/8 Holstein Gyr]. At 120 d of age, animals were randomly distributed among 3 groups: B (n = 18), vaccinated against brucellosis; C (n = 14), vaccinated against clostridia and CB (n = 18), vaccinated concomitantly for both. Rectal and thermographic temperatures were evaluated on days 1, 0, 1, 2, 3, 5, 7,10, 14, and 28 relatives to the vaccination day. Feed and water intake, body weight (BW), and feeding behavior were monitored daily by an electronic feeding system. Blood was sampled on days 0, 3, 7, 14, and 28, relative to the vaccination day for determination of glucose and -hydroxybutyrate (BHBA) concentrations. Blood sampled on day 0 (prevaccination) and on days 28 and 42 were used to evaluate the immune response against Brucella abortus and clostridia. There was an increase in rectal temperature between the first and the third day postvaccination in the 3 groups. The thermography revealed an increase of local temperature for 7 d on groups B and CB. Group C had increased local temperature for a longer period, lasting for up to 14 d. Dry mater intake was reduced for groups B and CB, but no alteration was observed for group C. No alterations regarding initial BW, final BW, average daily weight gain, and feed efficiency were observed. No differences were observed for the 3 vaccination groups for blood parameters throughout the evaluation period. The concomitant vaccination against brucellosis and clostridia led to lower neutralizing antibody titers against epsilon toxin of Clostridium perfringens and botulinum toxin type C of C. botulinum (C > CB > B). When cellular proliferation assay and serological tests to B. abortus were evaluated, no differences were observed between groups B and CB. The present results indicate that the concomitant vaccination against brucellosis and clostridia has no relevant impact on the intake, performance, and feeding behavior of dairy calves. However, the concomitant vaccination of vaccines against these 2 pathogens impacts animal immunity against clostridial infections.     

The value of incorporating carcass trait phenotypes in terminal sire selection indexes to improve carcass weight and quality of heavy lambs

Genetic selection for carcass traits is paramount to maximize the profitability and long‐term sustainability of any meat‐producing livestock species. The main objectives of this research were to evaluate the efficiency of indicator traits for the genetic improvement of lamb carcass traits and to determine the value of including carcass traits into terminal sire selection indexes for the Canadian sheep industry. The carcass traits included hot carcass weight (HCW), fat depth at the GR site (FATGR) and average carcass conformation score (AVGCONF), and were measured on heavy lambs (slaughter age less than 365 days and HCW greater than 16.3 kg) in commercial abattoirs. Growth traits were found to be moderately efficient indicator traits for the genetic improvement of HCW but selection on ultrasound traits was necessary to substantially improve the carcass quality traits (FATGR and AVGCONF). Economic selection indexes were designed by adding various combinations of carcass traits into the Canadian Sheep Genetic Evaluation System terminal indexes. Records measured on individuals and progeny were assumed to be the sources of information for live animal and carcass traits, respectively. The changes in index accuracy, efficiency and expected correlated response were used to assess the value of their inclusion. HCW was found to have a large economic value, and its inclusion into terminal selection indexes was expected to substantially increase their accuracy (0.08–0.12 points) and efficiency (20%–30%). However, further including FATGR (measured 110 mm from the carcass midline over the 12th rib) and AVGCONF had little impact on the accuracy (≤0.03) and efficiency (1%–7%) of the proposed indexes. Thus, the inclusion of carcass traits into the existing terminal selection indexes could be beneficial for the genetic improvement of HCW, but further research is needed to determine optimal methods of increasing carcass fatness and muscularity.     

Genomic prediction for meat and carcass traits in Nellore cattle using a Markov blanket algorithm

This study was carried out to evaluate the advantage of preselecting SNP markers using Markov blanket algorithm regarding the accuracy of genomic prediction for carcass and meat quality traits in Nellore cattle. This study considered 3675, 3680, 3660 and 524 records of rib eye area (REA), back fat thickness (BF), rump fat (RF), and Warner–Bratzler shear force (WBSF), respectively, from the Nellore Brazil Breeding Program. The animals have been genotyped using low-density SNP panel (30 k), and subsequently imputed for arrays with 777 k SNPs. Four Bayesian specifications of genomic regression models, namely Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression methods were compared in terms of prediction accuracy using a five folds cross-validation. Prediction accuracy for REA, BF and RF was all similar using the Bayesian Alphabet models, ranging from 0.75 to 0.95. For WBSF, the predictive ability was higher using Bayes B (0.47) than other methods (0.39 to 0.42). Although the prediction accuracies using Markov blanket of SNP markers were lower than those using all SNPs, for WBSF the relative gain was lower than 13%. With a subset of informative SNPs markers, identified using Markov blanket, probably, is possible to capture a large proportion of the genetic variance for WBSF. The development of low-density and customized arrays using Markov blanket might be cost-effective to perform a genomic selection for this trait, increasing the number of evaluated animals, improving the management decisions based on genomic information and applying genomic selection on a large scale.     

Habitat quality,not habitat amount,drives mammalian habitat use in the Brazilian Pantanal

Landscape Ecology - An understanding of species-habitat relationships is required to assess the impacts of habitat fragmentation and degradation. To date, habitat modeling in fragmented landscapes...     

Proximal sensor-enhanced soil mapping in complex soil-landscape areas of Brazil

Portable X-ray fluorescence (pXRF) spectrometry and magnetic susceptibility (MS) via magnetometer have been increasingly used with terrain variables for digital soil mapping. However, this methodology is still emerging in many countries with tropical soils. The objective of this study was to use proximal soil sensor data associated with terrain variables at varying spatial resolutions to predict soil classes using the Random Forest (RF) algorithm. The study was conducted on a 316-ha area featuring highly variable soil classes and complex soil-landscape relationships in Minas Gerais State, Brazil. The overall accuracy and Kappa index were evaluated using soils that were classified at 118 sites, with 90 being used for modeling and 28 for validation. Digital elevation models (DEMs) were created at 5-, 10-, 20-, and 30-m resolutions using contour lines from two sources. The resulting DEMs were processed to generate 12 terrain variables. Total Fe, Ti, and SiO₂ contents were obtained using pXRF, with MS determined via a magnetometer. Soil class prediction was performed using the RF algorithm. The quality of the soil maps improved when using only the five most important covariates and combining proximal sensor data with terrain variables at different spatial resolutions. The finest spatial resolution did not always provide the most accurate maps. The high soil complexity in the area prevented highly accurate predictions. The most important variables influencing the soil mapping were MS, Fe, and Ti. Proximal sensor data associated with terrain information were successfully used to map Brazilian soils at variable spatial resolutions.