DSpace Coleção: Artigo em periódico indexado (CPPSE)

Effect of bromoform-based feed additive on methane emissions and performance of Nellore cattle in feedlot backgrounding and finishing phases.

2026-01-01T00:00:00Z

Título: Effect of bromoform-based feed additive on methane emissions and performance of Nellore cattle in feedlot backgrounding and finishing phases. Autoria: SILVA, M. M.; MESSANA, J. D.; KIRCHHOFF, A. M.; GERMANO, J. V. de P.; GIAMPIETRO JÚNIOR, F. E.; RIGOBELLO, I. L.; ALVAREZ-HESS, P. S.; JACQUES, S.; TOGNELLI, R.; COSTA, D. F. A.; BERNDT, A.; REIS, R. A. Conteúdo: This study evaluated the effects of a bromoform based feed additive (BBFA) on growth performance and enteric methane emissions in Nellore cattle during feedlot backgrounding and finishing phases. Ninety-six Nellore bulls (10 +/- 2 mo old, body weight (BW) 315 +/- 23 kg (block 1), and BW = 360 + 7 kg [block 2]) were allocated to 1 of 2 treatments: CONTROL (basal diet) and BBFA (basal diet plus BBFA [to target 23 mg bromoform/kg dry matter]). Bulls were housed in pens (n = 6 animals/pen) and monitored over 218 d (108 d backgrounding, 110 d finishing). Performance parameters were measured in all bulls, while enteric methane emissions were assessed in a subset of 36 animals using the sulfur hexafluoride (SF6) tracer technique. Supplementation of the BBFA did not influence dry matter intake (DMI), weight gain or feed efficiency (P > 0.05). Compared with control, BBFA decreased methane production and yield by 26% and 25%, respectively, during backgrounding (P < 0.001). While, in the finishing phase, BBFA supplementation resulted in reductions of 58% in methane production, 59% in yield, and 60% in intensity (P < 0.001). These findings demonstrate the potential to supplement the BBFA throughout the lifecycle of cattle in Brazil, reducing methane emissions without any detrimental impacts on productivity.

Sheep breed-specific response to environment challenge against Haemonchus contortus and effect on immuno-hematological parameters.

2026-01-01T00:00:00Z

Título: Sheep breed-specific response to environment challenge against Haemonchus contortus and effect on immuno-hematological parameters. Autoria: OKINO, C. H.; BELLO, H. J. S.; NICIURA, S. C. M.; CUNHA, A. F. da; COSTA, E. C. da; CAMPOS, E. M. de; KAPRITCHKOFF, R. T. I.; CORRÊA, L. G. P.; MINHO, A. P.; ESTEVES, S. N.; CHAGAS, A. C. de S. Conteúdo: Variable resistance to Haemonchus contortus infection and the associated immune mechanisms have been investigated and characterized in different sheep breeds adapted to tropical climates. In a recent study, we compared the local immune responses of the resistant Santa Inês with those of the susceptible White Dorper and Texel sheep breeds under chronic haemonchosis, and evaluated the correlations of immune-related transcripts and different parasitic stages and sexes. The aim of present study was to further elucidate the immune mechanisms among these sheep breeds by comparing local responses, microscopic lesions in the abomasum and hematological parameters in lambs raised under varying levels of parasitic challenge. The naturally resistant Santa Inês breed maintained similar phenotypic characteristics across different levels of parasitic infection loads, whereas White Dorper and Texel breeds exhibited increased susceptibility under moderate to high challenge. Texel lambs showed altered mean corpuscular volume, indicative of macrocytic anemia, and also displayed the lowest resistance under low challenge conditions. Significantly higher levels of eosinophils, lymphocytes and monocytes in peripheral blood, along with increased expression of Galectin-11 gene in the abomasum, were observed in Santa Inês sheep compared to the other breeds. These responses may represent key host mechanisms contributing to improved control of infection. Overall, our findings demonstrate that resistance to H. contortus infection is breed-dependent and modulated by environmental parasite challenge, providing insights that may forward to the targeted strategies for sheep flock management.

Water performance indicators and benchmarks for dairy production systems.

2024-01-01T00:00:00Z

Título: Water performance indicators and benchmarks for dairy production systems. Autoria: PALHARES, J. C. P.; MATARIM, D. L.; SOUSA, R. V. de; MARTELLO, L. S. Conteúdo: The aim of the study is to discern benchmarks for the indicators L water cow−1 day−1 and L water kg milk−1 day−1 per type of production system and season. A total of 876 commercial dairy farms underwent comprehensive water consumption monitoring from January 2021 to December 2022. The monitored water consumptions were animal drinking water and water usage for cleaning. Confined systems exhibited the highest average for animal drinking and cleaning, 87.5 L water cow−1 day−1 and 84.4 L water cow−1 day−1, respectively. Semi-confined systems presented the lowest average for animal drinking, 54.4 L water cow−1 day−1. Pasture systems showed the lowest average for cleaning, 45.2 L water cow−1 day−1. The benchmarks proposed in this study can serve as the first references for animal drinking and milking parlor washing consumption for production systems in tropical conditions.

Derivation of prediction error variance for non-genotyped individuals in genomic selection.

2026-01-01T00:00:00Z

Título: Derivation of prediction error variance for non-genotyped individuals in genomic selection. Autoria: JUNQUEIRA, V. S.; YOKOO, M. J. I.; CARDOSO, F. F. Conteúdo: Genomic selection has transformed plant and animal breeding by enabling accurate prediction of genetic merit using DNA markers; however, comprehensive genotyping of all selection candidates remains economically prohibitive for most breeding programs. While breeding programs must decide which subset of individuals to genotype within budget constraints, current approaches rely primarily on experience-based decisions rather than quantitative frameworks. We present explicit mathematical derivations for prediction error variance (PEV) in non-genotyped individuals under mixed model equations, providing a theoretical foundation for evaluating genotyping strategies prospectively. The approach derives PEV expressions for non- genotyped selection candidates under different relationship matrix structures, including pedigree-based, genomic, and hybrid single-step methodologies that combine both information sources. The derivations accommodate complex breeding program structures with historical training populations containing both genotypes and phenotypes alongside contemporary selection candidates with only pedigree information. Using Schur complement methods applied to partitioned mixed model equations, the framework enables calculation of prediction uncertainty without requiring actual phenotypic data from selection candidates. The expressions simplify under different information scenarios, from cases with complete phenotypic data to situations where only relationship information is available. The method was validated through simulations across six scenarios with populations ranging from 180 to 15,500 individuals, confirming numerical equivalence with direct matrix inversion while demonstrating computational and memory advantages that increase with population size. Although genomic relationship matrix operations dominate the complexity, matrix decomposition techniques, including Cholesky factorization and APY methodology, can improve efficiency. The mathematical framework provides quantitative tools for transitioning from experience-based to mathematically- informed genotyping decisions, with applications extending to any field requiring prospective quantification of prediction uncertainty under resource constraints.