RESUMO
This research introduces a systematic framework for calculating sample size in studies focusing on enteric methane (CH4, g/kg of DMI) yield reduction in dairy cows. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a comprehensive search across the Web of Science, Scopus, and PubMed Central databases for studies published from 2012 to 2023. The inclusion criteria were: studies reporting CH4 yield and its variability in dairy cows, employing specific experimental designs (Latin Square Design (LSD), Crossover Design, Randomized Complete Block Design (RCBD), and Repeated Measures Design) and measurement methods (Open-circuit respirometry chambers (RC), the GreenFeed system, and the sulfur hexafluoride tracer technique), conducted in Canada, the United States and Europe. A total of 150 studies, which included 177 reports, met our criteria and were included in the database. Our methodology for using the database for sample size calculations began by defining 6 CH4 yield reduction levels (5, 10, 15, 20, 30, and 50%). Utilizing an adjusted Cohen's f formula and a power analysis we calculated the sample sizes required for these reductions in balanced LSD and RCBD reports from studies involving 3 or 4 treatments. The results indicate that within-subject studies (i.e., LSD) require smaller sample sizes to detect CH4 yield reductions compared with between-subject studies (i.e., RCBD). Although experiments using RC typically require fewer individuals due to their higher accuracy, our results demonstrate that this expected advantage is not evident in reports from RCBD studies with 4 treatments. A key innovation of this research is the development of a web-based tool that simplifies the process of sample size calculation (samplesizecalculator.ucdavis.edu). Developed using Python, this tool leverages the extensive database to provide tailored sample size recommendations for specific experimental scenarios. It ensures that experiments are adequately powered to detect meaningful differences in CH4 emissions, thereby contributing to the scientific rigor of studies in this critical area of environmental and agricultural research. With its user-friendly interface and robust backend calculations, this tool represents a significant advancement in the methodology for planning and executing CH4 emission studies in dairy cows, aligning with global efforts toward sustainable agricultural practices and environmental conservation.
RESUMO
Quantifying the effect of thermal stress on milk yields is essential to effectively manage present and future risks in dairy systems. Despite the existence of numerous heat indices designed to communicate stress thresholds, little information is available regarding the accuracy of different indices in estimating milk yield losses from both cold and heat stress at large spatiotemporal scales. To address this gap, we comparatively analyzed the performance of existing thermal indices in capturing US milk yield response to both cold and heat stress at the national scale. We selected 4 commonly used thermal indices: the temperature-humidity index (THI), black globe humidity index (BGHI), adjusted temperature-humidity index (THIadj), and comprehensive climate index (CCI). Using a statistical panel regression model with observational and reanalysis weather data from 1981 to 2020, we systematically compared the patterns of yield sensitivities and statistical performance of the 4 indices. We found that the US state-level milk yield variability was better explained by the THIadj and CCI, which combine the effects of temperature, humidity, wind, and solar radiation. Our analysis also reveals continuous and nonlinear responses of milk yields to a range of cold to heat stresses across all 4 indices. This implies that solely relying on fixed thresholds of these indices to model milk yield changes may be insufficient to capture cumulative thermal stress. Cold extremes reduced milk yields comparably to those affected by heat extremes on the national scale. Additionally, we found large spatial variability in milk yield sensitivities, implying further limitations to the use of fixed thresholds across locations. Moreover, we found decreased yield sensitivity to thermal stress in the most recent 2 decades, suggesting adaptive changes in management to reduce weather-related risks.
Assuntos
Temperatura Alta , Leite , Animais , Bovinos/fisiologia , Feminino , Indústria de Laticínios , Temperatura Baixa , Umidade , Lactação , Estados Unidos , Resposta ao Choque TérmicoRESUMO
Ten crossbred barrows weighting 20kg were allocated in five groups fed and on diets consisted of different total phosphorus (P) levels: 0.30 percent, 0.40 percent, 0.51 percent, 0.65 percent, and 0.73 percent. The animals were intravenously injected 7.4MBq of radioactive P (32P) and after seven days they were slaughtered for further analysis. The evaluated parameters were intake, excretion, specific activities, and flow of P in compartments (1-gut, 2-blood, 3-bone, and 4-soft tissue). Besides fecal losses, the kidneys played an import role in P regulation. The flows of P from tissue and gut to the blood were affected by P intake.
Foram usados 10 leitões machos castrados com média de peso vivo de 20kg, alojados em gaiolas metabólicas. O delineamento experimental foi inteiramente ao acaso e os tratamentos consistiram em níveis de fósforo (P) nas dietas: 0,30; 0,40; 0,51; 0,65 e 0,73 por cento. Os animais receberam injeção de 7,4 MBq de radiofósforo (32P) e após sete dias foram abatidos para posteriores análises. As variáveis avaliadas foram: ingestão, excreção, atividades específicas e fluxo de P nos compartimentos (1-trato digestivo, 2-corrente sanguínea, 3-tecidos moles e 4-ossos). Além das excreções fecais, os rins também representaram uma rota importante para a excreção do P. O fluxo de P dos tecidos e trato digestivo para o sangue não foi afetado pelo consumo de P. O modelo proposto foi eficiente para avaliar o fluxo de P.