Nutritional Evaluation of Tropical Forage Grass Alone and Grass-Legume Diets to Reduce in vitro Methane Production

Forage grass nutritional quality directly affects animal feed intake, productivity, and enteric methane (CH4) emissions. This study evaluated the nutritional quality, in vitro enteric CH4 emission potential, and optimization of diets based on two widely grown tropical forage grasses either alone or mixed with legumes. The grasses Urochloa hybrid cv. Cayman (UHC) and U. brizantha cv. Toledo (UBT), which typically have low concentrations of crude protein (CP), were incubated in vitro either alone or mixed with the legumes Canavalia brasiliensis (CB) and Leucaena diversifolia (LD), which have higher CP concentrations. Substitution of 30% of the grass dry matter (DM) with CB or LD did not affect gas production or DM degradability. After 96h of incubation, accumulated CH4 was 87.3mg CH4 g−1 DM and 107.7mg CH4 g−1 DM for the grasses alone (UHC and UBT, respectively), and 100.7mg CH4 g−1 DM and 113.2mg CH4 g−1 DM for combined diets (70% grass, 15% CB, and 15% LD). Diets that combined legumes (CB or LC) and grass (UHC or UBT) had higher CP contents, gross, and metabolizable energy (GE, ME, respectively) densities, as well as lower concentrations of neutral detergent fiber (NDF) and acid detergent lignin (ADL). The ME and nutritional variables such as NFD, tannins (T), and CP showed a positive correlation with in vitro net gas production, while ruminal digestibility was affected by CP, ADL, T, and GE. Optimal ratios of components for ruminant diets to reduce rumen net gas production and increase protein content were found with mixtures consisting of 60% grass (either UHC or UBT), 30% CB, and 10% LD. However, this ratio did not result in a decrease in CH4 production

Ambition meets reality:Achieving GHG emission reduction targets in the livestock sector of Latin America

Livestock production is a very relevant source of income and agricultural greenhouse gas (GHG) emissions in Colombia, Brazil, Argentina, Costa Rica, Uruguay, Mexico, and Peru. Several management and technological options with enteric methane mitigation potential have been evaluated and their scaling is anticipated to contribute toward achieving GHG emission reduction targets in the framework of the Paris Agreement. Yet, widespread adoption of promising mitigation options remains limited, raising questions as to whether envisaged emission reduction targets are achievable. Using findings from local studies, we explore the mitigation potentials of technologies and management practices currently proposed to mitigate enteric methane emissions from cattle production systems in the higher emitting countries of Latin America. We then discuss barriers for adopting innovations that significantly reduce cattle-based enteric methane emissions and the major shifts in policy and practice that are needed to raise national ambitions in the high emitting countries. Using the latest science and current thinking, we provide our perspective on an inclusive approach and re-imagine how the academic, research, business and public policy sectors can support and incentivize the changes needed to raise the level of ambition and achieve sustainable development goals (SDG), considering actions from the farm to the national scale

Benefits of Leucaena diversifolia in grazing steer’s diet: performance, methane and fatty acids

Leucaena diversifolia (Ld) is a legume species that has received little attention in terms of its nutritive value, methane (CH4) emissions, and impact on meat quality. To address this gap, a study was conducted to compare the performance, CH4 emissions, and fatty acid content of steers grazing on a monoculture of tropical grass Urochloa hybrid cv. Cayman versus a combination of Cayman and Ld. Over a period of 15 months, 14 Angus crossbred steers weighing an average of 374±7.5 kg were used in the study, with half of them grazing only Cayman grass and the other half grazing on a combination of Cayman and Ld at a ratio of 74:26. Live weight gain was recorded and CH4 emissions were measured after the animal productivity test. Meat quality and fatty acid profiles were measured after the steers were slaughtered. The results showed that steers grazing on a combination of Cayman and Ld consumed more dry matter, crude protein, and energy per day than those grazing on grass alone, and this difference was still evident when digestibility was considered (P≤0.05). Moreover, animals grazing on a combination of Cayman and Ld weighed an average of 63 kg more at the end of the experiment compared to those grazing only Cayman (466 vs. 403 kg; P≤0.05). Interestingly, animals that consumed only Cayman grass emitted more CH4 than those that included Ld in their diet (168 vs. 144 g/d; P≥0.05). The total polyunsaturated, monounsaturated, and saturated fatty acid concentrations in the meat did not differ between the two groups (P≥0.05). In conclusion, incorporating Ld in the diet of grazing steers can increase nutrient intake (protein and energy) and animal productivity without affecting daily net CH4 emissions or fatty acid concentrations in the meat. This study sheds light on the potential benefits of legume inclusion in animal diets and highlights the need for further research in this area

Strategies to achieve the GHG Mitigation Goals of the livestock sector in Latin America

Livestock production is a fundamental source of income and greenhouse gas (GHG) emissions in Latin American countries. 20 percent of the region's emissions come from agriculture, 70 percent of which comes from livestock. There are several management and technology options with enteric methane mitigation potential that have been evaluated and their scale is expected to contribute to achieving the GHG emission reduction targets under the Paris Agreement. These technologies include management of the animal diet, reproductive control, administration of supplements, and reduction of the age at slaughter, among others. However, widespread adoption of promising mitigation options remains limited, raising questions about whether the planned emission reduction targets are achievable. Using the results of local studies, we have explored the mitigation potentials of currently proposed management technologies and practices to mitigate enteric methane emissions from livestock production systems in Latin American countries with the highest emissions. We then discuss the barriers to adopting innovations that significantly reduce enteric methane emissions from livestock and the main changes in policies and practices necessary to raise national ambitions in high-emission countries. Drawing on today's latest science and thought, we take our perspective to an inclusive approach and reimagine how the academic, research, business and public policy sectors can support and incentivize the changes necessary to raise the level of ambition and achieve goals of sustainable development, taking into account actions from the farm to the national scale. Some improvements identified and that need to be made are improving access to information through effective technology transfer plans, access to financial products by small producers, and establishing seed multiplication systems for fodder materials

In-sample forecasting: A brief review and new algorithms

Statistical methods often distinguish between in-sample and out-of-sample approaches. In particular this is the case when time is involved. Then often time series methods are proposed that extrapolate past patterns into the future via complicated recursion formulas. Standard statistical inference is on the other hand concerned with estimating parameters within the given sample. This review paper is about a statistical methodology, where all parameters are estimated in-sample while producing a forecast out-of-sample without recursion or extrapolation. A new super-simulation algorithm ensures a faster implementation of the simplest and perhaps most important version of in-sample forecasting

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder