Exploring Rotational Grazing and Crossbreeding as Options for Beef Production to Reduce GHG Emissions and Feed-Food Competition through Farm-Level Bio-Economic Modeling.

In the context of a growing population, beef production is expected to reduce its consumption of human-edible food and its contribution to global warming. We hypothesize that implementing the innovations of fast rotational grazing and redesigning existing production systems using crossbreeding and sexing may reduce these impacts. In this research, the bio-economic model FarmDyn is used to assess the impact of such innovations on farm profit, workload, global warming potential, and feed-food competition. The innovations are tested in a Belgian system composed of a Belgian Blue breeder and a fattener farm, another system where calves raised in a French suckler cow farm are fattened in a farm in Italy, and third, a German dairy farm that fattens its male calves. The practice of fast rotational grazing with a herd of dairy-to-beef crossbred males is found to have the best potential for greenhouse gas reduction and a reduction of the use of human-edible food when by-products are available. Crossbreeding with early-maturing beef breeds shows a suitable potential to produce grass-based beef with little feed-food competition if the stocking rate considers the grassland yield potential. The results motivate field trials in order to validate the findings.

Quantification of methane emitted by ruminants: a review of methods.

The contribution of greenhouse gas (GHG) emissions from ruminant production systems varies between countries and between regions within individual countries. The appropriate quantification of GHG emissions, specifically methane (CH4), has raised questions about the correct reporting of GHG inventories and, perhaps more importantly, how best to mitigate CH4 emissions. This review documents existing methods and methodologies to measure and estimate CH4 emissions from ruminant animals and the manure produced therein over various scales and conditions. Measurements of CH4 have frequently been conducted in research settings using classical methodologies developed for bioenergetic purposes, such as gas exchange techniques (respiration chambers, headboxes). While very precise, these techniques are limited to research settings as they are expensive, labor-intensive, and applicable only to a few animals. Head-stalls, such as the GreenFeed system, have been used to measure expired CH4 for individual animals housed alone or in groups in confinement or grazing. This technique requires frequent animal visitation over the diurnal measurement period and an adequate number of collection days. The tracer gas technique can be used to measure CH4 from individual animals housed outdoors, as there is a need to ensure low background concentrations. Micrometeorological techniques (e.g., open-path lasers) can measure CH4 emissions over larger areas and many animals, but limitations exist, including the need to measure over more extended periods. Measurement of CH4 emissions from manure depends on the type of storage, animal housing, CH4 concentration inside and outside the boundaries of the area of interest, and ventilation rate, which is likely the variable that contributes the greatest to measurement uncertainty. For large-scale areas, aircraft, drones, and satellites have been used in association with the tracer flux method, inverse modeling, imagery, and LiDAR (Light Detection and Ranging), but research is lagging in validating these methods. Bottom-up approaches to estimating CH4 emissions rely on empirical or mechanistic modeling to quantify the contribution of individual sources (enteric and manure). In contrast, top-down approaches estimate the amount of CH4 in the atmosphere using spatial and temporal models to account for transportation from an emitter to an observation point. While these two estimation approaches rarely agree, they help identify knowledge gaps and research requirements in practice.

There is a need to accurately and precisely quantify greenhouse gas (GHG) emissions, specifically methane (CH4), to ensure correct reporting of GHG inventories and, perhaps more importantly, determine how to best mitigate CH4 emissions. The objective of this study was to review existing methods and methodologies to quantify and estimate CH4 emissions from ruminants. Historically, most techniques were developed for specific purposes that may limit their widespread use on commercial farms and for inventory purposes and typically required frequent calibration and equipment maintenance. Whole animal and head respiration chambers, spot sampling techniques, and tracer gas methods can be used to measure enteric CH4 from individual animals, but each technique has its own inherent limitations. The measurement of CH4 emissions from manure depends on the type of storage, animal housing, CH4 concentration inside and outside the boundaries of the area of interest, and ventilation rate, which is likely the most complex variable creating many uncertainties. For large-scale areas, aircraft, drones, and satellites have been used in association with the tracer flux method, inverse modeling, imagery, and LiDAR (Light Detection and Ranging), but research is lagging in validating these methods. Bottom-up approaches to estimating CH4 emissions rely on empirical or mechanistic modeling to quantify the contribution of individual sources. Top-down approaches estimate the amount of CH4 in the atmosphere using spatial and temporal models to account for transportation from an emitter to an observation point.

Consequential environmental life cycle assessment of a farm-scale biogas plant.

Producing biogas via anaerobic digestion is a promising technology for meeting European and regional goals on energy production from renewable sources. It offers interesting opportunities for the agricultural sector, allowing waste and by-products to be converted into bioenergy and bio-based materials. A consequential life cycle assessment (cLCA) was conducted to examine the consequences of the installation of a farm-scale biogas plant, taking account of assumptions about processes displaced by biogas plant co-products (power, heat and digestate) and the uses of the biogas plant feedstock prior to plant installation. Inventory data were collected on an existing farm-scale biogas plant. The plant inputs are maize cultivated for energy, solid cattle manure and various by-products from surrounding agro-food industries. Based on hypotheses about displaced electricity production (oil or gas) and the initial uses of the plant feedstock (animal feed, compost or incineration), six scenarios were analyzed and compared. Digested feedstock previously used in animal feed was replaced with other feed ingredients in equivalent feed diets, designed to take account of various nutritional parameters for bovine feeding. The displaced production of mineral fertilizers and field emissions due to the use of digestate as organic fertilizer was balanced against the avoided use of manure and compost. For all of the envisaged scenarios, the installation of the biogas plant led to reduced impacts on water depletion and aquatic ecotoxicity (thanks mainly to the displaced mineral fertilizer production). However, with the additional animal feed ingredients required to replace digested feedstock in the bovine diets, extra agricultural land was needed in all scenarios. Field emissions from the digestate used as organic fertilizer also had a significant impact on acidification and eutrophication. The choice of displaced marginal technologies has a huge influence on the results, as have the assumptions about the previous uses of the biogas plant inputs. The main finding emerging from this study was that the biogas plant should not use feedstock that is intended for animal feed because their replacement in animal diets involves additional impacts mostly in terms of extra agricultural land. cLCA appears to be a useful instrument for giving decision-makers information on the consequences of introducing new multifunctional systems such as farm-scale biogas plants, provided that the study uses specific local data and identifies displaced reference systems on a case-by-case basis.

Long-term survival and late graft loss in pediatric liver transplant recipients--a 15-year single-center experience.

Increasing numbers of children undergo successful liver transplantation. Limited data exist on long-term survival and late graft loss. Survival and graft loss were studied in 376 primary liver graft recipients who survived more than 3 months after transplantation (80.5% of all primary graft recipients). Patient records were reviewed retrospectively for causes of graft loss. Risk factors were identified by analyzing graft, recipient, and posttransplant variables using multivariate Cox regression. One-, 5-, and 10-year actuarial graft survival rates in the study population were 94.6%, 87.3%, and 86.3%, respectively. Corresponding patient survival rates were 95.7%, 91.4%, and 90.4%. Forty-seven (12.5%) grafts were lost subsequently, 15 by patient death with preserved graft function. Survival rate after late retransplantation was 63.3%. Causes of late graft loss were infection (21.2%), posttransplant lymphoproliferative disease (PTLD, 21.2%), chronic rejection (17%), biliary complications (14.8%), and recurrence of malignant disease (8.5%). Independent risk factors for late graft loss and patient death included liver malignancy as primary disease, steroid resistant rejection, and PTLD. Graft loss rate was significantly increased for reduced-size grafts. Patients undergoing transplantation after 1991 and recipients of full-size grafts were more likely to survive. In conclusion, the long-term outcome for pediatric primary liver graft recipients surviving the early postoperative period is excellent except for patients with liver malignancy. There is no increased risk of late graft loss with the use of split or living related donor grafts. Technical complications are only a minor factor in late graft loss, but complications related to immunosuppression and infection remain a major hazard and must be addressed.