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.

The increasing human population and demand for animal food products raise the issue of impacts of animal systems on food security caused by their use of human-edible feed and/or tillable land. The utility of replacing animal systems with potential food-crop systems needs to be assessed but is associated with many uncertainties. Some metrics analyse the contribution of current animal systems to food security, especially the dimension of food availability. These methods address feed conversion efficiency (i.e. total (‘gross’) or human-edible (‘net’)) or the efficiency of agricultural land use (i.e. total, permanent grassland, and tillable land) but never both simultaneously. The purpose of this study was to develop a new metric—‘net productivity’—to represent the performances of current animal systems more accurately by considering both the use of human-edible feed and agricultural land. Through a protein assessment, we analysed the ability of the existing and the new metrics to assess the performances of 111 dairy farms in Wallonia (Belgium). We found that net productivity was positively correlated with both metrics of feed conversion efficiency and negatively correlated with the three metrics of land use. To analyse the influence of farm characteristics, we grouped the farms into four clusters using k -means clustering based on these metrics of contribution to food security and then performed redundancy analysis to select the most influential farm characteristics aiming to highlight contrasted farm strategies. The highest net productivity was reached by an ‘intensive and net efficient’ farm strategy, which had intensive grass-based management, high milk production per cow, appropriate use of concentrates, and well-managed dairy followers (i.e. replacement heifers and calves). The newly developed metric of net productivity can be useful to quantify the contribution of dairy systems to food security by considering both the use of human-edible protein and agricultural land simultaneously.

Abstract 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.

Nutrient losses have to be avoided in agricultural systems for agronomic and environmental reasons. However, they are known to be potentially large and variable. Results from twenty nine trials aiming at quantifying nitrogen (N), phosphorus (P), potassium (K) and carbon (C) flows and losses from barn and manure storage for beef cattle (Belgian Blue double-muscled breed) were synthesized. They included variation in barn type (tied stall and deep litter), leading to contrasted manure types (respectively semi-solid manure and deep litter manure) of small groups (n = 4) of heifers or bulls. Despite uncertainties pointed out by non-zero P or K balances, we established for manure storage, a relation between K losses by flowing out as liquid and rainfalls: K lost (%K stored) = 100*(1-0.99*e((-0.00078*rainfalls) ((mm))); n = 28). We also emphasized, within the particular set of data treated, the effects of barn type (approached by STRAWr; kg straw kg(-1) DM in feed), manure storage duration (d), nitrogen in feed concentration (NFEED; g N kg(-1) DM) and storage temperature (degrees C) on N losses from the whole system (N lost (% N input) =-33.33 + 0.0869*storage duration+1.11*storage temperature+27.9*STRAWr+1.278*NFEED; r(2) = 0.700; n = 29) such as the strong relation between C and N losses during manure store per day of storage (N lost (% N stored d(-1))= 0.038 + 0.617*C lost (% C stored d(-1))). We also observed that, even if N and C inputs in the system were higher in deep litter systems due to straw supply, the amounts of N and C remaining in the manure after being stored were very similar, indicating higher losses of these nutrients from deep litter systems compared to tied stalls. These findings will further help in modeling cattle housing systems for nutrient cycling optimization. However, the relations established have to be validated for other tied stall and deep litter systems regarding the diversity in manure management for each barn type. Furthermore, when comparing manure provided under different housing systems, other agronomical (e.g. their sanitization due to heat increase when stored, ease of application to soil after storage) or environmental (e.g. greenhouse gas emissions) aspects have to be considered.

Life cycle assessment (LCA) is a useful tool for investigating the environmental performance of agricultural products. For many crop-based products, the agricultural production step shows substantial impacts in LCA results. Using the illustrative case of cereal production in Wallonia, Belgium, the study uses sensitivity analyses to explore the parameters to be adjusted in priority when conducting a local LCA for crop production, taking into account uncertainties tied to input and output inventory data and impact characterization factors.

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.

Mitigating the proportion of energy intake lost as methane could improve the sustainability and profitability of dairy production. As widespread measurement of methane emissions is precluded by current in vivo methods, the development of an easily measured proxy is desirable. An equation has been developed to predict methane from the mid-infrared (MIR) spectra of milk within routine milk-recording programs. The main goals of this study were to improve the prediction equation for methane emissions from milk MIR spectra and to illustrate its already available usefulness as a high throughput phenotypic screening tool. A total of 532 methane measurements considered as reference data (430 ± 129 g of methane/day) linked with milk MIR spectra were obtained from 165 cows using the SF6 technique. A first derivative was applied to the MIR spectra. Constant (P0), linear (P1) and quadratic (P2) modified Legendre polynomials were computed from each cows stage of lactation (days in milk), at the day of SF6 methane measurement. The calibration model was developed using a modified partial least-squares regression on first derivative MIR data points × P0, first derivative MIR data points × P1, and first derivative MIR data points × P2 as variables. The MIR-predicted methane emissions (g/day) showed a calibration coefficient of determination of 0.74, a cross-validation coefficient of determination of 0.70 and a standard error of calibration of 66 g/day. When applied to milk MIR spectra recorded in the Walloon Region of Belgium (≈2 000 000 records), this equation was useful to study lactational, annual, seasonal, and regional methane emissions. We conclude that milk MIR spectra has potential to be used to conduct high throughput screening of lactating dairy cattle for methane emissions. The data generated enable monitoring of methane emissions and production characteristics across and within herds. Milk MIR spectra could now be used for widespread screening of dairy herds in order to develop management and genetic selection tools to reduce methane emissions.

The emission of greenhouses gases (GHG) from ruminant production systems needs to be reduced. This can be achieved partly by better manure management, particularly for deep litter (DL) systems. Two contrasting removal frequency rates (1x, every 63.5 +/- 3.5 days; and 3x, every 23.1 +/- 1.5 days) were compared in a DL system for Belgian blue double-muscled heifers, focusing on CO2, CH4 and N2O emissions from the barn and during two manure storage periods, one mainly in autumn and the other mainly in winter. No significant effect (p = 0.447) of manure removal frequency on total GHG emissions was observed (1 x: 10.2 +/- 3.5; 3 x : 8.7 +/- 2.2 kg CO2 eq. kg(-1) live weight gain).The manure contributed significantly to total GHG emissions (average of 38.9 +/- 8.0% of CO2 eq.), emissions from the barn (4.0 +/- 0.7%) and manure store included (34.9 +/- 8.7%). Higher emissions (time 4.8 in CO2 eq.) from manure were observed when it was stored during the warmer period than the colder one. Large variations in emission pattern with the manure removal frequency rates were also observed, leading, potentially (not measured) to higher emissions from the 1 x treatment than the 3 x treatment for a longer storage period than the one tested in this experiment (63 +/- 1 days). Given the experimental choices, the variations in emission pattern observed indicated that mitigation options for GHG emissions from the barn and manure store related to manure removal frequency depend on manure storage duration and that keeping deep litter manure in barns without intermediate storage before spreading should be investigated. These options need to be confirmed through emission measurement during and after manure spreading in order to avoid a trade-off between emission stages. The relevance of such options in terms of agronomical concerns needs to be confirmed. (C) 2016 Elsevier B.V. All rights reserved.

Greenhouse gas emission intensity (GHGI; kilograms carbon dioxide equivalents/kilograms liveweight gain) have to be reduced so as to limit the impact of human activities on global warming while furnishing food to human. In this respect, performances of 654 Belgian Blue double-muscled bulls (BBdm) during their fattening phase were recorded. On this basis, their greenhouse gas emissions were modelled to estimate variation in GHGI and investigate mitigation options at that level. The relevance of theses option is discussed, taking into account the whole life and production system scales. Large variations (mean (s.d.)) were observed (from 7.2 (0.4) to 10.0 (0.7) kg carbon dioxide equivalents/kg liveweight gain) for, respectively, the 1st- and 4th-quantile groups defined for GHGI. Early culling, low liveweight and age at start of the fattening phase of the bulls would lead to a reduction of GHGI. Nevertheless, more than 32% of the variation remained unexplained. However, decision leading to reduction of GHG intensity at this stage of the life may be compensated in the early stage of BBdm. Attention is drawn on the necessity to encompass the whole life of BBdm for investigating mitigation options and on the sensitivity of the results on models and methodological choices.

The environmental impact of wheat production was assessed through Life Cycle Assessment (LCA). Local data were collected to characterize Walloon conventional and organic wheat production systems. Two functional units (FU) were investigated: 1kg of wheat grains at 15% humidity and 1ha used for wheat cropping. An uncertainty analysis assessed the significance of differences between conventional and organic systems. Using 1kg of grains as FU, results are not significantly different in global warming and cumulative energy demand. Very highly significant differences for soil acidification and eutrophication, and significant differences for agricultural land occupation were found to be in favor of conventional wheat production. Due to the high yield level in conventional farming (8.5 t/ha at 15% humidity against 4.5 t/ha for organic wheat), organic winter wheat has an equivalent or even, in some impact categories, a higher impact than conventional winter wheat. Using 1ha as FU, organic production is less impacting than conventional production, except for soil acidification and eutrophication. The choice of the FU has proven to be very sensitive. This study could be improved by accounting for rotation effects, by using more specific models to calculate emissions due to organic and mineral fertilization, and by accounting for carbon storage in soil.

Within the framework of the Optenerges project, funded under the Interreg IV program, the greenhouse gas (GHG) emissions of 62 cattle farms representative of the main production systems in the Province of Luxembourg in Wallonia, Belgium were assessed. The main goal of this study was to give reference values for GHG emission intensity in meat production systems based on grass (G) and on grass and maize (G-M). A second goal was to analyze emission variability in order to identify potential mitigation options. On average, for every kg live weight the G systems emitted 18.2 CO2 eq.. and the G-M systems 19.2 CO2 eq.. The difference reflected differences in feed and mineral fertilizer purchases, in manure emissions and in mineral fertilizer application. There were large variations in GHG emissions both between and within the two systems, particularly the latter. This variability was not due to the division of the farms into G and G-M systems, indeed production system types did not allow explaining the variation. When carbon credits were included in the assessment, there was an emission reduction of 31% and 23% for the G and G-M systems, respectively, indicating an opportunity for the systems using grassland to increase their advantage.

Comme souligne par Mazoyer et Roudart (2002), la mise en place de systemes de polyculture – elevage a permis d’accroitre la productivite des terres cultivees grâce au transfert de fertilite du saltus vers l’ager. Neanmoins, cette association n’a permis des augmentations significatives de rendements que suite au developpement d’une culture attelee lourde. En effet, celle-ci a permis la recolte de fourrages pour maintenir le cheptel en stabulation hivernale. Le fumier produit durant cette phase a alors pu etre transfere sur les terres afin d’y etre enfoui par labour. Suite a la fabrication d’engrais de synthese et au developpement de la traction mecanique, une specialisation des systemes et une dissociation des productions animales et vegetales a, a nouveau, eu lieu parallelement a une forte augmentation de la productivite du travail.

Uncertainties in environmental impacts of milk production related to model variables were investigated with Monte-Carlo simulation in a case study. Per kg of fat-and-protein-corrected milk produced, the 95% confidence interval of impacts was 6.2-10.4 g PO4eq, 10.1-25.6 g SO2eq, 1.1-1.9 kg CO2eq, -7.6-19.2 CTUe, 4.3-4.9 MJ and 1.11-1.28 m2yr for eutrophication, acidification, climate change, ecotoxicity, CED and land occupation respectively. Expressed as coefficients of variation, uncertainties ranged from 3% to 2097% as a function of the impact category. The most influential variables changed with impact category, except those related to the functional unit. Monte-Carlo simulation and sensitivity analysis help to identify variables requiring more accuracy and detect errors implementing multiple-variables models in calculation tools.

Model excreted nitrogen (N), phosphorus (P), carbon and potassium (K) distributions in cattle manures in function of the barn type

Durant l’entierete de leur cycle de production, les ruminants rejettent de maniere directe et indirecte les trois principaux gaz a effet de serre (Dioxyde de carbone CO2, methane CH4, Protoxyde d’azote N2 O). Les emissions directes sont principalement liees aux animaux, a leur gestion, aux processus de digestion et a la restitution des effluents d’elevage dans l’environnement. Les emissions indirectes sont principalement fonction des quantites et de la nature des intrants necessaires aux productions animales.

The diversity of beef cattle production systems in terms of diet, manure management and building design results in variation in greenhouse gas (GHG) emissions and the opportunities to reduce them. Within this context, we studied the effect of the varying proportions of concentrate (37-85% of DM) in the diet of Belgian Blue heifers on CH4 and N2O emissions from a tie-stall system (barn and solid manure storage). Trials were conducted over two consecutive periods in which manure was stored mainly in winter and spring. Increasing the proportions of concentrate in the diet reduced the GHG (CH4 + N2O) emissions from the barns from 8.5 +/- 1.6 to 1.9 +/- 0.4 kg CO2 eq/kg live-weight gain, but had not significant influence on the emissions from the stored solid manure. Seasonal variation in gas emissions was observed, with lower emissions from stored solid manure in winter than in spring (159 +/- 25 and 314 +/- 49 mg CO2, 0.14 +/- 0.02 and 2.47 +/- 0.78 mg CH4, and <0.01 and 0.24 +/- 0.09 mg N2O/kg of fresh manure stored/d of storage, respectively), indicating that manure storage in the warmer season should be avoided. The GHG (CH4 + N2O) emissions from stored solid manure, however, were less than 11% of the total emissions (barns + manure storage). The emphasis in these systems should therefore be on modelling and reducing direct CH4 emissions from cattle but feed production impact should also be included. The GHG emissions were validated using nutrient (C, K, P and ash) balances including CO2 and CH4 emissions for the C balance. (c) 2011 Elsevier B.V. All rights reserved.

In Europe, during the last 30 years, the decrease in sulphur (S) atmospheric depositions has led to S deficient grasslands. Concern for S fertilisation resulted in research about S fertilisation advices and definition of S nutritional diagnostic tools for plants. However, for grasses, S nutrition indicators are still discussed. We propose a diagnostic tool based upon linear relationships linking the sulphur and nitrogen (N) content of grasses. This diagnostic tool is built thanks to data from field and pot trials treated with an algorithm (Bolides) and discriminant analyses. The relationships allow the characterisation of the grass sulphur nutritional status following four categories: certainly sufficient, probably sufficient, probably deficient and certainly deficient. This relation based and tested on a large dataset from literature and own field trials allowed diagnosing correctly 94% of the sulphur sufficient grasses and 71% of the sulphur deficient grasses. (C) 2008 Elsevier B.V. All rights reserved.