Reducing environmental impacts of feed using multiobjective formulation: What benefits at the farm gate for pig and broiler production?

Feed production is the main contributor to several environmental impacts of livestock. To decrease environmental impacts of feed, those of feedstuffs should be considered during formulation. In particular, multiobjective feed formulation (MOF) can help reduce several environmental impacts simultaneously while keeping any increase in feed price moderate. The objective of this study was to assess environmental benefits of MOF at the farm gate for fattening pigs and broilers. For pigs, three feeding strategies were tested: classic 2-phase (2P), 2-phase with lower net energy content (2P-), and multiphase (MP). For broilers, two strategies were tested: classic 3-phase (3P) and 3-phase with higher digestible amino acid contents and lower metabolisable energy content (3P+). Diets were formulated using both least-cost formulation (LCF) and MOF, yielding six pig scenarios and four broiler scenarios. Environmental impacts at the farm gate were estimated using a modelling approach based on life cycle assessment. Indicators for six impact categories were then calculated: climate change (CC), cumulative non-renewable energy demand (CEDNR), acidification (AC), eutrophication (EU), land occupation (LO), and phosphorus demand (PD). As expected, MOF had lower farm-gate impacts than LCF (as much as -13%), but the degree of decrease varied by feeding strategy and impact. For pigs, MOF was equally effective in all strategies at reducing PD (-6 to -9%) and AC (-2%). In contrast, MOF was more effective in 2P and 2P- at decreasing CC (-5% to -7%), LO (-9% to -13%) and EU (-6% to -8%) than in MP (CC: -2%; LO: -4%; EU: -3%). The benefit of MOF was found greater in 2P (-7%) than in other pig strategies for CEDNR (-3 to +0%). For broilers, MOF was equally effective in both strategies tested at decreasing PD (-12%), AC (-2%), and EU (-4%). For CC and CEDNR, MOF was more effective in 3P (CC: -9%; CEDNR: -11%) than 3P+ (-6% for both impacts), but not for LO (+3% in 3P vs -1% in 3P+). These differences were due mainly to differences in animal performance (especially feed conversion ratio) among the strategies tested. Finally, in all scenarios, gross margin at the farm gate decreased with MOF comparatively to LCF (pigs: -3% to -11%); broilers: -7% to -11%). These results demonstrate the importance of comprehensive economic and environmental optimisation of feeding strategies by simultaneously considering feed impacts, animal performance, and manure management. To do so, further research is therefore required to develop new modelling tools.

MELODIE: a whole-farm model to study the dynamics of nutrients in dairy and pig farms with crops.

In regions of intensive pig and dairy farming, nutrient losses to the environment at farm level are a source of concern for water and air quality. Dynamic models are useful tools to evaluate the effects of production strategies on nutrient flows and losses to the environment. This paper presents the development of a new whole-farm model upscaling dynamic models developed at the field or animal scale. The model, called MELODIE, is based on an original structure with interacting biotechnical and decisional modules. Indeed, it is supported by an ontology of production systems and the associated programming platform DIESE. The biotechnical module simulates the nutrient flows in the different animal, soil and crops and manure sub-models. The decision module relies on an annual optimization of cropping and spreading allocation plans, and on the flexible execution of activity plans for each simulated year. These plans are examined every day by an operational management sub-model and their application is context dependent. As a result, MELODIE dynamically simulates the flows of carbon, nitrogen, phosphorus, copper, zinc and water within the whole farm over the short and long-term considering both the farming system and its adaptation to climatic conditions. Therefore, it is possible to study both the spatial and temporal heterogeneity of the environmental risks, and to test changes of practices and innovative scenarios. This is illustrated with one example of simulation plan on dairy farms to interpret the Nitrogen farm-gate budget indicator. It shows that this indicator is able to reflect small differences in Nitrogen losses between different systems, but it can only be interpreted using a mobile average, not on a yearly basis. This example illustrates how MELODIE could be used to study the dynamic behaviour of the system and the dynamic of nutrient flows. Finally, MELODIE can also be used for comprehensive multi-criterion assessments, and it also constitutes a generic and evolving framework for virtual experimentation on animal farming systems.

Modelling of manure production by pigs and NH3, N2O and CH4 emissions. Part I: animal excretion and enteric CH4, effect of feeding and performance.

A mathematical model was developed from literature data to predict the volume and composition of pig's excreta (dry and organic matter, C, N, P, K, Cu and Zn contents), and the emission of greenhouse gases (CH4 and CO2) though respiration and from the intestinal tract, for each physiological stage (post-weaning and fattening pigs and lactating and gestating sows). The main sources of variation considered in the model are related to animal performances (feed efficiency, prolificacy, body weight gain, etc.), to water and nutrient intakes and to housing conditions (ambient temperature). Model predictions were validated by using 19 experimental studies, most of them performed in conditions close to those of commercial farms. Validation results showed that the model is precise and robust when predicting slurry volume (R2 = 0.96), slurry N (R2 = 0.91), P (R2 = 0.95) and to a lesser extent dry matter (R2 = 0.75) contents. Faeces and urine composition (minerals and macronutrients) can also be precisely assessed, provided the composition and the digestibility of the feed are well known. Sensitivity analysis showed strong differences in CH4 emission and excretion amounts and composition according to physiological status, animal performance, temperature and diet composition. The model is an efficient tool to calculate nutrient balances at the animal level in commercial conditions, and to simulate the effect of production alternatives, such as feeding strategy or animal performance, on excreta production and composition. This is illustrated by simulations of three feeding strategies, which demonstrates important opportunities to limit environmental risks through diet manipulations.

Modelling of manure production by pigs and NH3, N2O and CH4 emissions. Part II: effect of animal housing, manure storage and treatment practices.

A model has been developed to predict pig manure evolution (mass, dry and organic matter, N, P, K, Cu and Zn contents) and related gaseous emissions (methane (CH4), nitrous oxide (N2O) and ammonia (NH3)) from pig excreta up to manure stored before spreading. This model forms part of a more comprehensive model including the prediction of pig excretion. The model simulates contrasted management systems, including different options for housing (slatted floor or deep litter), outside storage of manure and treatment (anaerobic digestion, biological N removal processes, slurry composting (SC) with straw and solid manure composting). Farmer practices and climatic conditions, which have significant effects on gaseous emissions within each option, have also been identified. The quantification of their effects was based on expert judgement from literature and local experiments, relations from mechanistic models or simple emission factors, depending on existing knowledge. The model helps to identify relative advantages and weaknesses for each system. For example, deep-litter with standard management practices is associated with high-greenhouse gas (GHG) production (+125% compared to slatted floor) and SC on straw is associated with high NH3 emission (+15% compared to slatted floor). Another important result from model building and first simulations is that farmer practices and the climate induce an intra-system (for a given infrastructure) variability of NH3 and GHG emissions nearly as high as inter-system variability. For example, in deep-litter housing systems, NH3 and N2O emissions from animal housing may vary between 6% and 53%, and between 1% and 19% of total N excreted, respectively. Thus, the model could be useful to identify and quantify improvement margins on farms, more precisely or more easily than current methodologies.