Anna Gras

Individual-based modeling of carbon and nitrogen dynamics in soils:: parameterization and sensitivity analysis of abiotic components

The need to predict with reasonable accuracy the fate of soil C and N compounds in soils in response to climate change is stimulating interest in a new generation of microscale models of soil ecosystem processes. Essential to the development of such models is the ability to describe the growth and metabolism of small numbers of individual microorganisms. In this context, the key objective of the research described in this article was to further develop an individual-based soil organic matter (SOM) model, INDISIM-SOM, first proposed a few years ago, and to assess its performance with a broader data set than previously considered. The INDISIM-SOM models the dynamics and evolution of C and N associated with organic matter in soils. The model involves a number of state variables and parameters related to SOM and microbial activity, including growth and decay of microbial biomass, temporal evolution of mineralized intermediate C and N, mineral N in ammonium and nitrate, carbon dioxide, and O2. Simulation results demonstrate good fit of the model to experimental data from laboratory incubation experiments performed on three different types of Mediterranean soils. A second objective was to determine the sensitivity of the model toward its various parameters. Sensitivity was small for several of the parameters, suggesting possible simplifications of the model for specific uses, but was significant particularly for the parameter associated with the fraction of the soil C present in the biomass. These results suggest that research should be focused on improving the measurement of this latter parameter.

Individual-based modelling and simulation of microbial processes: yeast fermentation and multi-species composting

Controlled microbial activity is the core of many industrial processes. Such dynamic microbial processes must be carefully studied to optimize their application. They are usually tackled by means of continuous mathematical modelling at the population level (top-down). An alternative approach is individual-based modelling (IbM) (bottom-up). INDISIM is a discrete and spatially explicit IbM. It sets the rules that govern each microbe and its interaction with its local environment, as well as the significant environmental processes. Then it performs simulations that include a large number of microbes, and the behaviour of the whole system emerges. The rules are changed to reproduce the behaviour of microbes depending on the system to be studied. Two adaptations of INDISIM to study yeast fermentations and multi-species composting are presented in this article (INDISIM-YEAST and INDISIM-COMP), proof of INDISIMs versatility. A few representative results are also shown.

Population analysis of a commercial Saccharomyces cerevisiae wine yeast in a batch culture by electric particle analysis, light diffraction and flow cytometry

Data from electric particle analysis, light diffraction and flow cytometry analysis provide information on changes in cell morphology. Here, we report analyses of Saccharomyces cerevisiae populations growing in a batch culture using these techniques. The size distributions were determined by electric particle analysis and by light diffraction in order to compare their outcomes. Flow cytometry parameters forward (related to cell size) and side (related to cell granularity) scatter were also determined to complement this information. These distributions of yeast properties were analysed statistically and by a complexity index. The cell size of Saccharomyces at the lag phase was smaller than that at the beginning of the exponential phase, whereas during the stationary phase, the cell size converged with the values observed during the lag phase. These experimental techniques, when used together, allow us to distinguish among and characterize the cell size, cell granularity and the structure of the yeast population through the three growth phases. Flow cytometry patterns are better than light diffraction and electric particle analysis in showing the existence of subpopulations during the different phases, especially during the stationary phase. The use of a complexity index in this context helped to differentiate these phases and confirmed the yeast cell heterogeneity.

Explaining low farm‐gate prices in the Catalan wine sector

Purpose – The viticulture sector represents a conspicuous part of the Catalan agricultural and agro food sector. While wine production in Catalonia has been increasing markedly over the first half of the 2000s, prices that grape producers receive have steadily declined threatening their standard of living. This has raised social and political concerns and calls for a better understanding of its causes. This paper aims to comprehend the sources of such price crisis.Design/methodology/approach – A Delphi survey is conducted during 2005 among a panel of 27 wine sector experts.Findings – The results find that experts agree in considering wine surplus and imperfect price transmission as the main causes determining low farm‐gate prices in the Catalan wine sector.Originality/value – The analysis aims at characterizing the food marketing chain for wine products in Catalonia by quantifying the trade flows occuring within this chain. This paper is the first attempt in Catalonia and Spain to quantify and characteriz...

INDISIM-Paracoccus, an individual-based and thermodynamic model for a denitrifying bacterium

We have developed an individual-based model for denitrifying bacteria. The model, called INDISIM-Paracoccus, embeds a thermodynamic model for bacterial yield prediction inside the individual-based model INDISIM, and is designed to simulate the bacterial cell population behavior and the product dynamics within the culture. The INDISIM-Paracoccus model assumes a culture medium containing succinate as a carbon source, ammonium as a nitrogen source and various electron acceptors such as oxygen, nitrate, nitrite, nitric oxide and nitrous oxide to simulate in continuous or batch culture the different nutrient-dependent cell growth kinetics of the bacterium Paracoccus denitrificans. The individuals in the model represent microbes and the individual-based model INDISIM gives the behavior-rules that they use for their nutrient uptake and reproduction cycle. Three previously described metabolic pathways for P. denitrificans were selected and translated into balanced chemical equations using a thermodynamic model. These stoichiometric reactions are an intracellular model for the individual behavior-rules for metabolic maintenance and biomass synthesis and result in the release of different nitrogen oxides to the medium. The model was implemented using the NetLogo platform and it provides an interactive tool to investigate the different steps of denitrification carried out by a denitrifying bacterium. The simulator can be obtained from the authors on request.

INDISIM-SOM, An Individual-Based Model To Study Shortterm Evolutions Of Carbon And Nitrogen Pools Related To Microbial Activity In Soil Organic Matter

This work deals with the implementation of a soil organic matter model in an individual-based modelling framework. The simulator INDISIM-SOM models the dynamics of carbon and nitrogen related to soil organic matter and the soil microbial activity by using a discrete simulation. This simulation model controls the activity of group of microbial cells in a space divided into square cells where amounts of different types of organic compounds are also controlled. Different metabolic pathways and sources of C and N the microorganisms can use are identified. INDISIM-SOM deals with the mineralization and nitrification of C and N and, the activity of heterotrophic microorganisms and nitrifier bacteria. The calibration of the simulation model has made use of data from laboratory incubation experiments performed on three different types of Mediterranean soils.

MbT-Tool: An open-access tool based on Thermodynamic Electron Equivalents Model to obtain microbial-metabolic reactions to be used in biotechnological process

Modelling cellular metabolism is a strategic factor in investigating microbial behaviour and interactions, especially for bio-technological processes. A key factor for modelling microbial activity is the calculation of nutrient amounts and products generated as a result of the microbial metabolism. Representing metabolic pathways through balanced reactions is a complex and time-consuming task for biologists, ecologists, modellers and engineers. A new computational tool to represent microbial pathways through microbial metabolic reactions (MMRs) using the approach of the Thermodynamic Electron Equivalents Model has been designed and implemented in the open-access framework NetLogo. This computational tool, called MbT-Tool (Metabolism based on Thermodynamics) can write MMRs for different microbial functional groups, such as aerobic heterotrophs, nitrifiers, denitrifiers, methanogens, sulphate reducers, sulphide oxidizers and fermenters. The MbT-Tools code contains eighteen organic and twenty inorganic reduction-half-reactions, four N-sources (NH4+, NO3−, NO2−, N2) to biomass synthesis and twenty-four microbial empirical formulas, one of which can be determined by the user (CnHaObNc). MbT-Tool is an open-source program capable of writing MMRs based on thermodynamic concepts, which are applicable in a wide range of academic research interested in designing, optimizing and modelling microbial activity without any extensive chemical, microbiological and programing experience.

Population analysis of a commercial Saccharomyces cerevisiae wine yeast in a batch culture by electric particle analysis, light diffraction and flow cytometry: Distributional analysis of S. cerevisiae in batch culture

Data from electric particle analysis, light diffraction and flow cytometry analysis provide information on changes in cell morphology. Here, we report analyses of Saccharomyces cerevisiae populations growing in a batch culture using these techniques. The size distributions were determined by electric particle analysis and by light diffraction in order to compare their outcomes. Flow cytometry parameters forward (related to cell size) and side (related to cell granularity) scatter were also determined to complement this information. These distributions of yeast properties were analysed statistically and by a complexity index. The cell size of Saccharomyces at the lag phase was smaller than that at the beginning of the exponential phase, whereas during the stationary phase, the cell size converged with the values observed during the lag phase. These experimental techniques, when used together, allow us to distinguish among and characterize the cell size, cell granularity and the structure of the yeast population through the three growth phases. Flow cytometry patterns are better than light diffraction and electric particle analysis in showing the existence of subpopulations during the different phases, especially during the stationary phase. The use of a complexity index in this context helped to differentiate these phases and confirmed the yeast cell heterogeneity.