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CINCALLI DB : a Field Network

News and Links

October 5, 2010

KERNELs, a database with informations on seeds stored at LEPSE was developped. It's an internal tool for the time being.


September, 25, 2010

Cincalli Interface will be opened for our partners as soon as possible. New web site is available. It presents the network of trials, the information system and the results obtained by the MAGE team


Phenodyn DB

The Web interface of the Phenodyn platform at LEPSE is now available here

Scientific Context

Nowadays, continuously is being accumulated evidence that global mean temperatures are increasing and the climate is becoming more erratic, with increased drought especially in certain arid and semi-arid areas. There is, consequently, a growing interest in developing cultivars that perform better under drought stress conditions. For evaluate the stability of the cultivars it is necessary to realize experiments in different environments, locations and/or years. However, this generates the well known phenomenon of genotype by environment interaction (GEI), which is an old problem of primary importance for quantitative genetics and its applications in breeding. Recent successes in QTL mapping have shifted the focus of GEI analysis from the genotype to gene level. Maize is particularly sensitive to drought stress occurring just before and during flowering when the crop's yield potential is defined. Extensive research into the tolerance of maize to drought stress at flowering has identified key secondary traits of grain yield, such as the ASI, improved ear fertility, stay-green and, to a lesser extent, leaf rolling (Bänziger et al. 2000, Bruce et al. 2002). Drought stress limits photosynthesis and reduces the flux of assimilates to the developing ears.

field kenya

The Network of Trials

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Cincalli stores two types of data as to observations: Environmental data with two temporal scales (hourly and daily) and Phenotypic data with two obervations levels (the plot and the plant)

Environmental data

The environmental data can be provided by meteorological stations independant of the trial, particularly for the variables about the air (temperature, humidity or evapotranspiration) or the radiation. These data are, most of the time, daily data. Few trials are fitted out this kind of devices that measure variables as the soil water potential or the soil temperature at the plot-level. It' from these systems that we hold data at the hour level. Hourly data can be averaged by day to get the same information in the Daily data table.

Phenotypic data

The observations realised at the plant level are treated and averaged at the plot level to have a complete dataset (all variables observed) for the elementary plot


Projects and Places

3 trial places for the Generation Challenge Program (GCP) :

  • Tlaltizapan (Mexico) in concert with the CIMMYT
  • New-Delhi (India) in concert with the Indian Agricultural Research Institute
  • Kiboko (Kenya) in concert with the Kenya Agricultural Research Institute

  • 4 trial places in France for the programs ANR Genoplante - WATERLESS, Dromadair and Progres Genetique :

  • Sainte-Pexine
  • Nérac
  • Mauguio
  • Le Magneraud

  • Cincalli Information System

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    The Database

    The schema of a database system is its structure described in a formal language. It defines the tables, the fields and relationships between the tables as presented below. You can refer the data dictionnary that describes tables and fields here

    schema data

    Tools of the Interface

    This interface aims to make the access to the data easier for the user thanks to selection tools and allows the computation of elaborated data associated to graphic functions. This set of tools is specific to the problematic of our research group.

  • Data Insertion
  • Data Consultation
  • Convertion of temporal data in degrees-days sum
  • Leaf Profiles representations
  • Histograms
  • Boxplots function environments
  • Relationships between variables



  • Results

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    From the raw data, a set of elaborated data and indexes is calculated to obtain a better characterization of the environment, the phenotype, and the relationship between the two ones.

    Leaf - Profiles

    leaf profile

    Leaf Appearance Rate

    LAR


    Leaf-profiles allow us to calculate the total leaf area of the plants and associating these data with the Leaves Appeareance Rates and the plants densities, we reach to estimate the Leaf Area Indexes (LAI) along the crop period. LAI is used also to calculte the water balance (RU) with an algorithm that takes too into account the water contributions (rainfalls and irrigation) and the evapotraspiration. We can like this have for each day, converted in degrees-days sum after emergence, a value in millimeters of the RU (in black) of the soil associated to the LAI (in red).

    LAIRU


    The LAI is used also to calculate the Intercepted Light by the plant, using too the daily data of Photosynthetically Active Radiation (PAR)

    Once these variables calculated for each daily step, they become precious tools to characterize the real conditions felt by the plants. For that, we consider these values at keys stages of the phenology as :

  • Maximum LAI
  • Water loss indexes for 3 periods of the crop cycle (from emergence to 9th leaf maturation, from 9th leave to male flowering time and from male flowering + 25 days)
  • Intercepted light at male flowering time

  • References

    Vargas, M., Domerg, C., Welcker, C., Tardieu, F., Ribaut, J.M., Araus, J.L., Gethi, J. (2009) Dissecting and modelling of QTLxE interaction in maize under drought : a QTL analysis of leaf growth and its impact on grain yield formation in typical tropical fields environments. (in redaction)


    Contacts

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  • Publication director: Tardieu François
  • Editorial director : Welcker Claude
  • Conception : Caroline Domerg
  • Technical follow-up :Vincent Nègre
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