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Dernière mise à jour : Mai 2018

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Welcome to ECOSYS

UMR ECOSYS - Ecologie fonctionnelle et écotoxicologie des agroécosystèmes

PROLAB Project

2013-2016

projet PROLAB
© INRA
Laboratory characterization of organic waste produced in the laboratory to predict their behavior in the field

Funding :

ADEME

Coordinator :

S. Houot, INRA UMR EcoSys Grignon

Partners:

INRA SAS Rennes, INRA Reims, INRA Laon, LDAR Laon, ESITPA Rouen, CIRAD La Réunion, Arvalis, Rittmo.

Abstract :

The recycling of organic waste products (PRO) on cropped soils contributes to crop fertilization (fertilizer value) and at maintaining soil organic matter stocks  (organic amendment).

The project Prolab aims to (1)  highlight the effects of PRO preparation methods on the analytical results of PRO, (2)  define the transposition of carbon and nitrogen mineralization during incubation lab towards field conditions to parameterize decision support tools, (3)  define protocols of organic matter fractionation adapted to all types of PRO and extrapolate a new index of residual organic carbon (Iroc, Lashermes et al., 2009) to any type of PRO, (4) assess determinants of ammonia volatilization risks after application of PRO and finally (5) predict N2O emissions after application. The characterizations cover 7 PRO representative of the main classes of encountered PRO and of the diversity of existing matrices.

The deliverables will include analytical procedures to characterize the main PRO adapted to their state (dry matter content, mineral N) and their origin (digestate, sludge compost, ...) to provide analytical results for PRO representative of the main spread PRO in field conditions and ensure the transposition of the characterizations from the lab towards the field conditions in order to predict their evolution after application. These defined procedures will subsequently be applied on a large number of PRO to complete a typology of C and N transformations, adapted to the diversity of PRO and making possible the environmental balance of their use in agriculture based on the C and N dynamics in field condition after their application.