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MERCI: a simple method and decision-support tool to estimate availability of nitrogen from a wide range of cover crops to the next cash crop

Abstract Background and aims Cover crops can efficiently increase nitrogen (N) recycling in agroecosystems. By providing a green-manure effect for the next crop, they allow reduced mineral fertilisation. We developed a decision-support tool, called MERCI, to predict N available from cover crop residues over time, from a single measurement of fresh shoot biomass. Methods We coupled a large experimental database from France with a simulation experiment using the soil-crop model STICS. More than 25 000 measurements of 74 species of cover crops as a sole crop or bispecific mixtures were collected. Linear regression models, at the species, family or entire-database level depending on the data available, were built to predict dry biomass, N amount and C:N ratio. Dynamics of N mineralized and leaching from cover crop residues were predicted at 24 contrasting sites as a function of the biomass, carbon (C):N ratio and termination date. Results Correlations between fresh biomass, dry biomass and N amounts in experimental data were strong (r = 0.80-0.96), and predicted N amounts in fresh shoot biomass were relatively accurate. Percentages of N mineralized and leached simulated by STICS were explained mainly by the C:N ratio, site and number of months after termination, but to different degrees. Conclusion MERCI is an easy and robust decision-support tool for predicting N release in the field, and could thus be adopted by advisors and farmers to improve management of nutrient recycling in temperate arable cropping systems.
- Centre de Coopération Internationale en Recherche Agronomique pour le Développement France
- National Research Institute for Agriculture, Food and Environment France
- Agroecology France
- Arvalis - Institut du Végétal France
- Département Sciences sociales, agriculture et alimentation, espace et environnement France
http://aims.fao.org/aos/agrovoc/c_24242, Mineralization, STICS model, lessivage du sol, [SDV]Life Sciences [q-bio], F60 - Physiologie et biochimie végétale, agroécologie, http://aims.fao.org/aos/agrovoc/c_15591, Biomass Green-manure Carbon Mineralization STICS model, modèle de simulation, 333, 630, plante de couverture, http://aims.fao.org/aos/agrovoc/c_3081, biomasse, http://aims.fao.org/aos/agrovoc/c_36669, Biomass, banque de données, système de culture, http://aims.fao.org/aos/agrovoc/c_16118, http://aims.fao.org/aos/agrovoc/c_1936, U10 - Informatique, mathématiques et statistiques, résidu de récolte, http://aims.fao.org/aos/agrovoc/c_4848, http://aims.fao.org/aos/agrovoc/c_24833, Green-manure, agroécosystème, Carbon, http://aims.fao.org/aos/agrovoc/c_92381, [SDV] Life Sciences [q-bio], http://aims.fao.org/aos/agrovoc/c_926, teneur en éléments minéraux, http://aims.fao.org/aos/agrovoc/c_1971, F04 - Fertilisation
http://aims.fao.org/aos/agrovoc/c_24242, Mineralization, STICS model, lessivage du sol, [SDV]Life Sciences [q-bio], F60 - Physiologie et biochimie végétale, agroécologie, http://aims.fao.org/aos/agrovoc/c_15591, Biomass Green-manure Carbon Mineralization STICS model, modèle de simulation, 333, 630, plante de couverture, http://aims.fao.org/aos/agrovoc/c_3081, biomasse, http://aims.fao.org/aos/agrovoc/c_36669, Biomass, banque de données, système de culture, http://aims.fao.org/aos/agrovoc/c_16118, http://aims.fao.org/aos/agrovoc/c_1936, U10 - Informatique, mathématiques et statistiques, résidu de récolte, http://aims.fao.org/aos/agrovoc/c_4848, http://aims.fao.org/aos/agrovoc/c_24833, Green-manure, agroécosystème, Carbon, http://aims.fao.org/aos/agrovoc/c_92381, [SDV] Life Sciences [q-bio], http://aims.fao.org/aos/agrovoc/c_926, teneur en éléments minéraux, http://aims.fao.org/aos/agrovoc/c_1971, F04 - Fertilisation
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