Résumé : Human activities, especially the widespread use of synthetic fertilizers, have profoundly disrupted the natural nitrogen cycle. This disruption has led to severe environmental issues, including eutrophication, biodiversity loss, and the formation of marine dead zones. According to the Planetary Boundaries Framework, the safe threshold for nitrogen input into the environment has already been largely exceeded. Addressing this imbalance is, therefore, a necessity. In this context, optimizing fertilization is a key step toward restoring balance and moving towards more sustainable agricultural systems.
To achieve this goal, it is essential to gain a deeper understanding of the behavior of nitrogen species in soil. One of the key processes in this cycle is nitrification, a biological process in which ammonium is converted into nitrite and then into nitrate through the action of microorganisms (bacteria). In this regard, the development of models of nitrification represents a valuable tool to describe and predict the dynamics of the process. Nevertheless, the parameters of such models are highly sensitive to multiple environmental and biological factors, reflecting the inherent complexity of living systems. This preliminary work aims at identifying a set of parameters of a dynamical model of the nitrification process using a experimental dataset consisting in concentration data of nitrogen species obtained under controlled laboratory conditions.
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