Prediction of nitrogen mineralization in organically fertilized growing media for soil‐less production

International audience

إنجليزي. Background: Organic fertilizers derived from recycled materials and by-products are currently investigated as a way of freeing ourselves from synthetic chemical mineral fertilizers within the framework of the agroecological transition. These organic fertilizers have to undergo a mineralization process mainly carried out by microbes, so that the mineral elements can be consumed by the plants.Aims: The challenge consists in providing tools to predict available N coming from mineralization of organic fertilizers to better control the doses and the frequency of application.Methods: We developed and compared two predictive models of N mineralization of organic fertilizers, a multivariate statistical model and a first-order kinetic model. Temperature (4, 20, 28, and 40◦C) and humidity (−3.2, −10, and −31.6 kPa) were modulated and confronted to the response of four different growing media (GM) types and two organic fertilizers during a 49-day experiment. The input parameters tested for the statistical model were the amount of N in the fertilizer, the initial N content, temperature and humidity of the GM.Results: Both models satisfactorily predicted the mineral N content, even if they tended to overestimate it for low concentrations (mostly corresponding to low temperature,4◦C) and the first-order kinetic model overestimated it for the highest mineral N content(1000–1300 mg N kg−1). The two models were used to predict mineral N content on an independent dataset acquired under in situ conditions. The errors of prediction (RMSE) ranged between 220 and 256 mg N kg−1 according to the multivariate and first-order models, respectively.Conclusions: Two models have demonstrated satisfactory their ability to estimate the mineral nitrogen content in GM they need to be validated in more GM-fertilizer couples and in the presence of plant