Calibration of the EU-Rotate_N model with measured C and N mineralization from potential fertilizers and evaluation of its prediction of crop and soil data from a vegetable field trial

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Mechanistic models are useful tools for understanding and taking account of the complex, dynamic processes such as carbon (C) and nitrogen (N) turnover in soil and crop growth. In this study, the EU-Rotate_N model was first calibrated with measured C and N mineralization from nine potential fertilizer resources decomposing at controlled soil temperature and moisture. The materials included seaweeds, wastes from the food industry, food waste anaerobically digested for biogas production, and animal manure. Then the model's ability to predict soil and crop data in a field trial with broccoli and potato was evaluated. Except for seaweed, up to 68% of added C and 54–86% of added N was mineralized within 60 days under controlled conditions. The organic resources fell into three groups: seaweed, high-N industrial wastes, and materials with high initial content of mineral N. EU-Rotate_N was successfully calibrated for the materials of industrial origin, whereas seaweeds, anaerobically digested food waste and sheep manure were challenging. The model satisfactorily predicted dry matter (DM) and N contents (root mean square; RMSE: 0.11–0.32) of the above-ground part of broccoli fertilized with anaerobically digested food waste, shrimp shell pellets, sheep manure and mineral fertilizers but not algal meal. After adjusting critical %N for optimum growth, potato DM and N contents were also predicted quite well (RMSE: 0.08–0.44). In conclusion, the model can be used as a learning and decision support tool when using organic materials as N fertilizer, preferably in combination with other models and information from the literature.

OriginalsprogEngelsk
Artikelnummer126336
TidsskriftEuropean Journal of Agronomy
Vol/bind129
Antal sider13
ISSN1161-0301
DOI
StatusUdgivet - 2021

Antal downloads er baseret på statistik fra Google Scholar og www.ku.dk


Ingen data tilgængelig

ID: 275485963