Performance of process-based models for simulation of grain N in crop rotations across Europe

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43210%2F17%3A43912031" target="_blank" >RIV/62156489:43210/17:43912031 - isvavai.cz</a>

Alternative codes found

RIV/86652079:_____/17:00476501

Result on the web

<a href="https://doi.org/10.1016/j.agsy.2017.03.005" target="_blank" >https://doi.org/10.1016/j.agsy.2017.03.005</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.agsy.2017.03.005" target="_blank" >10.1016/j.agsy.2017.03.005</a>

Result language

angličtina

Original language name

Performance of process-based models for simulation of grain N in crop rotations across Europe

Original language description

The accurate estimation of crop grain nitrogen (N; N in grain yield) is crucial for optimizing agricultural N management, especially in crop rotations. In the present study, 12 process-based models were applied to simulate the grain N of i) seven crops in rotations, ii) across various pedo-climatic and agro-management conditions in Europe, iii) under both continuous simulation and single year simulation, and for iv) two calibration levels, namely minimal and detailed calibration. The models performed better in predicting the grain N of winter wheat (Triticum aestivum L.), winter barley (Hordeum vulgare L.) and spring barley (Hordeum vulgare L.) compared to spring oat (Avena sativa L.), winter rye (Secale cereale L.), pea (Pisum sativum L.) and winter oilseed rape (Brassica napus L.). These differences are linked to the intensity of parameterization with better parameterized crops showing lower prediction errors. The model performance was influenced by N fertilization and irrigation treatments, and a majority of the predictions were more accurate under low N and rainfed treatments. Moreover, the multi-model mean provided better predictions of grain N compared to any individual model. In regard to the Individual models, DAISY, FASSET, HERMES, MONICA and STICS are suitable for predicting grain N of the main crops in typical European crop rotations, which all performed well in both continuous simulation and single year simulation. Our results show that both the model initialization and the cover crop effects in crop rotations should be considered in order to achieve good performance of continuous simulation. Furthermore, the choice of either continuous simulation or single year simulation should be guided by the simulation objectives (e.g. grain yield, grain N content or N dynamics), the crop sequence (inclusion of legumes) and treatments (rate and type of N fertilizer) included in crop rotations and the model formalism.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10509 - Meteorology and atmospheric sciences

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Agricultural Systems

ISSN

0308-521X

e-ISSN

—

Volume of the periodical

154

Issue of the periodical within the volume

June

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

15

Pages from-to

63-77

UT code for WoS article

000401876600007

EID of the result in the Scopus database

2-s2.0-85015720620