Evaluation of APSIM-wheat to simulate the response of yield and grain protein content to nitrogen application on an Andosol in Japan
The self-sufficiency ratio and national average yield of wheat are low in Japan. Reducing the yield gap and receiving the government subsidy for grain quality are vital strategies for profitability. Elucidating optimum nitrogen application scheme is awaited to attain both higher yield and appropriat...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Taylor & Francis Group
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/4eceac14ffdb44389debedd0594af5be |
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| Sumario: | The self-sufficiency ratio and national average yield of wheat are low in Japan. Reducing the yield gap and receiving the government subsidy for grain quality are vital strategies for profitability. Elucidating optimum nitrogen application scheme is awaited to attain both higher yield and appropriate grain protein content (GPC) for wheat cultivation in Japan. Such decision support can be realized by integrating field experimental knowledge to crop growth models, although they have scarcely been utilized for wheat production in Japan. Therefore, the purposes of this study were to apply a widely used crop growth model (APSIM) to wheat growth on an Andosol in the Kanto region in Japan by calibration and validation. Selected model parameters of APSIM-wheat for phenology, leaf growth, and grain formation were readjusted based on the phenology and growth data of soft and hard wheat cultivars. Then the model was validated by using similar variables obtained in an independent experiment. For the simulation of the optimum sowing for winter wheat in the Kanto area (November), the root mean square error for grain yield was 23 and 48 g m−2 for Ayahikari and Yumeshiho varieties, respectively, and that for GPC was 1.9 and 1.4%. Thus, the overall model performance was acceptable for optimum sowing. However, grain yield and dry matter production were significantly overestimated when the data of late sowing groups were included. Therefore, further model improvement was suggested to add an algorithm to reduce the number of emerged plants under cold temperature in late sowing conditions. |
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