Abstract

The self-sufficiency ratio and national average yield of wheat is 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 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 Kanto area (November), the root mean square error (RMSE) 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.

摘要

日本的小麦自给率和全国平均单产较低。缩小单产差距并获得政府对谷物质量的补贴是实现利润的重要策略。阐明最佳的氮肥施用方案正在等待日本的小麦种植获得更高的产量和适当的谷蛋白含量（GPC）。通过将田间试验知识整合到作物生长模型中，可以实现这种决策支持，尽管在日本很少将其用于小麦生产。因此，本研究的目的是通过校准和验证将广泛使用的作物生长模型（APSIM）应用于日本关东地区Andosol上的小麦生长。选定的APSIM-小麦模型参数，用于物候，叶片生长，根据软，硬小麦品种的物候和生长数据，重新调整了小麦的籽粒和籽粒的形成。然后，使用在独立实验中获得的相似变量对模型进行验证。为了模拟关东地区（11月）冬小麦的最佳播种，谷物产量的均方根误差（RMSE）为23和48 gmAyahikari和Yumeshiho品种的⁻²分别为GPC的-1和1.4％。因此，总体模型性能对于最佳播种是可以接受的。然而，当包括后期播种组的数据时，谷物产量和干物质产量被大大高估了。因此，建议对模型进行进一步的改进，以增加一种算法，以减少播种后期在低温下出现的植物数量。