• ISSN 1008-505X
  • CN 11-3996/S
焦江华, 张旭博, 梁硕, 孙楠, 徐梦, 徐明岗. 引入水稻“移栽时间效应”和光敏感性算法改进ORYZA模型并验证[J]. 植物营养与肥料学报, 2020, 26(7): 1251-1261. DOI: 10.11674/zwyf.19411
引用本文: 焦江华, 张旭博, 梁硕, 孙楠, 徐梦, 徐明岗. 引入水稻“移栽时间效应”和光敏感性算法改进ORYZA模型并验证[J]. 植物营养与肥料学报, 2020, 26(7): 1251-1261. DOI: 10.11674/zwyf.19411
JIAO Jiang-hua, ZHANG Xu-bo, LIANG Shuo, SUN Nan, XU Meng, XU Ming-gang. Improvement and validation of ORYZA model through introducing "transplanting time effect" and light sensitivity of rice[J]. Journal of Plant Nutrition and Fertilizers, 2020, 26(7): 1251-1261. DOI: 10.11674/zwyf.19411
Citation: JIAO Jiang-hua, ZHANG Xu-bo, LIANG Shuo, SUN Nan, XU Meng, XU Ming-gang. Improvement and validation of ORYZA model through introducing "transplanting time effect" and light sensitivity of rice[J]. Journal of Plant Nutrition and Fertilizers, 2020, 26(7): 1251-1261. DOI: 10.11674/zwyf.19411

引入水稻“移栽时间效应”和光敏感性算法改进ORYZA模型并验证

Improvement and validation of ORYZA model through introducing "transplanting time effect" and light sensitivity of rice

  • 摘要:
    目的 水稻生长模型是实现水稻管理自动化的重要工具。现有水稻模型未充分体现水稻生长的“移栽时间效应”,模型参数较多,使用较复杂。基于这些问题改进和完善水稻生长模型,以提高模型的准确性和实用性。
    方法 在ORYZA与RCSODS模型的基础上,结合已有水稻生育期时间节点计算方法及其对干物质积累与分配的影响权重,在模型中增加移栽时间效应和水稻动态消光系数方程。利用2003—2012年黑龙江省绥化市庆安县农业气象站的发育期、产量和气象数据,验证了改进后的水稻生长模型的模拟效果,对比分析改进前后的效果差异。
    结果 改进后模拟的返青期、分蘖期、孕穗期、抽穗期与成熟期和实际发育期时间节点的残差均方根 (RMSE) 分别为1.17、1.41、1.00、2.23和2.12天,整个发育期模拟RMSE与RE (相对误差) 平均为1.6天与1.3%。试验点位多年产量范围在6495~8715 kg/hm2,模拟值为7230~8207 kg/hm2,其中产量模拟最小误差为210 kg/hm2,平均RMSE与RE分别为714 kg/hm2与9.2%,模型相对误差率保持在10%以内。移栽前有效积温与水稻完成基本营养生长期所需的有效积温呈显著正相关 (R2 = 0.7837,P = 0.003),根据移栽时有效积温调整发育期模型第一阶段 (基本营养阶段)生长速率参数,使发育期的模拟误差缩小3倍,产量模拟误差缩小34%。
    结论 引入移栽前有效积温与基本营养生长期发育速率之间关系的响应方程,极大地提升了发育期模型的模拟效果;引入动态水稻消光系数方程,小幅度地提升了产量的模拟效果。改进后的模型可以促进水稻模型的发展,并更加准确地指导水稻生产。

     

    Abstract:
    Objective Rice growth model is an important tool for realizing automatic management of rice production. The existing rice model does not fully consider the "transplanting time effect" in rice growth, and not easy to use as too many parameters required. Therefore, the model was improved for its more accurate and practical use.
    Methods On the base of ORYZA and RCSODS models, combining with algorithms for the rice growth period and the importance of the periods in dry matter accumulation, the time effect of transplanting and the equation of dynamic extinction coefficient of rice were introduced into the model. The simulated growth period and yield were validated using the meteorological data in Suihua City, Heilongjiang Province from 2003 to 2012.
    Results The mean square root of residual difference (RMSE) of simulation were respectively 1.17 days, 1.41 days, 1.00 day, 2.23 days and 2.12 days in the periods of greening, tillering, booting, heading and maturity. The RMSE and RE (relative error) of simulation of the entire development period were averaged 1.6 days and 1.3%. The observed annual yields of rice ranged from 6495 kg/hm2 to 8715 kg/hm2, and the simulated yields ranged from 7230 kg/hm2 to 8207 kg/hm2, with the minimum error in yield of 210 kg/hm2, and the average RMSE and RE of 714 kg/hm2 and 9.2%, respectively. The relative error rate of simulation by the model was kept within 10%.The acquired effective cumulative temperature before transplanting was significantly and positively related to that required for rice to complete the basic vegetative period (R2 = 0.7837, P = 0.003), the growth rate parameter of the first growing stage in the model was adjusted according to this character, which decreased the simulation error in the date of growing period by three times, and in the yield by 34%.
    Conclusions The introduction of the “Transplanting time effect” and the “Dynamic extinction coefficient” improved the simulation accuracy of the model in rice growth period and yield significantly. The response equation of the acquired effective accumulation temperature before transplanting and that required for whole vegetative period is introduced into the model, which greatly decreases the simulation error in the date arriving a growth period. The introduction of equation of dynamic rice extinction coefficient decreases the simulation errors in yield. All the modifications have improved the accuracy of the model.

     

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