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Journal of Integrative Agriculture  2024, Vol. 23 Issue (3): 1006-1021    DOI: 10.1016/j.jia.2023.07.034
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Combining field data and modeling to better understand maize growth response to phosphorus (P) fertilizer application and soil P dynamics in calcareous soils

Weina Zhang1, 2, Zhigan Zhao4, Di He4, Junhe Liu1, Haigang Li3#, Enli Wang4#

 1 School of Biological and Food Processing Engineering, Huanghuai University, Zhumadian 463000, China

2 Key Laboratory of Plant–Soil Interactions, Ministry of Education/College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China

3 Inner Mongolia Key Laboratory of Soil Quality and Nutrient Resources/Key Laboratory of Grassland Resource (IMAU), Ministry of Education/College of Grassland, Resources and Environment, Inner Mongolia Agricultural University, Hohhot 010018, China

4 CSIRO Agriculture and Food, Canberra, ACT 2601, Australia

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摘要  

本研究利用田间试验数据评价了APSIM模型(Agricultural Production Systems sIMulator)在华北平原潮土上模拟磷有效性、玉米生物量和产量对磷肥施用的响应能力。通过的2年的田间试验数据(3种磷肥施用量:0、75、300 kg P2O5/ha)对模型进行校正,并通过敏感性分析研究APSIM模型中土壤磷参数变化对土壤模拟磷有效性和玉米生长的影响。其次,将模拟结果与作物生物量、产量、磷吸收和Olsen-P观测值进行比较,优化作物和土壤磷参数。利用同一试验点的2年独立试验数据对优化后的模型进行验证,结果表明优化后的模型能够较好地模拟玉米叶面积指数、生物量、籽粒产量、磷吸收量和籽粒磷含量对不同供磷水平的响应。通过修改叶片生长的钟形函数曲线,同时降低叶片衰老速率可以提高模型对现在玉米持绿品种LAI动态变化的模拟表现。实测的Olsen-P浓度与模拟的Labile-P含量之间存在显著相关关系,在之后的研究中可以使用该曲线关系初始化土壤中有效磷库。目前,因缺乏对土壤中不同磷库间转化过程的定量化,APSIM SoilP模块仍然难以进行参数化。



Abstract  We used field experimental data to evaluate the ability of the agricultural production system model (APSIM) to simulate soil P availability, maize biomass and grain yield in response to P fertilizer applications on a fluvo-aquic soil in the North China Plain.  Crop and soil data from a 2-year experiment with three P fertilizer application rates (0, 75 and 300 kg P2O5 ha–1) were used to calibrate the model.  Sensitivity analysis was carried out to investigate the influence of APSIM SoilP parameters on the simulated P availability in soil and maize growth.  Crop and soil P parameters were then derived by matching or relating the simulation results to observed crop biomass, yield, P uptake and Olsen-P in soil.  The re-parameterized model was further validated against 2 years of independent data at the same sites.  The re-parameterized model enabled good simulation of the maize leaf area index (LAI), biomass, grain yield, P uptake, and grain P content in response to different levels of P additions against both the calibration and validation datasets.  Our results showed that APSIM needs to be re-parameterized for simulation of maize LAI dynamics through modification of leaf size curve and a reduction in the rate of leaf senescence for modern stay-green maize cultivars in China.  The P concentration limits (maximum and minimum P concentrations in organs) at different stages also need to be adjusted.  Our results further showed a curvilinear relationship between the measured Olsen-P concentration and simulated labile P content, which could facilitate the initialization of APSIM P pools in the NCP with Olsen-P measurements in future studies.  It remains difficult to parameterize the APSIM SoilP module due to the conceptual nature of the pools and simplified conceptualization of key P transformation processes.  A fundamental understanding still needs to be developed for modelling and predicting the fate of applied P fertilizers in soils with contrasting physical and chemical characteristics.
Keywords:  maize        phosphorus availability        modeling        APSIM maize        APSIM  SoilP
  
Received: 05 April 2023   Accepted: 19 June 2023
Fund: 

This work was funded by the National Natural Science Program of China (2022YFD1900300), the China Scholarship Council (CSC) through the CSC-CSIRO (Commonwealth Scientific and Industrial Research Organisation) Joint Ph D Program, the Zhumadian Major Scientific and Technological Innovation Project, China (170109564016) and the Huanghuai University Scientific Research Foundation, China (502310020017).

About author:  Weina Zhang, E-mail: zhangweina921012@163.com; #Correspondence Haigang Li, Mobile: +86-13426493910, E-mail: haigangli@cau.edu.cn; Enli Wang, Tel: +61-262465964, E-mail: Enli.Wang@csiro.au

Cite this article: 

Weina Zhang, Zhigan Zhao, Di He, Junhe Liu, Haigang Li, Enli Wang. 2024.

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