globalchange  > 气候减缓与适应
DOI: 10.3390/agronomy9020109
WOS记录号: WOS:000460694200068
论文题名:
Optimizing the Sowing Date and Irrigation Strategy to Improve Maize Yield by Using CERES (Crop Estimation through Resource and Environment Synthesis)-Maize Model
作者: Saddique, Qaisar1,2; Cai, Huanjie1,2; Ishaque, Wajid3; Chen, Hui1,2; Chau, Henry Wai4; Chattha, Muhammad Umer5; Hassan, Muhammad Umair5; Khan, Muhammad Imran6; He, Jianqiang1,2
通讯作者: Cai, Huanjie
刊名: AGRONOMY-BASEL
ISSN: 2073-4395
出版年: 2019
卷: 9, 期:2
语种: 英语
英文关键词: CERES-maize ; Summer maize ; Sowing date ; Irrigation strategy ; Guanzhong Plain
WOS关键词: ZEA-MAYS L. ; CLIMATE-CHANGE ; CROP MODEL ; WATER PRODUCTIVITY ; SIMULATION-MODEL ; FARMING SYSTEMS ; WHEAT MODEL ; PERFORMANCE ; CORN ; GROWTH
WOS学科分类: Agronomy ; Plant Sciences
WOS研究方向: Agriculture ; Plant Sciences
英文摘要:

Summer maize (Zea mays L.) is a widely cultivated crop in the arid and semi-arid Guanzhong region of China. However, due to the spatial and temporal variation in rainfall, the seasonal maize yield varies substantially and occasionally is not economical for poor farmers to produce. Recent water-saving agricultural practices were developed by the government to make it possible to apply supplementary irrigation at optimum sowing dates to maximize maize production under limited rainfall in the region. CERES (Crop Estimation through Resource and Environment Synthesis)-maize model was used to identify the appropriate irrigation strategies, crop growth stages and sowing dates for sustainable maize production. Model calibration process were carried out for full irrigation treatments of four growing seasons, (2012-2015). The data used for calibration included: Crop phenology, grain yield, aboveground biomass and leaf area index. The calibration phase model showed good agreement between simulated and observed values, with normalized root mean square error (nRMSE) ranging from 4.51% to 14.5%. The performance of the calibrated model was evaluated using the field data of grain yield, aboveground biomass, leaf area index and water use efficiency. The performance of the model during evaluation was satisfactory with acceptable nRMSE error ranging from 7% to 10%. Soil moisture content was evaluated for full irrigation treatments for both 2012 and 2013 seasons. With results showing that soil moisture content below 35 cm layer was well simulated with nRMSE, 0.57 to 0.86 respectively. Appropriate simulated sowing dates for higher production and water productivity were from 14 to 24 June. The proper amount and timing of irrigation water application was 100 mm at the flowering stage, and 100 mm at the grain filling stage respectively. Summer maize yield can be improved by adjusting the sowing date and applying supplementary irrigation when precipitation cannot meet the crop water demand in the Guanzhong Plain.


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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/128942
Appears in Collections:气候减缓与适应

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作者单位: 1.Northwest A&F Univ, Coll Water Resources & Architectural Engn, Yangling 712100, Shaanxi, Peoples R China
2.Northwest A&F Univ, Minist Educ, Key Lab Agr Soil & Water Engn Arid & Semiarid Are, Yangling 712100, Shaanxi, Peoples R China
3.Nucl Inst Agr & Biol, Faisalabad 38000, Pakistan
4.Lincoln Univ, Dept Soil & Phys Sci, Canterbury 85084, New Zealand
5.Univ Agr Faisalabad, Dept Agron, Faisalabad 38040, Pakistan
6.Univ Agr Faisalabad, Dept Irrigat & Drainage, Faisalabad 38000, Pakistan

Recommended Citation:
Saddique, Qaisar,Cai, Huanjie,Ishaque, Wajid,et al. Optimizing the Sowing Date and Irrigation Strategy to Improve Maize Yield by Using CERES (Crop Estimation through Resource and Environment Synthesis)-Maize Model[J]. AGRONOMY-BASEL,2019-01-01,9(2)
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