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Agronomy 2019, 9(2), 109; https://doi.org/10.3390/agronomy9020109

Optimizing the Sowing Date and Irrigation Strategy to Improve Maize Yield by Using CERES (Crop Estimation through Resource and Environment Synthesis)-Maize Model

1
College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China
2
Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, China
3
Nuclear Institute for Agriculture & Biology, Faisalabad 38000, Pakistan
4
Department of Soil and Physical Sciences, Lincoln University, Canterbury 85084, New Zealand
5
Department of Agronomy, University of Agriculture, Faisalabad 38040, Pakistan
6
Department of irrigation and drainage, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
*
Author to whom correspondence should be addressed.
Received: 26 January 2019 / Revised: 11 February 2019 / Accepted: 20 February 2019 / Published: 25 February 2019
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Abstract

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. View Full-Text
Keywords: CERES-maize; Summer maize; Sowing date; Irrigation strategy; Guanzhong Plain CERES-maize; Summer maize; Sowing date; Irrigation strategy; Guanzhong Plain
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Saddique, Q.; Cai, H.; Ishaque, W.; Chen, H.; Chau, H.W.; Chattha, M.U.; Hassan, M.U.; Khan, M.I.; He, J. Optimizing the Sowing Date and Irrigation Strategy to Improve Maize Yield by Using CERES (Crop Estimation through Resource and Environment Synthesis)-Maize Model. Agronomy 2019, 9, 109.

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