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Modeling the effects of plant density on maize productivity and water balance in the Loess Plateau of China

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  • Ren, Xinmao
  • Sun, Dongbao
  • Wang, Qingsuo

Abstract

Loess Plateau of China is an area with serious soil evaporation and large inter-annual rainfall variations. Water stress is the major limiting factor for crop production in local area. Optimizing plant density is one crucial management in semi-arid dry land areas where crop growth is constrained by precipitation and a high evaporative demand. The Agricultural Production System Simulator (APSIM) was parameterized and tested with two years datasets, and then used to investigate long-term rainfed maize productivity and water balance with the historical weather records. Model application showed that water use and yield were varied because of the plant density and the inter-annual variability of precipitation. Plant density presented no influence on the evapotranspiration (ET) in extremely dry years, dry years and mild wet years but a significantly (P<0.05) influence in normal and extremely wet years. In extremely dry years, the grain yield and (WUE) were all significantly (P<0.05) decreased when plant density increased. The grain yield and WUE showed a parabolic relation with the plant density except extremely dry years. On average, the maximum yield and WUE were 6715kgha−1 and 1.81kgm−3 at 52500 plants ha−1 (D2) in dry years, 7857kgha−1 and 1.92kgm−3 at 67500 plants ha−1 (D3) in normal years, 8937kgha−1 and 2.19kgm−3 at 67500 plants ha−1 (D3) in mild wet years，and 9713kgha−1 at 82500 plants ha−1 (D4) and 2.25kgm−3 at 67500 plants ha−1 (D3) in extremely wet years, respectively. However, no significant difference was obtained for average yield or WUE when compared traditional density of 52500 plants ha−1 (D2) with higher plant density. Compared with the traditional plant density of 52500 plants ha−1 (D2), the increase of plant density significantly (P<0.05) reduced soil evaporation, only with the exception of extremely dry years. In order to get long term average benefits in the study area and similar agro-ecological zones, plant populations should not exceed 32500 plants ha−1 (D1) in extremely dry years, indeed, lower may be better. A plant density of 52500 plants ha−1 (D2) in dry years and 67500 plants ha−1 (D3) in normal years, mild wet years and extremely wet years are recommended as the optimum value, respectively.

Suggested Citation

  • Ren, Xinmao & Sun, Dongbao & Wang, Qingsuo, 2016. "Modeling the effects of plant density on maize productivity and water balance in the Loess Plateau of China," Agricultural Water Management, Elsevier, vol. 171(C), pages 40-48.
    • Handle: RePEc:eee:agiwat:v:171:y:2016:i:c:p:40-48
    DOI: 10.1016/j.agwat.2016.03.014
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    References listed on IDEAS

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    1. McCown, R. L. & Hammer, G. L. & Hargreaves, J. N. G. & Holzworth, D. P. & Freebairn, D. M., 1996. "APSIM: a novel software system for model development, model testing and simulation in agricultural systems research," Agricultural Systems, Elsevier, vol. 50(3), pages 255-271.
    2. Piper, Ernest L. & Weiss, Albert, 1990. "Evaluating CERES-Maize for reduction in plant population or leaf area during the growing season," Agricultural Systems, Elsevier, vol. 33(3), pages 199-213.
    3. Nyakudya, Innocent Wadzanayi & Stroosnijder, Leo, 2014. "Effect of rooting depth, plant density and planting date on maize (Zea mays L.) yield and water use efficiency in semi-arid Zimbabwe: Modelling with AquaCrop," Agricultural Water Management, Elsevier, vol. 146(C), pages 280-296.
    4. Persaud, N. & Khosla, R., 1999. "Partitioning soil-water losses in different plant populations of dry-land corn," Agricultural Water Management, Elsevier, vol. 42(2), pages 157-172, November.
    5. Nelson, R. A. & Holzworth, D. P. & Hammer, G. L. & Hayman, P. T., 2002. "Infusing the use of seasonal climate forecasting into crop management practice in North East Australia using discussion support software," Agricultural Systems, Elsevier, vol. 74(3), pages 393-414, December.
    6. Chen, Chao & Wang, Enli & Yu, Qiang, 2010. "Modelling the effects of climate variability and water management on crop water productivity and water balance in the North China Plain," Agricultural Water Management, Elsevier, vol. 97(8), pages 1175-1184, August.
    7. Jiang, Xuelian & Kang, Shaozhong & Tong, Ling & Li, Fusheng & Li, Donghao & Ding, Risheng & Qiu, Rangjian, 2014. "Crop coefficient and evapotranspiration of grain maize modified by planting density in an arid region of northwest China," Agricultural Water Management, Elsevier, vol. 142(C), pages 135-143.
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