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Assessing Growth and Water Productivity for Drip-Irrigated Maize under High Plant Density in Arid to Semi-Humid Climates

Author

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  • Feng Wang

    (Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs, Beijing 100081, China
    Gansu Provincial Key Laboratory of Aridland Crop Sciences, College of Agronomy, Gansu Agricultural University, Lanzhou 730070, China)

  • Jun Xue

    (Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs, Beijing 100081, China)

  • Ruizhi Xie

    (Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs, Beijing 100081, China)

  • Bo Ming

    (Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs, Beijing 100081, China)

  • Keru Wang

    (Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs, Beijing 100081, China)

  • Peng Hou

    (Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs, Beijing 100081, China)

  • Lizhen Zhang

    (College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China)

  • Shaokun Li

    (Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs, Beijing 100081, China)

Abstract

Determining the water productivity of maize is of great significance for ensuring food security and coping with climate change. In 2018 and 2019, we conducted field trials in arid areas (Changji), semi-arid areas (Qitai) and semi-humid areas (Xinyuan). The hybrid XY335 was selected for the experiment, the planting density was 12.0 × 10 4 plants ha −1 , and five irrigation amounts were set. The results showed that yield, biomass, and transpiration varied substantially and significantly between experimental sites, irrigation and years. Likewise, water use efficiency (WUE) for both biomass (WUE B ) and yield (WUE Y ) were affected by these factors, including a significant interaction. Normalized water productivity (WP*) of maize increased significantly with an increase in irrigation. The WP* for film mulched drip irrigation maize was 37.81 g m −2 d − 1 ; it was varied significantly between sites and irrigation or their interaction. We conclude that WP* differs from the conventional parameter for water productivity but is a useful parameter for assessing the attainable rate of film-mulched drip irrigation maize growth and yield in arid areas, semi-arid areas and semi-humid areas. The parametric AquaCrop model was not accurate in simulating soil water under film mulching. However, it was suitable for the prediction of canopy coverage (CC) for most irrigation treatments.

Suggested Citation

  • Feng Wang & Jun Xue & Ruizhi Xie & Bo Ming & Keru Wang & Peng Hou & Lizhen Zhang & Shaokun Li, 2022. "Assessing Growth and Water Productivity for Drip-Irrigated Maize under High Plant Density in Arid to Semi-Humid Climates," Agriculture, MDPI, vol. 12(1), pages 1-16, January.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:1:p:97-:d:722514
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    References listed on IDEAS

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    1. Geerts, Sam & Raes, Dirk, 2009. "Deficit irrigation as an on-farm strategy to maximize crop water productivity in dry areas," Agricultural Water Management, Elsevier, vol. 96(9), pages 1275-1284, September.
    2. Kang, Shaozhong & Hao, Xinmei & Du, Taisheng & Tong, Ling & Su, Xiaoling & Lu, Hongna & Li, Xiaolin & Huo, Zailin & Li, Sien & Ding, Risheng, 2017. "Improving agricultural water productivity to ensure food security in China under changing environment: From research to practice," Agricultural Water Management, Elsevier, vol. 179(C), pages 5-17.
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    1. Konstantinos Dolaptsis & Xanthoula Eirini Pantazi & Charalampos Paraskevas & Selçuk Arslan & Yücel Tekin & Bere Benjamin Bantchina & Yahya Ulusoy & Kemal Sulhi Gündoğdu & Muhammad Qaswar & Danyal Bust, 2024. "A Hybrid LSTM Approach for Irrigation Scheduling in Maize Crop," Agriculture, MDPI, vol. 14(2), pages 1-26, January.

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