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Yan Zhu
Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling, Shaanxi, 712100, China

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Journal article
Published: 16 September 2020 in Agricultural Water Management
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Climate change poses great challenges for food security and water use. This study aimed to investigate the response of winter wheat in Northern China to climate change and propose corresponding strategies to maintain yield and crop water productivity (WPc). Climate model projections from the fifth phase of the Climate Model Intercomparison Project (CMIP5) were used to drive the process-based soil–water–atmosphere–plant (SWAP) agro-hydrological model. The SWAP parameters were optimized by the Parameter Estimation program (PEST), which extended the crop model to the regional scale. SWAP was used to simulate responses of crop growth, evapotranspiration (ET), and yield to baseline (2006–2012) climate and two representative concentration pathway (RCP) scenarios (RCP4.5 and RCP8.5) for future climate conditions. The results indicated that PEST had high optimization efficiency and calibrated SWAP performed well (average relative error < 20.87 % and normalized root mean square error < 25.83 %). Compared with baseline, the maximum and minimum temperatures increased significantly (P < 0.05) by 6.47°C and 8.59°C, respectively. The cumulative precipitation during the growing season increased by 303.22–316.12 mm. Warming significantly (P < 0.05) reduced the growth period of winter wheat by 25.3–34.7 days, especially in the emergence–heading stage. Path analysis revealed that significant (P < 0.05) change of precipitation was a determining factor in increasing ET. The adverse effect of temperature increase offset the promotion of yield due to radiation, and ultimately led to a yield reduction of 35.57–41.14 %. The optimization scenario indicated that late-maturing varieties and irrigation adjustment could improve yield (up to 38.21 %) and WPc (up to 44.30 %) under future climate conditions. Implementing irrigation at an early growing stage (joining and heading) was beneficial to increase yield and WPc. We recommend combining late-maturing varieties with irrigation adjustments to maintain yield and WPc under future climate conditions.

ACS Style

Xiaowen Wang; Liang Li; Yibo Ding; Jiatun Xu; Yunfei Wang; Yan Zhu; Xiaoyun Wang; Huanjie Cai. Adaptation of winter wheat varieties and irrigation patterns under future climate change conditions in Northern China. Agricultural Water Management 2020, 243, 106409 .

AMA Style

Xiaowen Wang, Liang Li, Yibo Ding, Jiatun Xu, Yunfei Wang, Yan Zhu, Xiaoyun Wang, Huanjie Cai. Adaptation of winter wheat varieties and irrigation patterns under future climate change conditions in Northern China. Agricultural Water Management. 2020; 243 ():106409.

Chicago/Turabian Style

Xiaowen Wang; Liang Li; Yibo Ding; Jiatun Xu; Yunfei Wang; Yan Zhu; Xiaoyun Wang; Huanjie Cai. 2020. "Adaptation of winter wheat varieties and irrigation patterns under future climate change conditions in Northern China." Agricultural Water Management 243, no. : 106409.

Journal article
Published: 30 March 2020 in Sustainability
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Aerated irrigation (AI) is a method to mitigate rhizosphere hypoxia caused by the wetting front from subsurface drip irrigation (SDI). This study evaluated the impacts of AI on soil aeration, plant growth performance, fruit yield (tomato), irrigation water use efficiency (IWUE), fruit nutrition (lycopene and Vitamin C (VC)) and taste (soluble sugar, organic acid and sugar–acid ratio) quality. A three-factorial experiment including AI and SDI at three irrigation levels (W0.6, W0.8 and W1.0, corresponding with crop-pan coefficients of 0.6, 0.8 and 1.0) and two dripper depths (D15 and D25, burial at 15 and 25 cm, respectively), totaling 12 treatments overall, was conducted in a greenhouse during the tomato-growing season (April–July) in 2016. The AI improved soil aeration conditions, with significantly increased soil oxygen concentration and air-filled porosity relative to SDI. Moreover, the AI improved crop growth performance, with increased root morphology (diameter, length density, surface area and volume density), delayed flowering time, prolonged flowering duration and increased shoot (leaf, stem and fruit) dry weight, and harvest index. Fruit yield per plant, fruit weight, IWUE, the contents of lycopene, VC and soluble sugar, and sugar–acid ratio significantly increased under AI treatments (P < 0.05). As the irrigation level increased, fruit yield, number, and weight increased (P < 0.05), but IWUE and fruit lycopene, soluble sugar, and organic acid content decreased (P < 0.05). The dripper depth had no significant impact on fruit yield, nutrition and taste quality. Principal component analysis revealed that the optimal three treatments in terms of fruit yield, IWUE, and nutrition and taste quality were the treatments W0.6D25AI, W1.0D25AI and W1.0D15AI. These results suggest that AI can improve tomato growth performance and increase fruit yield, nutrition and taste quality, and IWUE through enhancing soil aeration conditions.

ACS Style

Yan Zhu; Huanjie Cai; Libing Song; Xiaowen Wang; Zihui Shang; Yanan Sun. Aerated Irrigation of Different Irrigation Levels and Subsurface Dripper Depths Affects Fruit Yield, Quality and Water Use Efficiency of Greenhouse Tomato. Sustainability 2020, 12, 2703 .

AMA Style

Yan Zhu, Huanjie Cai, Libing Song, Xiaowen Wang, Zihui Shang, Yanan Sun. Aerated Irrigation of Different Irrigation Levels and Subsurface Dripper Depths Affects Fruit Yield, Quality and Water Use Efficiency of Greenhouse Tomato. Sustainability. 2020; 12 (7):2703.

Chicago/Turabian Style

Yan Zhu; Huanjie Cai; Libing Song; Xiaowen Wang; Zihui Shang; Yanan Sun. 2020. "Aerated Irrigation of Different Irrigation Levels and Subsurface Dripper Depths Affects Fruit Yield, Quality and Water Use Efficiency of Greenhouse Tomato." Sustainability 12, no. 7: 2703.