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Yang Y, Liu G, Guo X, Liu W, Xue J, Ming B, Xie R, Wang K, Hou P, Li S. Quantitative Relationship Between Solar Radiation and Grain Filling Parameters of Maize. FRONTIERS IN PLANT SCIENCE 2022; 13:906060. [PMID: 35755643 PMCID: PMC9226782 DOI: 10.3389/fpls.2022.906060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 05/24/2022] [Indexed: 06/15/2023]
Abstract
A quantitative understanding of the factors driving changes in grain filling is essential for effective prioritization of increasing maize yield. Grain filling is a significant stage in maize yield formation. Solar radiation is the energy source for grain filling, which is the ultimate driving factor for final grain weight and grain filling capacity that determine maize yield. Here, we first confirmed the quantitative relationships between grain filling parameters and photosynthetically active radiation (PAR) by conducting field experiments using different shading and plant density conditions and cultivars in 2019 and 2020 in Xinjiang, China. The results showed that with every 100 MJ m-2 increase in PAR, the average grain filling rate (G ave), maximum grain-filling rate (G max), and the kernel weight at the time of maximum grain-filling rate (W max) increased by 0.073 mg kernel-1 day-1, 0.23 mg kernel-1 day-1, and 0.24 mg kernel-1, and the time of maximum grain-filling rate (T max) delayed by 0.91 day. Relative changes in PAR were significantly and positively correlated with relative changes in yield and G ave. With every 1% change in PAR, yield and G ave changed by 1.16 and 0.17%, respectively. From the perspective of grain filling capacity, DH618 was a more shade-resistant cultivar than XY335 and ZD958. It is urgent to breed maize cultivars with low light tolerance and high grain yield in the face of climate change, particularly the decrease in solar radiation.
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Affiliation(s)
- Yunshan Yang
- The Key Laboratory of Oasis Eco-Agriculture, Xinjiang Production and Construction Corps/College of Agronomy, Shihezi University, Shihezi, China
- Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Guangzhou Liu
- Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xiaoxia Guo
- The Key Laboratory of Oasis Eco-Agriculture, Xinjiang Production and Construction Corps/College of Agronomy, Shihezi University, Shihezi, China
| | - Wanmao Liu
- School of Agriculture, Ningxia University, Yinchuan, China
| | - Jun Xue
- Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Bo Ming
- Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Ruizhi Xie
- Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Keru Wang
- Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Peng Hou
- Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Shaokun Li
- The Key Laboratory of Oasis Eco-Agriculture, Xinjiang Production and Construction Corps/College of Agronomy, Shihezi University, Shihezi, China
- Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
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Gui X, Wang L, Su X, Yi X, Chen X, Yao R, Wang S. Environmental factors modulate the diffuse fertilization effect on gross primary productivity across Chinese ecosystems. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 793:148443. [PMID: 34171807 DOI: 10.1016/j.scitotenv.2021.148443] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Revised: 05/31/2021] [Accepted: 06/09/2021] [Indexed: 06/13/2023]
Abstract
Diffuse radiation allocated by cloud cover and aerosols can promote vegetation photosynthesis, which is known as the diffuse fertilization effect (DFE). As an important uncertain factor regulating the DFE, understanding the role of environmental conditions in the response of terrestrial ecosystems to diffuse radiation is vital for quantitative and intensive studies. By using a light use efficiency model and statistical methods with satellite data and ChinaFLUX observation data, the optimal environmental range of DFE was estimated, the indirect role of vapor pressure deficit (VPD) and air temperature (Ta) on DFE was explored, and the relative contribution of diffuse photosynthetically active radiation (PARdif) on gross primary productivity (GPP) was analyzed across Chinese ecosystems under different sky conditions. The results showed that the DFE increased with leaf area index (LAI), but distributed a unimodal curve along with VPD and Ta, both of which had an optimum range that was lower in the forest (or cropland) and higher in the grass (or desert) ecosystem. When considering the co-effect of VPD and Ta, the strongest positive effect of DFE was found at 0-5 h Pa and 20-25 °C. Based on path analysis, PARdif promoted GPP and served as the main controlling factor in forest ecosystems predominantly through a direct pathway from half-hourly to the daily scale, while Ta and VPD occupied the dominant position at single-canopy ecosystem sites. When the aerosol optical depth (AOD) increased, the relative contribution of PARdif increased in multiple-canopy ecosystems and decreased in single-canopy ecosystems; when the sky conditions changed from sunny to cloudy, the relative contribution of PARdif was higher in the forest ecosystem and increased significantly in the grass ecosystem. These findings offer a more comprehensive understanding of the environmental effects of regulating DFE on GPP across ecosystems.
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Affiliation(s)
- Xuan Gui
- Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China; Hubei Key Laboratory of Critical Zone Evolution, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
| | - Lunche Wang
- Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China; Hubei Key Laboratory of Critical Zone Evolution, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China.
| | - Xin Su
- Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China; Hubei Key Laboratory of Critical Zone Evolution, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
| | - Xiuping Yi
- Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China; Hubei Key Laboratory of Critical Zone Evolution, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
| | - Xinxin Chen
- Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China; Hubei Key Laboratory of Critical Zone Evolution, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
| | - Rui Yao
- Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China; Hubei Key Laboratory of Critical Zone Evolution, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
| | - Shaoqiang Wang
- Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China; Hubei Key Laboratory of Critical Zone Evolution, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
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