The features of main osmolytes, silicon and their coupling effects in improving drought resistance of the typical xerophytes in the desert areas of Northwest China

Catalpa bungei C.A.Mey. is a common ornamental timber species. Its survival and growth are greatly affected by water scarcity in arid and semi-arid areas of Northwest China. Evidence suggests arbuscular mycorrhizal fungus (AMF) may improve plant drought resistance. However, there is limited information on the systematic effects of AMF on drought resistance in C. bungei seedlings. Here, a pot experiment was used to explore the effects of inoculation with the AMF Rhizophagus intraradices on the growth and physiological performance of C. bungei under different water treatment conditions. Three water levels and two mycorrhizal inoculation treatments were used with factorial design. The results showed that drought stress noticeably affected the growth and physiological performance of C. bungei seedlings. However, inoculation with R. intraradices significantly ameliorated the growth, and alleviated the effects of drought stress. The growth parameters of AMF-inoculated seedlings significantly increased regardless of water status. AMF changed the biomass allocation in seedlings by reducing the root mass ratio (RMR) and root/shoot ratio. AMF-inoculated seedlings displayed higher gas exchange parameters, photosynthetic pigment concentrations, specific leaf area (SLA), but lower specific leaf weight (SLW), regardless of water status. AMF alleviated drought-induced oxidative stress by attenuating the excess generation of reactive oxygen species (ROS), especially H2O2 and O2−, in leaves. Inoculation with AMF under drought stress also dramatically augmented indole-3-acetic acid (IAA) and gibberellins (GA3) levels and the IAA/abscisic acid (ABA) and GA3/ABA ratios, but reduced ABA and zeatin (ZT) levels in leaves. AMF symbiosis improved root morphology and promoted the absorption of nitrogen (N) and phosphorus (P) in seedlings. We conclude that inoculation with R. intraradices is potentially useful for afforestation and cultivation of C. bungei in Northwest China. Furthermore, AMF improved soil structure by increasing the glomalin-related soil protein (GRSP) contents and the proportion of macro-aggregates (0.25–0.5 mm) in the rhizosphere soil.

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Nowcasting of Surface Solar Irradiance Using FengYun-4 Satellite Observations over China

Remote Sensing ◽

10.3390/rs11171984 ◽

2019 ◽

Vol 11 (17) ◽

pp. 1984 ◽

Cited By ~ 4

Author(s):

Yang ◽

Gao ◽

Li ◽

Jia ◽

Jiang

Keyword(s):

Solar Irradiance ◽

Satellite Images ◽

Motion Vector ◽

Northwest China ◽

Mean Bias Error ◽

Bias Error ◽

Random Mutation ◽

Time Horizons ◽

Desert Areas ◽

Sky Conditions

The accurate prediction of surface solar irradiance is of great significance for the generation of photovoltaic power. Surface solar irradiance is affected by many random mutation factors, which means that there are great challenges faced in short-term prediction. In Northwest China, there are abundant solar energy resources and large desert areas, which have broad prospects for the development of photovoltaic (PV) systems. For the desert areas in Northwest China, where meteorological stations are scarce, satellite remote sensing data are extremely precious exploration data. In this paper, we present a model using FY-4A satellite images to forecast (up to 15–180 min ahead) global horizontal solar irradiance (GHI), at a 15 min temporal resolution in desert areas under different sky conditions, and compare it with the persistence model (SP). The spatial resolution of the FY-4A satellite images we used was 1 km × 1 km. Particle image velocimetry (PIV) was used to derive the cloud motion vector (CMV) field from the satellite cloud images. The accuracy of the forecast model was evaluated by the ground observed GHI data. The results showed that the normalized root mean square error (nRMSE) ranged from 18.9% to 21.6% and the normalized mean bias error (nMBE) ranged from 3.2% to 4.9% for time horizons from 15 to 180 min under all sky conditions. Compared with the SP model, the nRMSE value was reduced by about 6%, 8%, and 14% with the time horizons of 60, 120, and 180 min, respectively.

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