Plant Biology · 2018 · 16 citations · 34 references
AgricultureCrop SciencesPlant SciencesCrop PhysiologyPhotosynthesisPlant EcophysiologyCrop-water RelationsDroughtDrought PhysiologyDrought Stress PhysiologyDrought TolerancePhotosynthesis In CropsDrought Effects On ProductivityDrought StressDrought Stress EffectsGreenhouse TrialsPlant Drought PhysiologyPlant Growth PhysiologyPlant Physiological ResponsesWater Stress Effects On Photosynthesis
Abstract In the course of climate change, crop plants are exposed to both altered precipitation volumes and frequencies in many cultivation areas. Reduced water availability and longer periods without precipitation can lead to changes in plant physiology and productivity. In this greenhouse study, we investigated physiological responses, including maximum quantum yield of photosystem II (F v /F m ) and water use efficiency (WUE) as well as diverse productivity‐related parameters, including grain yield per plant, to continuous (irrigated three times a week) versus pulsed (once a week) irrigation in spring wheat ( Triticum aestivum L.). In both drought regimes, plants were exposed to four different irrigation volumes. F v /F m was not influenced by irrigation treatment but was significantly higher after 6 weeks of drought than after 2 weeks. WUE increased with decreasing irrigation volume and based on generative biomass; it was higher in continuously‐watered compared to pulsed‐watered plants that received a similar amount of water over the experiment. Infrequent irrigation led to a reduction in grain yield of up to 51%. This lower productivity was primarily caused by fewer tillers in pulsed‐watered plants. Additionally, at low water volume the thousand grain weight (TGW) was lower in infrequently‐compared to frequently‐watered plants. In contrast, the number of grains per ear was higher in pulsed‐watered plants. In conclusion, reduced irrigation frequency, next to a decrease in irrigation volume, negatively affects WUE and grain yield of spring wheat. These results might have important implications for irrigation scheduling and breeding programmes under a changing climate.
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R: A Language and Environment for Statistical Computing
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