5 research outputs found
Distinct morphological, physiological, and biochemical responses to light quality in barley leaves and roots
Light quality modulates plant growth, development, physiology, and metabolism through a series of photoreceptors perceiving light signal and related signaling pathways. Although the partial mechanisms of the responses to light quality are well understood, how plants orchestrate these impacts on the levels of above- and below-ground tissues and molecular, physiological, and morphological processes remains unclear. However, the re-allocation of plant resources can substantially adjust plant tolerance to stress conditions such as reduced water availability. In this study, we investigated in two spring barley genotypes the effect of ultraviolet-A (UV-A), blue, red, and far-red light on morphological, physiological, and metabolic responses in leaves and roots. The plants were grown in growth units where the root system develops on black filter paper, placed in growth chambers. While the growth of above-ground biomass and photosynthetic performance were enhanced mainly by the combined action of red, blue, far-red, and UV-A light, the root growth was stimulated particularly by supplementary far-red light to red light. Exposure of plants to the full light spectrum also stimulates the accumulation of numerous compounds related to stress tolerance such as proline, secondary metabolites with antioxidative functions or jasmonic acid. On the other hand, full light spectrum reduces the accumulation of abscisic acid, which is closely associated with stress responses. Addition of blue light induced accumulation of Îģ-aminobutyric acid (GABA), sorgolactone, or several secondary metabolites. Because these compounds play important roles as osmolytes, antioxidants, UV screening compounds, or growth regulators, the importance of light quality in stress tolerance is unequivocal
āļāļēāļĢāļāļĢāļ°āđāļĄāļīāļāļāļ·āđāļāļāļĩāđāđāļŠāļĩāđāļĒāļāļāđāļģāļāđāļ§āļĄāļ āļēāļĒāđāļāđāļāļēāļĢāđāļāļĨāļĩāđāļĒāļāđāļāļĨāļāļŠāļ āļēāļāļ āļđāļĄāļīāļāļēāļāļēāļĻ āļāļĢāļāļĩāļĻāļķāļāļĐāļē: āļāļ·āđāļāļāļĩāđāļĢāļēāļāļāđāļģāļāđāļ§āļĄ āļāļāđāļāđāļāļ āļāļąāļāļŦāļ§āļąāļāļŠāļēāļĨāļ°āļ§āļąāļ āļŠāļāļ. āļĨāļēāļ§ Flood Risk Assessment under Climate Change: Study Case Khongsedon Floodplain, Salavan Province, Lao PDR
āļāļēāļĢāļ§āļīāļāļąāļĒāļāļĩāđāļĄāļĩāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļ·āđāļāļāļĢāļ°āđāļĄāļīāļāļāļ·āđāļāļāļĩāđāđāļŠāļĩāđāļĒāļāļāđāļģāļāđāļ§āļĄāļāļąāļāđāļāļ·āđāļāļāļāļēāļāļāļēāļĢāđāļāļĨāļĩāđāļĒāļāđāļāļĨāļāļŠāļ āļēāļāļ āļđāļĄāļīāļāļēāļāļēāļĻ āđāļāļāļ·āđāļāļāļĩāđāļĢāļēāļāļāđāļģāļāđāļ§āļĄāļāļķāļāļāļāđāļāđāļāļ āļāļąāļāļŦāļ§āļąāļāļŠāļēāļĨāļ°āļ§āļąāļ āļŠāļāļ. āļĨāļēāļ§ āđāļāļĒāđāļāđāļāļ§āļīāļāļĩāļāļēāļĢāļĻāļķāļāļĐāļēāļāļāļāđāļāđāļ 5 āļŠāđāļ§āļāļĒāđāļāļĒ āđāļāđāđāļāđ 1) āļāļēāļĢāļŠāļāļąāļāđāļĨāļ°āļāļēāļĢāļāļĢāļąāļāđāļāđāļāđāļāļĄāļđāļĨāļ āļđāļĄāļīāļāļēāļāļēāļĻāđāļāļāđāļ§āļ āļ.āļĻ. 2020â2100 āļāļēāļāđāļāļāļāļģāļĨāļāļ Mixed Resolution version of Max Planck Institute Earth System Model (MPI-ESM-MR) āļ āļēāļĒāđāļāđāļāļēāļĢāļāļĨāđāļāļĒāļāđāļēāļāđāļĢāļ·āļāļāļāļĢāļ°āļāļāđāļāļĢāļ°āļāļąāļāļāļēāļāļāļĨāļēāļ (RCP4.5) āđāļĨāļ°āļĢāļ°āļāļąāļāļŠāļđāļāļĄāļēāļ (RCP8.5) āļāđāļāļĄāļđāļĨāļ āļđāļĄāļīāļāļēāļāļēāļĻāđāļāđāļāļđāļāļŠāļāļąāļāđāļĨāļ°āļāļĢāļąāļāđāļāđāļāļ§āļēāļĄāļāļđāļāļāđāļāļāļāđāļ§āļĒāđāļāļāļāļģāļĨāļāļ CMhyd 2) āļāļēāļĢāļāļĢāļ°āđāļĄāļīāļāļāļĢāļīāļĄāļēāļāļāđāļģāļāđāļēāđāļāļāļāļēāļāļāļ āļēāļĒāđāļāđāđāļāļ·āđāļāļāđāļ RCP4.5 āđāļĨāļ° RCP8.5 āđāļāļĒāđāļāđāđāļāļāļāļģāļĨāļāļ SWAT 3) āļāļēāļĢāļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāļāļēāļāđāļĨāļ°āļāļ§āļēāļĄāļāļĩāđāļāļāļāļāđāļģāļāđāļ§āļĄāđāļāļĒāđāļāđāļāļēāļĢāđāļāļāđāļāļ Log Pearson Type III āļāļēāļāļāļĢāļīāļĄāļēāļāļāđāļģāļāđāļēāļŠāļđāļāļŠāļļāļāļĢāļēāļĒāļāļĩāļāļēāļāđāļāļāļāļģāļĨāļāļ SWAT āđāļĨāļ°āļāļēāļāļāļēāļĢāļāļĢāļ§āļāļ§āļąāļāđāļāļāļāļĩāļāđāļāļāđāļ§āļ āļ.āļĻ. 1993â2019 āļāļķāđāļāļāļĢāļīāļĄāļēāļāļāđāļģāļāđāļ§āļĄāļŠāļđāļāļŠāļļāļāļāļĩāđāļāļēāļāļ§āđāļēāļāļ°āđāļāļīāļāļāļķāđāļāđāļāļāļāļēāļāļāđāļāđāļāļģāļŦāļāļāļĢāļāļāļāļĩāļāļēāļĢāđāļāļīāļāļāđāļģāļāļĩāđāđāļāļāļāđāļēāļāļāļąāļ āđāļāđāđāļāđ āļĢāļāļ 25, 50, 100 āđāļĨāļ° 200 āļāļĩ 4) āļāļēāļĢāļāļģāļĨāļāļāļĨāļąāļāļĐāļāļ°āļāļēāļāļāļĨāļĻāļēāļŠāļāļĢāđ āđāļāļ·āđāļāļŦāļēāļāļ§āļēāļĄāļĨāļķāļāļāļāļāļāđāļģāļāđāļ§āļĄāđāļĨāļ°āļāļ§āļēāļĄāđāļĢāđāļ§āļāđāļģāļāđāļ§āļĄ āļāļāļāđāļāđāļĨāļ°āļĢāļāļāļāļĩāļāļēāļĢāđāļāļīāļāļāđāļģāđāļāļĒāđāļāđ āđāļāļāļāļģāļĨāļāļ HEC-RAS āđāļĨāļ° 5) āļāļēāļĢāļāļĢāļ°āđāļĄāļīāļāļĢāļ°āļāļąāļāļāļ·āđāļāļāļĩāđāđāļŠāļĩāđāļĒāļāļāđāļģāļāđāļ§āļĄ āđāļāļĒāđāļāđāļŦāļĨāļąāļāļāļēāļĢ Flood Hazard Rating (FHR) āļāđāļ§āļĒāđāļāļĢāđāļāļĢāļĄ ArcGIS āļāļĨāļāļēāļĢāļĻāļķāļāļĐāļēāļāļĩāđāđāļŦāđāđāļŦāđāļāļ§āđāļēāļāļ·āđāļāļāļĩāđāđāļŠāļĩāđāļĒāļāļāđāļģāļāđāļ§āļĄāđāļāļ·āđāļāļāļāļēāļāļāļēāļĢāđāļāļĨāļĩāđāļĒāļāđāļāļĨāļāļŠāļ āļēāļāļ āļđāļĄāļīāļāļēāļāļēāļĻāļ āļēāļĒāđāļāđāđāļāļ·āđāļāļāđāļ RCP4.5 āđāļĨāļ° RCP8.5 āļĄāļĩāđāļāļ§āđāļāđāļĄāļāļĩāđāļāļ°āđāļāļīāđāļĄāļāļķāđāļ āđāļĨāļ°āļāļ·āđāļāļāļĩāđāđāļŠāļĩāđāļĒāļāļāđāļģāļāđāļ§āļĄāļ āļēāļĒāđāļāđāđāļāļ·āđāļāļāđāļ RCP8.5 āļāļ°āļŠāļđāļāļāļ§āđāļē RCP4.5 āđāļāļĒāđāļāļĨāļĩāđāļĒāļāļĢāļ°āļĄāļēāļ 7.44% āļāđāļēāļāļ§āļēāļĄāđāļāļāļāđāļēāļāļāļĩāđāļāļĩāđāđāļŦāđāđāļŦāđāļāļ§āđāļēāļāļēāļĢāļāļąāļāļāļēāļĢāļāļ§āļēāļĄāđāļŠāļĩāđāļĒāļāļāļēāļāļāđāļģāļāđāļ§āļĄāļ āļēāļĒāđāļāđāđāļāļ·āđāļāļāđāļ RCP8.5 āļāļ§āļĢāđāļāļīāđāļĄāļĢāļ°āļāļąāļāļāļēāļĢāļāļąāļāļāļēāļĢāļĄāļēāļāļāļ§āđāļē RCP4.5 āļāļ·āđāļāļāļĩāđāđāļŠāļĩāđāļĒāļāļāđāļģāļāđāļ§āļĄāļĢāļ°āļāļąāļāļĄāļēāļ āļŠāđāļ§āļāđāļŦāļāđāļāļĒāļđāđāļāļĢāļīāđāļ§āļāļāđāļēāļāļāđāļāļāđāļģāđāļĨāļ°āļāđāļēāļĒāļāđāļģ āđāļĨāļ°āļāļ·āđāļāļāļĩāđāđāļŠāļĩāđāļĒāļāļāļēāļāļāļĨāļēāļāļŠāđāļ§āļāđāļŦāļāđāļāļĒāļđāđāļāļĢāļīāđāļ§āļāļāļāļāļāļĨāļēāļāļāļąāđāļāđāļāđāļāļ·āđāļāļāđāļ RCP4.5 āđāļĨāļ° RCP8.5 āļŠāđāļ§āļāļāļĢāļīāļĄāļēāļāļāļāđāļāļāđāļ§āļāļĪāļāļđāđāļĨāđāļāđāļāļīāđāļĄāļāļķāđāļ 9.27% (RCP4.5) āđāļĨāļ° 1.27% (RCP8.5) āđāļĨāļ°āļāđāļ§āļāļĪāļāļđāļāļāđāļāļīāđāļĄāļāļķāđāļ 17.42% (RCP4.5) āđāļĨāļ° 21.98% (RCP8.5) āļŠāļģāļŦāļĢāļąāļāļāļĢāļīāļĄāļēāļāļāđāļģāļāđāļēāđāļāļāđāļ§āļāļĪāļāļđāđāļĨāđāļāđāļāļīāđāļĄāļāļķāđāļ 8.16% (RCP4.5) āđāļĨāļ° 4.07% (RCP8.5) āļŠāđāļ§āļāđāļāļĪāļāļđāļāļāđāļāļīāđāļĄāļāļķāđāļ 13.43% (RCP4.5) āđāļĨāļ° 18.11% (RCP8.5) āļāļĨāļāļĩāđāđāļāđāļĢāļąāļāļāļēāļāļāļēāļĢāļ§āļīāļāļąāļĒāļāļĢāļąāđāļāļāļĩāđāļĄāļĩāļāļĢāļ°āđāļĒāļāļāđāļāļĒāđāļēāļāļĒāļīāđāļāđāļāļāļēāļĢāđāļŦāđāļāđāļāļĄāļđāļĨāđāļāļ·āđāļāļāļāđāļāđāļāđāļŦāļāđāļ§āļĒāļāļēāļāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļāđāļĨāļ°āļāļāđāļāļāļļāļĄāļāļāđāļāļ·āđāļāđāļāļĢāļĩāļĒāļĄāļĢāļąāļāļĄāļ·āļāļāļąāļāđāļŦāļāļļāļāļēāļĢāļāđāļāļļāļāļāļ āļąāļĒāđāļāļĒāđāļāļāļēāļ°āļāļēāļĢāļāļąāļāļāļēāļĢāļāļēāļĢāđāļāđāļāļĩāđāļāļīāļThis study aims to assess flood risk areas due to climate change in the Khongsedon floodplain, Salavan province, Lao PDR. The methodology is divided into five subsections: 1) extracting and bias correcting climatic data in the period of A.D. 2020â2100 from MPI-ESM-MR model under moderate greenhouse gas emissions (RCP4.5) and very high greenhouse gas emissions (RCP8.5). The climatic data are extracted and bias corrected by CMhyd model; 2) estimating the future streamflow under RCP4.5 and RCP8.5 using SWAT model; 3) analysis of flood magnitude and frequency using Log Pearson type III distribution of annual maximum streamflow obtained from SWAT model and historical annual maximum streamflow during the period between A.D. 1993â2019. The peak flows were estimated for different return periods such as 25, 50, 100, and 200 years; 4) simulating the hydraulic characteristic s (i.e. flood depth and flood velocity) of each return period using HEC-RAS; and 5) assessment levels of flood prone areas using Flood Hazard Rating (FHR) by ArcGIS. The results indicate that the flood risk areas due to climate change under RCP4.5 and RCP8.5 are more likely to increase, and the flood risk areas under RCP8.5 will be higher than RCP4.5 on average approximately 7.44%. This difference value suggests that under RCP8.5 condition, the degree of management should be greater than the one of RCP4.5. The upper and downstream areas are susceptible to high flood risks while the central area is more likely to experience moderate risks under the RCP4.5 and RCP8.5 conditions. The rainfall in dry season increased by 9.27% (RCP4.5) and 1.27% (RCP8.5). In rainy season, it was found to increase by 17.42% (RCP4.5) and 21.98% (RCP8.5). The dry season streamflow under RCP4.5 and RCP8.5 increased by 8.16% and 4.07%, respectively. In rainy season, runoff increased by 13.43% (RCP4.5) and 18.11% (RCP8.5). The results obtained from this study are particularly useful in providing preliminary information to relevant agencies and people in the community for preparing and dealing with floods events, especially land use management
The Dynamics of Immature Rubber Photosynthetic Capacities Under Macronutrients Deficiencies
International audienceParÃĄ rubber produces natural latex which is essential for the industries. Rubber plant in immature phase is prone to macronutrient deficiencies due to improper management practices in the field and the nature of immature plants that have sensitive physiological responses under stress conditions. The study aimed to assess the effect of macronutrient limitation on immature rubber treesâ photosynthetic capacity and growth. The immature rubber was pot-grown inside the greenhouse with a completely randomized design experiment and nutrient limitations used as the treatments. The treatments consisted of 5 levels, namely, NPK; NP (-K); NK (-P); PK (-N); Control (-NPK). Photosynthetic capacity parameters (Vc max: maximum rate RuBisCO carboxylation, Jmax: RuBP regeneration rate, and TPU: Triose Phosphate Utilization), tree growth (plant height, flush number, leaf number, stem diameter), and leaf macronutrient (N, P, and K) concentrations were periodically measured. Welschâs test (Îą = 0.05) continued with Games-Howell pairwise comparison, followed by Pearsonâs correlation test and polynomial regressions were performed to describe the nutrient limitation and photosynthetic capacity relationships. Results showed that the leaf nutrient concentration corresponds with the given treatments, even though it was above the critical level for immature rubber. The limitation of N fertilization slightly reduced plant development and growth such as height, leaf number, flush number, relative growth rate, and photosynthetic capacities. However, the P and K limitation effect could not be observed clearly in the observation periods on growth and photosynthetic capacity parameters. Furthermore, the mobility rate of nutrients from the soil to the plants and its translocation inside plant organs played more essential role in plant growth and photosynthetic capacities. Prolonged observation periods on various rubber clones have to be performed to deeply understand the effects of nutrient deficiencies on immature rubber tree morphophysiological activities. HIGHLIGHTS Rubber plant in immature phase have sensitive physiological responses under stress conditions, and it is prone to macronutrient deficiencies due to improper management practices in the field Assessment of macronutrient limitation effect on immature rubber treesâ photosynthetic capacity and growth is essential to understand how the plants strive under the nutrient scarcity and providing a perspective which nutrient is more essential The N fertilization played more essential role compared to P and K, for immature rubber growth and photosynthetic activity GRAPHICAL ABSTRAC
Distinct morphological, physiological, and biochemical responses to light quality in barley leaves and roots
Light quality modulates plant growth, development, physiology, and metabolism through a series of photoreceptors perceiving light signal and related signaling pathways. Although the partial mechanisms of the responses to light quality are well understood, how plants orchestrate these impacts on the levels of above- and below-ground tissues and molecular, physiological, and morphological processes remains unclear. However, the re-allocation of plant resources can substantially adjust plant tolerance to stress conditions such as reduced water availability. In this study, we investigated in two spring barley genotypes the effect of ultraviolet-A (UV-A), blue, red, and far-red light on morphological, physiological, and metabolic responses in leaves and roots. The plants were grown in growth units where the root system develops on black filter paper, placed in growth chambers. While the growth of above-ground biomass and photosynthetic performance were enhanced mainly by the combined action of red, blue, far-red, and UV-A light, the root growth was stimulated particularly by supplementary far-red light to red light. Exposure of plants to the full light spectrum also stimulates the accumulation of numerous compounds related to stress tolerance such as proline, secondary metabolites with antioxidative functions or jasmonic acid. On the other hand, full light spectrum reduces the accumulation of abscisic acid, which is closely associated with stress responses. Addition of blue light induced accumulation of Îģ-aminobutyric acid (GABA), sorgolactone, or several secondary metabolites. Because these compounds play important roles as osmolytes, antioxidants, UV screening compounds, or growth regulators, the importance of light quality in stress tolerance is unequivocal