Abstract Switchgrass (Panicum virgatumL.) is a prominent bioenergy crop with robust resilience to environmental stresses. However, our knowledge regarding how precipitation changes affect switchgrass photosynthesis and its responses to light and CO2remains limited. To address this knowledge gap, we conducted a field precipitation experiment with five different treatments, including −50%, −33%, 0%, +33%, and +50% of ambient precipitation. To determine the responses of leaf photosynthesis to CO2concentration and light, we measured leaf net photosynthesis of switchgrass under different CO2concentrations and light levels in 2020 and 2021 for each of the five precipitation treatments. We first evaluated four light and CO2response models (i.e., rectangular hyperbola model, nonrectangular hyperbola model, exponential model, and the modified rectangular hyperbola model) using the measurements in the ambient precipitation treatment. Based on the fitting criteria, we selected the nonrectangular hyperbola model as the optimal model and applied it to all precipitation treatments, and estimated model parameters. Overall, the model fit field measurements well for the light and CO2response curves. Precipitation change did not influence the maximum net photosynthetic rate (Pmax) but influenced other model parameters including quantum yield (α), convexity (θ), dark respiration (Rd), light compensation point (LCP), and saturated light point (LSP). Specifically, the meanPmaxof five precipitation treatments was 17.6 μmol CO2m−2 s−1, and the ambient treatment tended to have a higherPmax. The +33% treatment had the highestα, and the ambient treatment had lowerθandLCP, higherRd, and relatively lowerLSP. Furthermore, precipitation significantly influenced all model parameters of CO2response. The ambient treatment had the highestPmax, largestα, and lowestθ,Rd, and CO2compensation pointLCP. Overall, this study improved our understanding of how switchgrass leaf photosynthesis responds to diverse environmental factors, providing valuable insights for accurately modeling switchgrass ecophysiology and productivity.
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Nanoparticle-enabled integration of air capture and conversion of CO 2
This work demonstrates a nanoparticle-enabled integration of air capture and conversion of CO2. Ambient CO2is captured in a KOH–ethylene glycol solution and then selectively reduced to formate under 50 °C and ambient pressure using Pd NPs.
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- PAR ID:
- 10612401
- Publisher / Repository:
- Royal Society of Chemistry
- Date Published:
- Journal Name:
- Nanoscale
- Volume:
- 16
- Issue:
- 39
- ISSN:
- 2040-3364
- Page Range / eLocation ID:
- 18620 to 18628
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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