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222 results for “photosynthesis”

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Convergence in phosphorus constraints to photosynthesis dataset - modelling results

The archive contains the extract of model results shown in the publication 'Convergence in phosphorus constraints to photosynthesis' by David Ellsworth et al. in Nature Communication. README: # Simulation results from ORCHIDEE LSM v1.2 (https://doi.org/10.14768/20200407002.1) # time period: 1992-2021 # author: Daniel Goll (dsgoll123@gmail.com) # the following variables are found in these files: # GPP [g/m2/yr]                                         -> gpp.nc # POTENTIAL GPP (assuming maximum P content) [g/m2/yr]  -> gpp_pot_max.nc # POTENTIAL GPP (assuming average P content) [g/m2/yr]  -> gpp_pot_avg.nc # LEAF N:P RATIO [g/g]                                  -> leafNP.nc

opencc-by-4.0Jun 2022View details →

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Assessment of microphytobenthos communities in the Kinzig catchment using photosynthesis-related traits, digital light microscopy and 18S-V9 amplicon sequencing

This folder contains the datasets used in the article submitted to Frontiers in Ecology and Evolution in which we investigated the functional and compositional responses of microphytobenthos communities to surrounding land uses in the Kinzig River catchment, central Germany. We measured photosynthetic biomass using a Benthotorch, and analysed the diatom community using a newly developed digital light microscopy approach and 18S-V9 amplicon sequencing to characterise the whole protistan assemblages at sampling sites located in rural vs. urban areas. The folder contain the following datasets: kinzig2021_18SV9_filtered.csv  # microphytobenthos 18SV9 amplicon sequencing data kinzig_paper.csv # OMNIDIA output of diatom data from microscopy and diatom subset from 18SV9 amplicon sequencing (including 4 letters OMINIDIA taxa codes for diatoms) kinzig2021_benthotorch.csv # Photosynthetic biomass (BenthoTorch data) Kinzig2021_fieldData.csv # environmental data env_dataKinz2021.csv # environment dataset Kinzig2021_diatDM&18S.R # Rscript used for analysis

opencc-by-4.0Apr 2024View details →

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Data and code to map the genomic potential for photosynthesis in piconanoplankton

This archive contains the R and Python scripts, model outputs and technical documentation corresponding to an application of the Bluecloud Plankton Genomic Virtual Lab workflow to map the genomic potential for photosynthesis in piconanoplankton. Alternatively, the workflow is also accessible via the bluecloud catalogue at <a href="https://data.d4science.net/Zraq">https://data.d4science.net/Zraq</a> or at the following Github repository <a href="https://github.com/alexschickele/bluecloud/releases/tag/v1.0">https://github.com/alexschickele/bluecloud/releases/tag/v1.0</a>

opencc-by-4.0Apr 2024View details →

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Dataset for "High photosynthesis rates in Brassiceae species are mediated by leaf anatomy enabling high biochemical capacity, rapid CO2 diffusion and efficient light use"

Dataset used in the paper Retta MA, Van Doorselaer L, Driever SM, Yin X, de Ruijter NCA, Verboven P, Nicolaï BM, Struik PC. High photosynthesis rates in Brassiceae species are mediated by leaf anatomy enabling high biochemical capacity, rapid CO2 diffusion and efficient light use. New Phytol. 2024 Sep 18. doi: 10.1111/nph.20136. PMID: 39294895. Please cite the paper presenting this datase. <h1>Plant Species and Inbred Lines:</h1> <ul> <li>Hirschfeldia incana L. (7th generation inbred line 190003 HIN-NIJ-07-B) </li> <li>Brassica nigra L. (3rd generation inbred line 210093 BNI-DG1-03-B)</li> <li>Brassica rapa L. (inbred line ‘R-o-18’)</li> <li>Arabidopsis thaliana (accession Columbia)</li> </ul> <h1>Growth Conditions:</h1> <ul> <li>Media: Rock-wool blocks (Grodan Plantop, Roermond, Netherlands, 10×10×7.5 cm)</li> <li>Fertigation: Nitrogen-rich nutrient solution via automated dripping system.</li> <li>Light Conditions: 12 h day/12 h night, light intensity of 200 µmol m-2 s-1 and 1800 µmol m-2 s-1</li> <li>Temperature: Day/Night temperatures of 23 °C and 20 °C, respectively.</li> <li>Relative Humidity: 70%</li> </ul> <h1>Codes</h1> Species: <ul> <li>Hirschfeldia incana L. - H. incana</li> <li>Brassica nigra L. - B. nigra</li> <li>Brassica rapa L. - B. rapa</li> <li>Arabidopsis thaliana - A. thaliana</li> </ul> Light conditions: <ul> <li>High light - HL</li> <li>Low light - LL</li> </ul> Replicates: <ul> <li>Biological replicates were labeled with numbers, e.g. replicate one from high light grown Hirschfeldia incana is referred to as HiHL1</li> </ul> <h1>Measurements</h1> <h2>Leaf Gas Exchange and Chlorophyll Fluorescence Measurements (GasExchangeData.zip):</h2> <ul> <li>Four leaves per species per treatment.</li> <li>Conducted using a LI-6800 (LI-COR, Lincoln, NE, USA) on the mid-position of the youngest fully expanded leaf.</li> <li>The resoponse of photosynthesis to irradiance and external CO2 concentrations augumneted with multi-phase flash fluorescence were made</li> </ul> <h2>Optical Properties Measurement (Absorbance & chlorophyll.zip):</h2> <ul> <li>Leaves: Four leaves per species per treatment.</li> <li>Leaf transmittance and reflectance measured using a dual channel spectrophotometer (absorptance_reflac_data_355_750.xlsx)</li> <li>Chlorophyll content measured using a spectrophotometer (Chlorophyll.xlsx).</li> </ul> <h2>Stomatal Density and Size Analysis (Stomata.zip):</h2> Sampling: <ul> <li>Leaves: Four leaves per species per treatment.</li> <li>Plants: Samples taken from three different plants.</li> <li>Leaf-side: abaxial and adxial leaf side.</li> </ul> Microscopy Setup: <ul> <li>Stomatal imprints made using clear nail polish, imaged using a light microscope at 20x.</li> </ul> Data Output: <ul> <li>Imaging Results: .jpg files organised under folders for species e.g. AtHL\R1 T+B.zip contains images ofimprints of top (T) and bottom (B) leaf sides from replicate plant 1 (R1) of A. thaliana grown under high light (AtHL). The images are named as for example, AT_HL_BOTTOM_R1_A_stacked_minimum.jpg, The leters A to E label various imges made from one imprint.</li> </ul> <h2>Light and Electron Microscopy of Leaf Sections (CellwallChloroplast.zip):</h2> Sampling: <ul> <li>Leaves: Four leaves per species per treatment.</li> <li>Plants: Samples taken from four different plants.</li> </ul> Sample preparation <ul> <li>Leaf samples fixed, dehydrated, embedded in Araldite, and sectioned for imaging.</li> <li>1 µm think sections were made for light microscopy</li> <li>Sections  of 70 nm were double stained for TEM</li> </ul> Microscopy Setup: <ul> <li>Mesophyll cells imaged at 400x and 700x to measure chloroplast coverage.</li> <li>Electron microscopy performed with Zeiss EM900 electron microscope.</li> </ul> <h2>Mesophyll Chlorophyll (ConfocalData.zip):</h2> Sampling: <ul> <li>Leaves: Three leaves per species per treatment.</li> <li>Plants: Samples taken from three different plants.</li> <li>Thickness: 200 ± 10 µm sections prepared using a sliding microtome</li> </ul> Microscopy Setup: <ul> <li>Microscope: Leica DM8 inverted scope equipped with a Stellaris 5 confocal microscope (Leica Microsystems, Wetzlar, Germany).</li> <li>Excitation: 490 nm excitation laser line</li> <li>Fluorescence Recording: Chlorophyll autofluorescence recorded in a spectral range of 660−700 nm.</li> <li>Objective: Leica objective ×10/0.4 NA.</li> <li>Z-Stacks:  85–112 µm depth, two random positions per sample</li> </ul> Data Output: <ul> <li>Imaging Results: Z-stacks of chlorophyll autofluorescence in mesophyll cells.</li> <li>Spectral Information: Chlorophyll autofluorescence recorded in the 660−700 nm range.</li> </ul> Analysis: <ul> <li>Software: The confocal files are in .lif format and can be viewed using Leica application suite (LASx), ImageJ</li> </ul>

opencc-by-4.0Dec 2022View details →

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FIG. 2 in Does the removal of non-photosynthetic sections lead to a down-regulation of photosynthesis in mosses? A first experiment

FIG. 2. — Comparisons of the sample- (A-C) and mass- (D-F) based CO2 assimilation rates of green and brown moss sections, and the sum of these two sections (sample-based plots) and the changes through time for three moss species. Shown are the mean values ± standard errors (smaller than the symbol in some cases) of different sections determined at different time points, starting at a few minutes after separation. Sample-based plots are expressed as the CO2 exchange per sample to allow a direct comparison of intact and separated sections. Gray solid and dashed lines show the mean values of intact shoots (values shown to the right), ± standard errors. Asterisks indicate significant differences in assimilation rates between intact shoots and the sum of the separated sections (paired t-test, p<0.05, n = 4). And the capital and lowercase letters indicate significant differences among time points (p<0.05).

opencc-zeroMay 2021View details →

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FIG. 1 in Does the removal of non-photosynthetic sections lead to a down-regulation of photosynthesis in mosses? A first experiment

FIG. 1. — Shoots of the three moss species used for the "brown-section-removal" experiment, collected on the eastern slope of Gongga Mountain. A, Actinothuidium hookeri (Mitt.) Broth.; B, Pleuroziopsis ruthenica (Weinm.) Kindb. ex E. Britton; C, Pogonatum nudiusculum Mitt. The red arrows indicate the points where the brown and green sections were separated.

opencc-zeroMay 2021View details →

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Supporting data for Onyshchenko et al. 2018 Single loss of photosynthesis in diatoms

These are alignments from Onyshchenko, Ruck, Nakov and Alverson 2018: Single loss of photosynthesis in diatoms 16s.afa - Chloroplast 16s alignment of data from NCBI and newly generated data from the Alverson lab. Aligned with ssu-align agains the bacterial covariance model and masked to remove poorly aligned regions with default settings. cob.afa - Mitochondrial cob alignment of newly generated data from the Alverson lab. lsu.afa - Nuclear 28s alignment of newly generated data from the Alverson lab. Aligned with ssu-align against a heterokont covariance model of secondary structure and masked to remove poorly aligned regions with default settings. lsu-w-ncbi.afa - Nuclear 28s alignment of data from NCBI and newly generated data from the alverson lab. Aligned with ssu-align against a heterokont covariance model of secondary structure and masked to remove poorly aligned regions with default settings. mito.afa - Concatenation of cob and nad alignmnets. (new data only) mito-lsu.afa - Concatenation of cob, nad, and 28s alignmnets. (new data only) mito-ncbi-lsu.afa - Concatenation of cob, nad, and 28s alignments. (both new data and data from NCBI for 28s) nad.afa - Mitochondrial nad1 alignment of newly generated data from the Alverson lab. Nitz-meta-data.csv - Meta data for newly generated sequences.

opencc-by-4.0Feb 2018View details →

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Repository: Potential for Photosynthesis on Mars within snow and ice

This repository contains: 1. Modeled Spectral Irradiances (W m-2 micron-1) within Vertically Inhomogeneous Glacier Ice from Khuller, Warren, Christensen & Clow (2024) a) Fig_1_12cm_model: Modeled Spectral Irradiance at 12 cm  b) Fig_1_36cm_model: Modeled Spectral Irradiance at 36 cm  c) Fig_1_58cm_model: Modeled Spectral Irradiance at 58 cm  d) Fig_1_77cm_model: Modeled Spectral Irradiance at 77 cm  2. Modeled Spectral Actinic Flux (W m-2 micron-1) from Khuller, Warren, Christensen & Clow (2024) a) Clean Snow/Firn/Ice (without dust) at 33 S latitude     i) Fig_2a: Pure snow with 0.5 mm grain size     ii) Fig_2b: Pure firn with 2.5 mm grain size     iii) Fig_2c: Pure glacier ice with 14 mm grain size b) Clean Snow/Firn/Ice (without dust) at 54 N latitude     i) Ext_Fig_2a: Pure snow with 0.5 mm grain size     ii) Ext_Fig_2b: Pure firn with 2.5 mm grain size     iii) Ext_Fig_2c: Pure glacier ice with 14 mm grain size     c) Dusty Snow/Firn/Ice (with 0.01% dust by mass) at 33 S latitude     i) Fig_2d: Dusty snow with 0.5 mm grain size     ii) Fig_2e: Dusty firn with 2.5 mm grain size     iii) Fig_2f: Dusty glacier ice with 14 mm grain size d) Dusty Snow/Firn/Ice (with 0.01% dust by mass) at 54 N latitude     i) Ext_Fig_2d: Dusty snow with 0.5 mm grain size     ii) Ext_Fig_2e: Dusty firn with 2.5 mm grain size     iii) Ext_Fig_2f: Dusty glacier ice with 14 mm grain size e) Dusty Snow/Firn/Ice (with 0.1% dust by mass) at 33 S latitude     i) Fig_2g: Dusty snow with 0.5 mm grain size     ii) Fig_2h: Dusty firn with 2.5 mm grain size     iii) Fig_2i: Dusty glacier ice with 14 mm grain size f) Dusty Snow/Firn/Ice (with 0.1% dust by mass) at 54 N latitude     i) Ext_Fig_2g: Dusty snow with 0.5 mm grain size     ii) Ext_Fig_2h: Dusty firn with 2.5 mm grain size     iii) Ext_Fig_2i: Dusty glacier ice with 14 mm grain size     3. Modeled Depths for DNA Damage Limit, PAR Upper Limit, and PAR Lower Limit (meters) from Khuller, Warren, Christensen & Clow (2024) a) Sensitivity to dust content FILE FORMAT: Dust Content (ppmw), DNA Damage Limit Depth (m), PAR Lower Limit Depth (m), PAR Upper Limit Depth (m)     i) final_Depths_south_dust_sensitivity:  sensitivity to dust content for the martian southern hemisphere     ii) final_Depths_north_dust_sensitivity: sensitivity to dust content for the martian northern hemisphere b) Sensitivity to ice grain radius FILE FORMAT: Ice Grain Radius (micron), DNA Damage Limit Depth (m), PAR Lower Limit Depth (m), PAR Upper Limit Depth (m)     i) final_Depths_south_radius_sensitivity:  sensitivity to ice grain radius for the martian southern hemisphere     ii) final_Depths_north_radius_sensitivity: sensitivity to ice grain radius for the martian northern hemisphere c) Sensitivity to latitude FILE FORMAT: Latitude (degrees), DNA Damage Limit Depth (m), PAR Lower Limit Depth (m), PAR Upper Limit Depth (m)     i) final_Depths_south_latitude_sensitivity:  sensitivity to latitude for the martian southern hemisphere     ii) final_Depths_north_latitude_sensitivity: sensitivity to latitude for the martian northern hemisphere d) Sensitivity to solar zenith angle FILE FORMAT: Solar Zenith Angle (degrees), DNA Damage Limit Depth (m), PAR Lower Limit Depth (m), PAR Upper Limit Depth (m)     i) final_Depths_south_zenith_sensitivity:  sensitivity to solar zenith angle for the martian southern hemisphere     ii) final_Depths_north_zenith_sensitivity: sensitivity to solar zenith angle for the martian northern hemisphere 4. Wavelengths used for files listed in 1 from Khuller, Warren, Christensen & Clow (2024) wavelengths_greenland: wavelength in microns 5. Wavelengths used for files listed in 2 and 3 from Khuller, Warren, Christensen & Clow (2024) wavelengths: wavelength in microns 6. Depths used for files listed in 2 from Khuller, Warren, Christensen & Clow (2024) depths: depths in meters 7. Normalized DNA spectrum used in Khuller, Warren, Christensen & Clow (2024) norm_dna_spectrum: normalized DNA spectrum

opencc-by-4.0Aug 2024View details →

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The genome of a nonphotosynthetic diatom provides insights into the metabolic shift to heterotrophy and constraints on the loss of photosynthesis

Data associated with: Onyshchenko et al. 2021. <a href="https://doi.org/10.1111/nph.17673">The genome of a nonphotosynthetic diatom provides insights into the metabolic shift to heterotrophy and constraints on the loss of photosynthesis</a>. New Phytologist. Contents include: <ul> <li>Nitzschia Nitz4 genome sequence and annotation</li> <li>OrthoFinder inputs and outputs</li> <li>CAFE inputs and outputs</li> <li>Transcriptome assemblies</li> <li>Variant calling results</li> </ul> Use the command `tar -zxvf nitzschia.tgz` to unpack the archive.

opencc-by-4.0Aug 2021View details →

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Data for: Triose phosphate utilization stress during photosynthesis addressed with dynamic assimilation measurements

Oscillations in CO2 assimilation rate and associated fluorescence parameters have been observed alongside the triose phosphate utilization (TPU) limitation of photosynthesis for nearly 50 years. However, the mechanics of these oscillations are poorly understood. Here we utilize the recently developed Dynamic Assimilation Techniques (DAT) for measuring the rate of CO2 assimilation to increase our understanding of what physiological condition is required to cause oscillations. We found that TPU limiting conditions alone were insufficient, and that plants must enter TPU limitation quickly to cause oscillations. We found that ramps of CO2 caused oscillations proportional in strength to the speed of the ramp, and that ramps induce oscillations with worse outcomes than oscillations induced by step change of CO2 concentration. An initial overshoot is caused due to a temporary excess of available phosphate. During the overshoot, the plant out-performs steady state TPU and ribulose 1,5-bisphosphate regeneration limitations of photosynthesis but cannot exceed the rubisco limitation. We performed additional optical measurements which support the role of photosystem I reduction and oscillations in availability of NADP+ and ATP in supporting oscillations.

opencc-zeroDec 2022View details →

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Towards a Diverse Next-Generation Energy Workforce: Teaching Artificial Photosynthesis and Electrochemistry in Elementary Schools through Active Learning

Artificial photosynthesis is a promising approach to generate important commodity chemicals using abundant chemical feedstocks and renewable energy sources. Despite its importance, affordable and effective hands-on classroom activities that demonstrate artificial photosynthesis and teach key concepts, especially for primary school students, is lacking. This will be a critical step in the development of the next-generation energy workforce, especially one that is diverse in race and gender. To aid in this effort, we present an artificial photosynthesis lesson plan based on active-learning techniques that uses safe and highly accessible materials (baking soda, tap water, plastic jars, Ni coil, alligator clips, and a solar cell) to perform solar-powered water splitting. The efficacy of the lesson plan in teaching basic concepts of artificial photosynthesis was evaluated with pre- and post-test data, which shows a statistically significant improvement in overall student understanding. Importantly, the data show that the lesson plan presented here is effective at narrowing the performance gap between minority students and overly represented groups. This study aids in the development and education of a demographically diverse energy workforce through an active learning-based lesson plan for primary school students.

opencc-by-4.0Jan 2023View details →

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