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56 results for “Plant physiology”
Management and plant physiology data for grassland sites in Germany
<p>Management and vegetation data for sites Fendt (DE-Fen), Rottenbuch (DE-RbW) and Graswang (DE-Gwg) in Southern Germany, observed between 2012 and 2017. Weekly resolution vegetation traits are included for 2015.</p> <p>The sites are part of TERENO, a network of observatories in Germany. The time period includes the ScaleX intensive observation campaigns that took place in 2015 and 2016. The data format is NetCDF4. A Jupyter notebook is available (see Related identifiers, GitLab) with technical notes and examples. </p>
Fig. 1 in Protease inhibitors of fodder plants as a factor of immune response influencing the physiological state of the potato ladybird beetle Henosepilachna vigintioctomaculata (Coleoptera: Coccinellidae)
Fig. 1. Analysis of the population of the potato ladybird beetle with the species-specific PCR-markers of the gene COI mtDNA. А – species-specific marker for H. vigintioctopunctata, 400 b.p.; Б – species-specific marker for H. vigintioctomaculata, 406 b.p.; М – marker of the lengths of fragments 100 b.p. ladder; 1–3 – Primorsky krai: Chuguevsky district; 4–6 – Amurskaya oblast; 7–17 – Primorsky krai: Timiryazevsky.
Fig. 3 in Protease inhibitors of fodder plants as a factor of immune response influencing the physiological state of the potato ladybird beetle Henosepilachna vigintioctomaculata (Coleoptera: Coccinellidae)
Fig. 3. Sinergetic activity of the protainases of trypsin type (in an insect) and trypsin inhibitors (in a plant) in the course of feeding on different potato varieties.
Figure 1 in Crop physiological considerations for combining variable-density planting to optimize seed costs and weed suppression
Figure 1. Schematic representation of (A) an aerial image using an unmanned aerial vehicle (UAV) to scout fields in year 1, (B) detection of areas of high (orange) and low (yellow) weed density in year 1, and (C) implementation of year 1 weed maps to calibrate precision planter to plant in high (red) and low (green) crop densities in year 2.
Figure 2 in Crop physiological considerations for combining variable-density planting to optimize seed costs and weed suppression
Figure 2. Schematic diagram representing the workflow process of the area planting optimization model. The graph on the bottom left corresponds to low-density planting yields of maize (red circles, solid line, y = 288.5 − 2.07x), cotton (gray triangles, dashed line, y = 176 − 1.58x), and soybean (blue squares, dotted line, y = 86.5 − 0.70x) in g seed−1.
Fig. 4 in Physiological Responses Of Rare Coastal Salt Marsh Plant Triglochin Maritima L. To Soil Chemical Heterogeneity
Fig. 4. Time-course of Peformance Index (A) and chlorophyll concentration (B) in leaves of T. maritima plants grown in different substrates.
Fig. 7 in Physiological Responses Of Rare Coastal Salt Marsh Plant Triglochin Maritima L. To Soil Chemical Heterogeneity
Fig. 7. Correlation between summary Na + K concentration and extract EC in leaves (A) and roots (B) of T. maritima plants.
Fig. 1 in Physiological Responses Of Rare Coastal Salt Marsh Plant Triglochin Maritima L. To Soil Chemical Heterogeneity
Fig. 1. Effect of treatment type on soil electrical conductivity (A) and pH (B) after 8 weeks of cultivation.
Fig. 5 in Physiological Responses Of Rare Coastal Salt Marsh Plant Triglochin Maritima L. To Soil Chemical Heterogeneity
Fig. 5. Time-course of Na+ (A), K+ (B) and Ca2+ concentration in leaves of T. maritima plants grown in different substrates.
Fig. 6 in Physiological Responses Of Rare Coastal Salt Marsh Plant Triglochin Maritima L. To Soil Chemical Heterogeneity
Fig. 6. Effect of treatment type on Na+ (A) and K+ (B) concentration in roots of T. maritima plants after 8 weeks of cultivation.
Рис. 1. КоΛичество макрокониΑий грибов роΑа Fusarium (% от общего чисΛа эΛементов морфоΛогии) на органах и в физиоΛогических жиΑкостях картофеΛьной коровки Fig. 1. Number of macroconidia of fungus species from the genus Fusarium (% of the total number of morphological elements) on organs and in physiological fluids of the potato ladybird beetle in On the vector characteristics of the potato ladybird beetle Henosepilachna Vigintioctomaculata (Motsch.) (Coleoptera, Coccinellidae) in the system "phytophagous insect - plant pathogen - plant"
Рис. 1. КоΛичество макрокониΑий грибов роΑа Fusarium (% от общего чисΛа эΛементов морфоΛогии) на органах и в физиоΛогических жиΑкостях картофеΛьной коровки Fig. 1. Number of macroconidia of fungus species from the genus Fusarium (% of the total number of morphological elements) on organs and in physiological fluids of the potato ladybird beetle
FIGURE 1 in Fish injuries resulting from transient operating conditions in a Brazilian hydropower plant: morphological, physiological and biochemical evaluation in Pimelodus maculatus (Siluriformes: Pimelodidae)
FIGURE 1 | Histological gill alterations in Pimelodus maculatus collected during transient operating conditions (magnification: × 400). Arrows indicate the following lesions: A. Aneurysm; B. Epithelium detachment; C. Telangiectasia; and D. Interlamellar hyperplasia.
FIGURE 2 in Fish injuries resulting from transient operating conditions in a Brazilian hydropower plant: morphological, physiological and biochemical evaluation in Pimelodus maculatus (Siluriformes: Pimelodidae)
FIGURE 2 | Histological alterations in liver and spleen of Pimelodus maculatus collected during transient operating conditions in the tailrace of Machadinho HPP (magnification: × 400). Arrows and asterisks indicate the following lesions: A. Melanomacrophage centers (asterisk) and congested vein (arrow) in the liver; B. Blood cells indicating hepatic hemorrhage (asterisk); C. Melanomacrophage centers in the spleen (asterisk); D. Mononuclear inflammatory infiltrate in the spleen (arrow).
Linked collectors and determiners for: The Herbarium Fund of the Institute of Botany, Plant Physiology and Genetics at the Tajikistan National Academy of Sciences - BRAHMS records.
Natural history specimen data linked to collectors and determiners held within, "The Herbarium Fund of the Institute of Botany, Plant Physiology and Genetics at the Tajikistan National Academy of Sciences - BRAHMS records". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/d4b0f477-0ddf-4c47-a1fe-a7ffed28788e">https://bionomia.net/dataset/d4b0f477-0ddf-4c47-a1fe-a7ffed28788e</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/d4b0f477-0ddf-4c47-a1fe-a7ffed28788e">https://gbif.org/dataset/d4b0f477-0ddf-4c47-a1fe-a7ffed28788e</a>. Formatted as a Frictionless Data package.
Plant Water Potentials and Plant Physiology at the Sevilleta National Wildlife Refuge, New Mexico (1989-1992)
Physiological status of plants is monitored in conjunction with the sampling schedule outlined in Sevilleta Plant Demography. Several perennial life forms, including tree (Juniperus and Pinus), shrub (Larrea) and grass (Oryzopsis and Sporobolus), are being monitored at 1-3 of four sites which differ in elevation and topography as well as edaphic and annual precipitation characteristics. For the 1990 field season we are adding a spring annual, Lesquerella to our sampling efforts at these same sites. Currently, water status (xylem potentials, bars) is monitored twice a year, in spring (after the 'dry' season) and fall (after the 'wet' season). Three replicate measurements are made on each of 10-20 individuals per species per site. Three measurements are made at pre-dawn and midday to determine the diurnal range of values for each plant. For the 1990 field season, we will also be measuring peak photosynthetic rates for selected individuals by gas exchange measurements and porometry. Together with demographic data, this data set permits assessment of the physiological bases of plant growth and reproduction in response to short- and long-term changes in abiotic and biotic aspects of the environment.
Fifteen physiological traits related to osmoregulation and reactive oxygen species metabolism in two life form aquatic plants under a natural water salinity gradient on the Tibetan Plateau and Northwest China
<p><span>Aquatic plants, as the primary producers, determine the community structure and ecological function of freshwater ecosystems. However, salinization threatens inland freshwater wetlands and thus the survival of aquatic plants. Exploring the plant physiological responses to increasing water salinity could enhance our understandings of plant adaptive strategies under future climate change regimes in wetlands. We measured 15 physiological traits of 49 aquatic plant species along a large environmental gradient in alpine and arid regions of western China, to explore the physiological adaptions and compare the similarities and differences in adaptive strategies between the two life forms to natural water salinity. We found that both water salinity and low temperature were key factors affecting aquatic plants in alpine and arid regions. Aquatic plants adapt to saline habitats by accumulating proline and sulfur (S) concentrations, and to cold habitats by increasing ascorbate peroxidase activity. Plant trait network analysis showed that the hub trait in emergent plants was S, but in submerged plants was proline, suggesting that emergent plants balanced osmoregulation and reactive oxygen metabolism via S-containing compounds, while submerged plants prioritizing the regulation of osmotic balance via proline.</span></p>
Data supporting "Stems Matter: Xylem Physiological Limits Are an Accessible and Critical Improvement to Models of Plant Gas Exchange in Deep Time"
<p>Model outputs from from <em>Paleo</em>-BGC and <em>Paleo</em>-BGC+. Code detailing data structure and allowing reproduction of analysis can be found at github.com/wjmatthaeus</p>
Data for "The effect of drought on agronomic and plant physiological characteristics of cocksfoot (Dactylis glomerata L.) cultivars "
<p>Data for " The effect of drought on agronomic and plant physiological characteristics of cocksfoot (Dactylis glomerata L.) cultivars "</p> <p>Data include all raw data necessary for the analyses of the manuscript. These include data on climatic parameters the experiment design, the growth, the fresh and dry matter yield, the crude protein content, the water use and the water use efficiency.</p> <p> </p> <p>Description of the data and file structure</p> <p>The data are divided into two sheets. The first contains data necessary for the analyses presented in the main text. The second includes data about temperature solar radiation and Vapor Pressure.</p>
Fig. 2. A in Physiological Responses Of Rare Coastal Salt Marsh Plant Triglochin Maritima L. To Soil Chemical Heterogeneity
Fig. 2. A typical morphology of T. maritima plants grown in different substrates for 7 weeks.
Expression data of the flowering time genes in chickpea, extracted from Ridge et al. (2017). Plant Physiology 175, 802-815.
<p>This data is supplementary to the following paper: Gursky, V.V., Kozlov, K.N., Nuzhdin, S.V., and Samsonova, M.G. (2018) Dynamical Modeling of the Core Gene Network Controlling Flowering Suggests Cumulative Activation from the <em>FLOWERING LOCUS T </em>Gene Homologs in Chickpea. <em>Frontiers in Genetics</em>. 9:547. doi: 10.3389/fgene.2018.00547</p> <p>The data was obtained by digitizing Figure 5 of the following paper: Ridge, S., Deokar, A., Lee, R., Daba, K., Macknight, R. C., Weller, J. L., and Tar'an, B. (2017). The chickpea Early flowering 1 (Efl1) locus is an ortholog of arabidopsis ELF3. <em>Plant Physiology </em>175, 802-815. doi:10.1104/pp.17.00082</p> <p>The archive contains files (in csv format) with the expression data of each of the following ten genes: <em>FTa1</em>, <em>FTa2</em>, <em>FTa3</em>, <em>FTb</em>, <em>FTc</em>, <em>AP1</em>, <em>FD</em>, <em>TFL1a</em>, <em>TFL1c</em>, and <em>LFY</em>, for the cultivars CDC Frontier and ICCV 96029 and for two growth conditions (long day, LD, and short day, SD). Each file is named according to the following scheme: <Gene name>_<Cultivar name>_<Growth conditions>.csv. Each file contains values in the following three columns (separated by commas): time (in days after sowing), relative transcription level (%ACTIN), and standard error. In the case of the genes <em>AP1</em>, <em>FD</em>, <em>TFL1a</em>, <em>TFL1c</em>, and <em>LFY</em>, the standard error was assumed equal to the size of the points in the figure when the actual error range was smaller than that size (and, thus, not visible in the figure). In the case of the genes <em>FTa1</em>, <em>FTa2</em>, <em>FTa3</em>, <em>FTb</em>, and <em>FTc</em>, the standard error was recorded as 0 for such points (the error for these genes was not used in the study).</p> <p>The data was extracted with the help of the web-based tool <em>WebPlotDigitizer</em> (https://automeris.io/WebPlotDigitizer).</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.