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698 results for “Soybean”
Fig 2 in Survival, growth, and biomass of brine shrimp (Artemia franciscana) fed with spirulina powder and soybean flour
Fig 2: The body length of Artemia fed with different feeds at 21 days of rearing
Fig 1 in Survival, growth, and biomass of brine shrimp (Artemia franciscana) fed with spirulina powder and soybean flour
Fig 1: The survival rate of Artemia fed with different feeds at 21 days of rearing
Figure 2 in Replacement level of rubber seed cake for soybean meal on the growth of Japanese quail
Figure 2. Kernel of rubber seeds.
Figure 1 in Replacement level of rubber seed cake for soybean meal on the growth of Japanese quail
Figure 1. Raw rubber seeds from the plantation.
Fig. 1 in Evaluating categories of resistance in soybean genotypes from the United States and Brazil to Aphis glycines (Hemiptera: Aphididae)
Fig. 1. Damage level scale (1 to 5); feeding damage caused by Aphis glycines on soybean leaves.
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from pDSSAT soybean simulations
This data set contains output data from simulations with the model pDSSAT for soybean as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above-ground biomass, planting day, maturity day, anthesis day, potential irrigation water withdrawal, actual growing season evapotranspiration . Simulations are based on 31-year simulations using the AgMERRA (Ruane et al. 2015) data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A0= 'none', A1='regain original growing season').
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from GEPIC soybean simulations
This data set contains output data from simulations with the model GEPIC for soybean as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above-ground biomass, planting day, maturity day, potential irrigation water withdrawal, actual growing season evapotranspiration . Simulations are based on 31-year simulations using the AgMERRA (Ruane et al. 2015) data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A0= 'none', A1='regain original growing season').
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from EPIC-TAMU soybean simulations
This data set contains output data from simulations with the model EPIC-TAMU for soybean as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above-ground biomass, planting day, maturity day, actual growing season evapotranspiration . Simulations are based on 31-year simulations using the AgMERRA (Ruane et al. 2015) data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A0= 'none', A1='regain original growing season').
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from EPIC-IIASA soybean simulations
This data set contains output data from simulations with the model EPIC-IIASA for soybean as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above-ground biomass, planting day, maturity day, potential irrigation water withdrawal, actual growing season evapotranspiration . Simulations are based on 31-year simulations using the AgMERRA (Ruane et al. 2015) data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A0= 'none', A1='regain original growing season').
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from PEPIC soybean simulations
This data set contains output data from simulations with the model PEPIC for soybean as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above-ground biomass, planting day, maturity day, potential irrigation water withdrawal, actual growing season evapotranspiration . Simulations are based on 31-year simulations using the AgMERRA (Ruane et al. 2015) data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A0= 'none', A1='regain original growing season').
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from PROMET soybean simulations
This data set contains output data from simulations with the model PROMET for soybean as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above-ground biomass, planting day, maturity day, anthesis day, actual growing season evapotranspiration . Simulations are based on 31-year simulations using the ERA-Interim (Dee et al. 2011) data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A0= 'none', A1='regain original growing season').
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from APSIM-UGOE soybean simulations
This data set contains output data from simulations with the model APSIM-UGOE for soybean as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above-ground biomass, planting day, maturity day, anthesis day, potential irrigation water withdrawal, actual growing season evapotranspiration . Simulations are based on 31-year simulations using the AgMERRA (Ruane et al. 2015) data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A0= 'none', A1='regain original growing season').
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from CARAIB soybean simulations
<p>This data set contains output data from simulations with the model CARAIB for soybean as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above-ground biomass, planting day, maturity day, potential irrigation water withdrawal, actual growing season evapotranspiration . Simulations are based on 31-year simulations using the AgMERRA (Ruane et al. 2015) data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A0= 'none', A1='regain original growing season').</p>
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from JULES soybean simulations
This data set contains output data from simulations with the model JULES for soybean as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above-ground biomass, planting day, maturity day, anthesis day, potential irrigation water withdrawal, actual growing season evapotranspiration . Simulations are based on 31-year simulations using the WFDEI (Weedon et al. 2014) data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A0= 'none', A1='regain original growing season').
Fig. 4 in Biology and reproductive capacity of Spodoptera eridania (Cramer) (Lepidoptera, Noctuidae) in different soybean cultivars
Fig. 4. Number of eggs/female of Spodoptera eridania during the oviposition period.
Delivering metribuzin from biodegradable nanocarriers: Assessing herbicidal effects for soybean plant protection and weed control
<p>The data presents the indicators of soybean and soil health after metribuzin biodegradable nanocarriers and conventional metribuzin. Besides, the uptake and distribution of metribuzin in soil and weed plants (Amaranthus retroflexus) were associated with weed control evaluations.</p>
Figure 8 in Potential neuroprotective of trans-resveratrol a promising agent tempeh and soybean seed coats-derived against beta-amyloid neurotoxicity on primary culture of nerve cells induced by 2-methoxyethanol
Figure 8. Treatment Group with resveratrol tempeh + 2-ME after induced by Beta-Amyloid (10 x10).
Figure 5 in Potential neuroprotective of trans-resveratrol a promising agent tempeh and soybean seed coats-derived against beta-amyloid neurotoxicity on primary culture of nerve cells induced by 2-methoxyethanol
Figure 5. Treatment group: 2- ME (10 x10).
Figure 9. Treatment Group with 2 in Potential neuroprotective of trans-resveratrol a promising agent tempeh and soybean seed coats-derived against beta-amyloid neurotoxicity on primary culture of nerve cells induced by 2-methoxyethanol
Figure 9. Treatment Group with 2-ME after induced by Beta-Amyloid (10 x10).
Figure 2 in Potential neuroprotective of trans-resveratrol a promising agent tempeh and soybean seed coats-derived against beta-amyloid neurotoxicity on primary culture of nerve cells induced by 2-methoxyethanol
Figure 2. Treatment group: 2- ME + Resveratrol Standard (10 x10).
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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.