Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
101
datasets available to search
ShareScore release 0.9.0
Dataset results
101 results for “cover crops”
Cover crop mixtures enhance multiple ecosystem functions: A global meta-analysis
Open the record for dataset details and reuse information.
Reconciling plant and microbial ecological strategies to elucidate cover crop effects on soil carbon and nitrogen cycling
Open the record for dataset details and reuse information.
Forest cover and fruit crop size differentially influence frugivory of select rainforest tree species in Western Ghats, India (Part II)
Open the record for dataset details and reuse information.
Data from: Cover crop species alter tallgrass prairie community assembly
Open the record for dataset details and reuse information.
Data from: Impacts of rotation, tillage, cover cropping, and drainage on soil health in soybean-based cropping systems: Evidence from 4–50-year trials across the US
Open the record for dataset details and reuse information.
Data from: Cover crops dismantle keystone ant/aphid mutualisms to enhance insect pest suppression and weed biocontrol
Open the record for dataset details and reuse information.
Forest cover and proximity decrease herbivory and increase crop yield via enhanced natural enemies in soybean fields
Open the record for dataset details and reuse information.
Data from: Netted crop covers reduce honey bee foraging activity and colony strength in a mass flowering crop
The widespread use of protective covers in horticulture represents a novel landscape-level change, presenting challenges for crop pollination. Honey bees (Apis mellifera L) are pollinators of many crops, but their behaviour can be affected by conditions under covers. To determine how netting crop covers can affect honey bee foraging dynamics, colony health, and pollination services, we assessed the performance of 52 nucleus honey bee colonies in five covered and six uncovered kiwifruit orchards. Colony strength was estimated pre- and post- introduction, and the foraging of individual bees (including pollen-, nectar-, and naïve foragers) was monitored in a subset of the hives fitted with RFID readers. Simultaneously, we evaluated pollination effectiveness by measuring flower visitation rates and the number of seeds produced after single honey bee visits. Honey bee colonies under cover exhibited both an acute loss of foragers and changes in the behaviour of successful foragers. Under cover, bees were four times less likely to return after their first trip outside the hive. Consequently, the number of adult bees in hives declined at a faster rate in these orchards, with colonies losing on average 1,057 ± 274 of their bees in under two weeks. Bees that did forage under cover completed fewer trips provisioning their colony, failing to re-enter after a few short-duration trips. These effects are likely to have implications for colony health and productivity. We also found that bee density (bees/thousand flowers) and visitation rates to flowers were lower under cover, however we did not detect a resultant change in pollination. Our findings highlight the need for environment-specific management techniques for pollinators. Improving honey bee orientation under covers and increasing our understanding of the effects of covers on bee nutrition and brood rearing should be primary objectives for maintaining colonies and potentially improving pollination in these systems.
Cover crop and irrigation impacts on weeds and maize yield
<p>Winter cover crops (CC) may facilitate weed management by inhibiting weed seed germination and seedling emergence and suppressing weed growth within the cash crop. In southern New Mexico, with scarce winter precipitation and limited irrigation water, producing sufficient CC biomass for effective weed suppression while conserving water resources is challenging. This study assessed the water requirement to produce a CC with enough biomass for weed suppression benefits during cash crop growth at two locations in New Mexico. Three winter CC species, barley, Austrian winter pea and mustard, grown singly and in a three‐way mix, under three differential irrigation treatments (one, two or three irrigations after emergence) were evaluated for their weed‐suppressive potential. Maize was planted as a cash crop four weeks after winter CC termination. Number of irrigations had no effect on the CC and weed biomass production. All CCs had lower weed density prior to maize planting compared with fallow. Barley and the three‐way mix reduced weed density by 56–96% and 68–95%, respectively. All CC treatments had lower weed biomass at the end of critical period for weed control in maize compared with fallow. Weed biomass at maize harvest did not differ between treatments. The maize yield was consistently higher in conventionally managed, weed‐free subplots, than in unsprayed weedy subplots, suggesting that CCs did not suppress weeds throughout the maize growing season. Except for barley, CCs did not cause reductions in maize yield compared with fallow. Overall, the study suggested that with adequate winter precipitation, weed‐suppressive winter cover crop stands can be produced with just one irrigation at seeding and one supplemental irrigation, making them a viable option in water‐limited agroecosystems.</p>
Raw data for "Assessing Cover Crop and Intercrop Performance Along a Farm Management Gradient" (2022)
<p>This dataset accompanies the publication "Assessing Cover Crop and Intercrop Performance Along a Farm Management Gradient" by Stratton et al. in the journal Agriculture, Ecosystems, and Environment (2022). <a href="https://doi.org/10.1016/j.agee.2022.107925">https://doi.org/10.1016/j.agee.2022.107925</a></p> <p>METHODS:</p> <p>We conducted our experiment between May 2018 and December 2019 on 14 farms in the eastern coastal highlands region of Santa Catarina, Brazil. The mean altitude of sites was 467 m (+/- 161 m). Eastern Santa Catarina has a subtropical climatic pattern, with mean annual rainfall ranging from 1,500-1,700 mm (Wrege et al., 2012). While 2018 had typical weather patterns for the region, 2019 was a dry year, particularly during the spring months (Appendix B, Table B.1). All farms were located in the Colonial Serrana Catarinense soil microregion, one of 16 designated microregions in the state of Santa Catarina (EMBRAPA, 2004). Primary soil types in our study site are associations of dystric Cambisols and haplic Acrisols (typic Dystrocryepts and typic Paleudults in the USDA Soil Taxonomy), which tend to be moderately to highly acidic, with limited soil nutrient availability and moisture retention (EMBRAPA, 2004; IUSS Working Group WRB, 2015; USDA, 2010). To support crop production, farmers in the region typically apply lime (calcium and magnesium carbonate) to agricultural fields to increase soil pH from <5.5 to 6 (Comissão de Química e Fertilidade do Solo - RS/SC, 2016). Exact farm locations within the region are not given and farmer identities have been anonymized.</p> <p><em>Experimental design</em></p> <p>The fully factorial experiment had six treatments (Figure 2): (1) cover crop + pea-cucumber intercrop, (2) cover crop + pea monocrop, (3) cover crop + cucumber monocrop, (4) fallow + pea-cucumber intercrop, (5) fallow + pea monocrop, and (6) fallow + cucumber monocrop. Due to the timing of farm recruitment, only conventional and transitioning farms participated in the first year of cover cropping (2018); agroecological farms were added to the study during the vegetable intercropping period of 2018 and had their first round of cover cropping in 2019. The cover crop mixture treatment was designed to emulate traditional practices in the region, as well as to include functionally complementary legume and grass species: common vetch (<em>Vicia sativa </em>L.) and black oat (<em>Avena strigosa </em>Schreb). We also selected vegetables with distinct ecological functional traits, such that intercropping represented an increase in functional diversity relative to mono-cropped vegetables. Snow peas are N-fixing legumes with a vining, upright structure and a deep root system, whereas cucumbers are low-lying, non-legume cucurbits that provide groundcover and have a relatively shallow, extensive root system.</p> <p> </p> <p>Cover crop treatments consisted of two adjacent 50 m2 plots in each field, one of which was planted with the cover crop mixture; the other served as a weedy fallow control. In 2018, the cover crop mixture seeding rate was 72 kg/ha black oat and 36 kg/ha common vetch. Due to poor vetch performance in mixtures at this rate, we increased the vetch seeding rate to 60 kg/ha in 2019, maintaining the black oat rate from 2018. Cover crop seeds were inoculated with the Brazilian strain <em>Rhizobium etli </em>(SEMIA 384; source: FEPAGRO) at 4 g/kg vetch seed prior to planting. Cover crops were grown until peak flowering, and then cover crops (and weeds in the fallow) were incorporated into the soil by rototiller (<em>n</em> = 7 farms) or by hand hoeing (<em>n</em> = 7 farms), based on farms’ available machinery, between September 5-10 in 2018 and September 10-18 in 2019 (approximately one week following cover crop sampling on each farm).</p> <p> </p> <p>Vegetables were planted two weeks following cover crop and weed biomass incorporation within a period of 7-10 days across sites. Harvest dates were spaced such that crops were growing for approximately the same period across farms. The 50 m2 plots were each divided into three intercrop treatments with a ~1 m2 pathway between each treatment, for a total of 6 treatments randomly assigned to plots per 100 m2. We planted a climbing variety of snow peas (<em>Pisum sativum</em> subsp. <em>sativum</em> var. <em>macrocarpum</em>,<strong> </strong>“<em>Torta de flor roxa”</em>) and pickling cucumber (<em>Cucumis sativa </em>L. var. <em>Pepino HT </em>05) in intercrops and in their respective monocrops, using a replacement design (i.e., equivalent crop densities in all treatments). Snow pea seeds were inoculated with <em>Rhizobium leguminosarum</em> var. <em>viceae</em> (SEMIA 3007/BR 619, source: UFSC ENR/CCA) at a rate of 4 g/kg directly prior to planting. There were five rows of crops per treatment, with only the three middle rows harvested to limit edge effects. In-row spacing was 60 cm for cucumber and 20 cm for peas, with 60 cm between rows in both intercrops and monocrops. Cucumbers were grown as starts for 2.5 weeks before planting, and peas were planted from seed on the same planting date as cucumber starts.</p> <p> </p> <p>In the summer between January and May 2019 all fields were planted to a sunflower (<em>Helianthus annuus</em> L.) crop, which was incorporated into the soil during flowering approximately two weeks prior to cover crop planting in 2019. Because we sought to understand the effects of crop diversification given existing water and nutrient limitations on working farms, the experiment was entirely rainfed and legume N fixation was the sole external N source.</p> <p><em>Soil sampling and analysis</em></p> <p>Prior to the first cover cropping period, we collected a composite sample of 15-20 soil cores (2.5 cm diameter, 20 cm depth) on both the cover crop and fallow sides of each experimental field (<em>n</em> = 28) for analysis of baseline conditions (see Appendix B for full details). Briefly, soil was analyzed for pH, macro- and micronutrients, and soil organic matter (SOM) by the Santa Catarina State Agricultural Agency (EPAGRI) in Ituporanga, Santa Catarina, Brazil, using standard protocols (Comissão de Química e Fertilidade do Solo - RS/SC, 2016). pH was measured with a glass electrode both with and without Sikora’s buffer, and buffered pH is used throughout this paper (Tecnal TEC-11 MP). Soil organic C and total soil N to 20 cm were determined by dry combustion on a Leco TruMac CN Analyzer (Leco Corporation, St. Joseph, Michigan, USA). We measured soil texture (% clay, sand, and silt) using a total dispersion method with sodium hexametaphosphate (Empresa Brasileira de Pesquisa Agropecuaria (EMBRAPA), 1997). Bulk density was estimated from the mass of 10 fresh soil cores per treatment, with subsequent accounting for soil moisture.</p> <p> </p> <p>We measured C mineralization as a baseline indicator of soil microbial activity and biological soil fertility at the start of the experiment, and N mineralization as a response variable following the second year of cover crop treatments. Specifically, using the baseline soil sample, we conducted a short-term (24-hour) C mineralization assay to determine potentially mineralizable C (PMC), which measures the flux of CO2 following re-wetting of previously air-dried, sieved soil using a Li-Cor (Franzluebbers et al., 2000; Hurisso et al., 2016). To measure potentially mineralizable N (PMN), we conducted a two-week aerobic incubation using fresh soil collected at vegetable crop planting in the second year of the experiment (spring 2019), two weeks after cover crop and weed biomass incorporation (Drinkwater et al., 1996; Appendix B.2). PMN was calculated as the difference between extractable soil inorganic N (NH4+ and NO3-) at the start and end of the incubation. We used pre-incubation extractable inorganic N concentration (mg/kg) as a measure of soil inorganic N availability at vegetable crop planting.</p> <p> <em>Cover crop sampling and analysis</em></p> <p>Cover crop biomass sampling took place from August 28-September 2 in 2018 and September 4-10 in 2019. During peak flowering of both common vetch and black oat, we destructively harvested the aboveground biomass of cover crop mixtures and weedy fallows from two 0.5 x 0.5 m quadrats of each treatment per field. We took care to avoid treatment edges, cut plant material to the soil surface, and separated harvested plant material by species, grouping all weeds together. Aboveground biomass was dried in a forced-air oven at 60 °C for 48 hours. Following grinding in a Wiley mill to 2 mm, % N and C content was determined by dry combustion on an elemental analyzer (Leco, as above). Community-weighted means were calculated for total aboveground biomass C and N in cover crop species and weeds, to determine the overall C and N inputs to soil following incorporation of biomass on each farm. We measured biological N2 fixation in inoculated common vetch from the cover crop phase of the experiment in 2018 and 2019. Vetch N fixation was estimated using the 15N natural abundance method (Shearer and Kohl, 1986), which compares stable N isotope ratios in the legume and reference species (oat monocultures) (Appendix C).</p> <p> <em>Vegetable crop sampling and analysis</em></p> <p>To capture the full production period of both cucumber and pea crops, yield was measured in two harvests, which were approximately 14 days apart on each farm. Harvest dates ran from November 16-December 6 in 2018 and November 20-December 4 in 2019. We measured yield by weighing all harvestable fruit from three designated, representative row sections (6 plants on average per row) per crop type per treatment. Rows were sampled from the center of each treatment to reduce edge effects. We calculated yield as total crop production (g) per plant harvested in each row. Mean yield for each crop type was calculated as the average of the three harvested rows per treatment on a per-plant basis and was then aggregated to the plot and hectare level based on experimental planting densities. Total N harvested, or “N yield”, was calculated for all treatments by multiplying the % N in each vegetable crop by its yield (kg/ha) after accounting for crop water content. Using plot-level yield data, we subsequently calculated the relative yield total (Land Equivalent Ratio, LER) for intercrop treatments by farm using the standard equation (Vandermeer, 1989) (Table 1). As a relative measure of total crop production per area, when mean LER > 1, intercrops were considered to have “overyielded” compared to their component monocrops. We calculated the LER for N yield (LERN in kg N/ha) using the same formula.</p> <p> </p> <p>At the second vegetable harvest, we destructively sampled whole aboveground crop biomass, including residues and remaining fruits, from the designated experimental rows. Following the harvest, a minimum of six representative cucumbers per treatment (from different plants) per farm were washed in deionized water, air-dried, sliced, and the middle sections were combined into a homogenized, composite sample of ~100 g and then dried for one week at 60 ºC. All peas from each treatment’s subplot were washed in deionized water, air-dried, de-stemmed, chopped, and each homogenized sample (35-60 g fresh material) was subsequently dried at 60 ºC in a forced-air oven for 48 h to one week, until fully desiccated. Dried vegetable biomass residues were ground using a Wiley mill; vegetable crop samples were ground in a coffee grinder; and all vegetable samples were analyzed for % C and N on a LECO elemental analyzer.</p> <p><strong>See</strong><strong> supplemental material from Stratton et al. 2022 for further detailed information on methods.</strong></p>
Decomposing cover crops modify root-associated microbiome composition and disease tolerance of cash crop seedlings
<p>The assembly of root-associated microbes during the seedling stage has strong impact on subsequent performance of crops. Major factors influencing this assembly are crop species identity and composition of potential root-colonizing microbes in the bulk soil. The latter can be modified by soil management, such as organic amendments. The incorporation of residues of cover crops before the start of the growing season of cash crops presents an interesting option for steering of root-associated seedling microbiomes as there is a wide range of cover crops species with different properties available for farmers.</p> <p>In a greenhouse study, we examined the effect of soil amendments with milled shoot and root materials of seven cover crop species (niger seed, phacelia, rapeseed, radish, vetch, black oat and buckwheat) on the soil nitrogen and biomass of seedlings of four cash crop species (asparagus, carrot, onion and sugar beet) and their root-associated bacteria and fungi. Field-grown cover crops material used for the study was collected at two time points (before and after winter) which had strong impact on plant elemental composition. Since the soil used for the study was a mixture of sandy arable soils with a history of soil-borne fungal diseases (Fusarium and Rhizoctonia), we also examined whether decomposing cover crop residues had an influence on the severity of damping-off diseases.</p> <p>Within the context of a strong selection of root-associated microbes by cash crop species, we found significant modifying effects by cover crop materials. High-quality residues (with low C/N ratio) caused profound shifts within root-associated Proteobacteria and increases in relative abundance of certain microbial groups such as Bacillaceae and Mortierellomycetes. These changes coincided with differences in establishment and survival of cash crop seedlings. This indicates that fine-tuning of cover crops amendments for different cash crops is required to realize enhanced functioning of root microbiomes.</p>
Dataset about the adoption of winter cover crops at the municipality level for mainland France
<p>Dataset about winter soil cover before spring crops for mainland France</p>
Leveraging functional traits of cover crops to coordinate crop productivity and soil health
<p><span>1. Plants act as ecosystem engineers playing fundamental roles in steering their surroundings, including soil abiotic and biotic conditions, soil organisms, and the complex soil food web they comprise. Trait-based approaches have been considered a 'Holy Grail' in linking plants to ecosystem functions, but the mechanistic relationship between plant traits and the soil food web as an indicator of soil health remains poorly understood.</span></p> <p><span>2. We examined this relationship for 16 cover crop species differing in leaf and root traits in a field experiment where corn (Zea mays) was the main crop. Based on functional traits, the cover crop species were categorized into two ecological strategies at either end of the resource acquisitive-conservative spectrum. We investigated the effects of cover crop ecological strategies on corn productivity and soil health. We used soil nematodes as an indicator of soil health and analyzed soil physico-chemical properties and microbial community activities.</span></p> <p><span>3. We found that acquisitive cover crops supported higher soil resource availability, bacterial energy channels in the soil food web, and greater corn productivity than conservative cover crops. In contrast, conservative cover crops supported higher abundances of fungivores and omni-carnivores than acquisitive cover crop, which reflected a more structured and complex soil food web, implying a healthier soil ecosystem. Conservative cover crops also increased corn productivity compared to the no cover crop control treatment.</span></p> <p><span>4. Synthesis and applications. Collectively, this work shows that cover crops with distinct ecological strategies had their own strengths to enhance ecosystem functions: acquisitive and conservative cover crops improved crop productivity and soil health, respectively. These results indicates that farmers and policy makers can make trait-based choices in selecting cover crop best serving the local needs. This points to a win-win solution for food production and ecosystem sustainability.</span></p>
DRAM raw annotations for "Cover Crop Root Exudates Impact Soil Microbiome Functional Trajectories in Agricultural Soils" Seitz et al 2024
<p>Additional File 5: <span>Raw DRAM MAG annotations. </span></p>
Cover crops effect on global croplands modelled by LPJ-GUESS
<p>This file contains the input and output data for cover crop simulations on global scale by LPJ-GUESS. The site-level observations collected from the existing literature for model evaluation are also included. More details can be found in our Earth's Future (EF) paper: <a href="https://doi.org/10.1029/2022EF003142">https://doi.org/10.1029/2022EF003142</a></p>
Data for: Cover crop functional types differentially alter the content and composition of soil organic carbon in particulate and mineral-associated fractions
<p>Cover crops (CCs) can increase soil organic carbon (SOC) sequestration by providing additional OC residues, recruiting beneficial soil microbiota, and improving soil aggregation and structure. The various CC species that belong to distinct plant functional types (PFTs) may differentially impact SOC formation and stabilization. Biogeochemical theory suggests that selection of PFTs with distinct litter quality (C:N ratio) should influence the pathways and magnitude of SOC sequestration. Yet, we lack knowledge on the effect of CCs from different PFTs on the quantity and composition of physiochemical pools of SOC. We sampled soils under monocultures of three CC PFTs (legume [crimson clover]; grass [triticale]; and brassica [canola]) and a mixture of these three species, from a long-term CC experiment in Pennsylvania, USA. We measured C content in bulk soil and C content and composition in contrasting physical fractions: particulate organic matter, POM; and mineral-associated organic matter, MAOM. The bulk SOC content was higher in all CC treatments compared to the fallow. Compared to the legume, monocultures of grass and brassica with lower litter quality (wider C:N) had higher proportion of plant-derived C in POM, indicating selective preservation of complex structural plant compounds. In contrast, soils under legumes had greater accumulation of microbial-derived C in MAOM. Our results for the first time, revealed that the mixture contributed to a higher concentration of plant-derived compounds in POM relative to the legume, and a greater accumulation of microbial-derived C in MAOM compared to monocultures of grass and brassica. Mixtures with all three PFTs can thus increase the short- and long-term SOC persistence balancing the contrasting effects on the chemistries in POM and MAOM imposed by monoculture CC PFTs. Thus, despite different cumulative C inputs in CC treatments from different PFTs, the total SOC stocks did not vary between CC PFTs, rather PFTs impacted whether C accumulated in POM or MAOM fractions. This highlights that CCs of different PFTs may shift the dominant SOC formation pathways (POM vs. MAOM), subsequently impacting short- and long-term SOC stabilization and stocks. Our work provides a strong applied field test of biogeochemical theory linking litter quality to pathways of C accrual in soil.</p>
Cover crop and nitrogen rate management practices influence corn (Zea mays) NDVI and nitrogen content
<p>Cover crops are rarely adopted in the northern Corn Belt because of short growing periods but could provide benefits when grown between wheat (<em>Triticum aestivum</em> L<em>.</em>) and corn (<em>Zea mays</em> L<em>.</em>). We evaluated corn NDVI (normalized difference vegetation index) and leaf N (at six leaf, ear leaf, 75% silk, and physiological maturity), over three growing seasons in response to factorial treatments of cover crop (annual ryegrass [<em>Lolium perenne</em> L. ssp. <em>multiflorum </em>(Lam.) Husnot], radish [Raphanus sativus L.], and no-cover control) and N rate (0X, 0.25X, 0.5X, and 1X) relative to the recommended rate based on pre-plant soil tests (157–190 kg N ha<sup>–1</sup>). Grain N was also measured in the last study year (2016) to evaluate if leaf N indicated grain N. Radish cover crop increased corn NDVI relative to the no-cover control, but annual ryegrass decreased NDVI relative to no-cover control. This response to cover crop treatment suggests that radish cover crop may improve corn nutritional status. Corn receiving 1X N rate had the slowest decrease in leaf N over the growing season, but 2016 data revealed that grain from all treatments receiving some level of N had similar N content. Root biomass was also highest in the 0.5X N rate treatment and could explain the previously reported result that 0.5X N rate results in highest corn yield. Taken together, these results suggest that half the recommended N fertilizer can be used with little effect on nutritional status of corn following spring wheat in the northern Corn belt.</p>
Towards efficient N cycling in intensive maize: role of cover crops and application methods of digestate liquid fraction
<p class="MsoNormal"><span>Digestate, a by-product of biogas production, is widely recognized as a promising renewable nitrogen (N) source with high potential to replace synthetic fertilizers. Yet, inefficient digestate use can lead to pollutant N losses as ammonia (NH<sub>3</sub>) volatilization, nitrous oxide (N<sub>2</sub>O) emissions and nitrate (NO<sub>3</sub><sup>-</sup>) leaching. Cover crops may reduce some of these N losses and recycle the N back into the soil after incorporation, but the net effect on the N balance depends on the cover crop species. In a one-year field study, we tested the effects of two application methods (i.e., surface broadcasting, BDC; and shallow injection, INJ) of the liquid fraction of separated co-digested cattle slurry (DLF), combined with different winter cover crop options (CCs, i.e., rye, white mustard or bare fallow), as starter fertilizer for maize. Later in the season, side-dressing with urea was required to fulfill maize N-requirements. We tested treatment effects on yield, N-uptake, N-use efficiency parameters, and N-losses in the form of N<sub>2</sub>O emissions and NO<sub>3</sub><sup>-</sup> leaching. Cover crop development and biomass production were strongly affected by their contrasting frost tolerance, with spring-regrowth for rye, while mustard was winter killed. After the cover crops, injection of DLF increased N<sub>2</sub>O emissions significantly compared with BDC (emission factor of 2.69 <em>vs.</em> 1.66%). Nitrous oxide emissions accounted for a small part (11-13%) of the overall yield-scaled N losses (0.46 - 0.97 kg N Mg grain<sup>-1</sup>). The adoption of CCs reduced fall NO<sub>3</sub><sup>-</sup> leaching, <span>being 51% and 64% lower for mustard and rye than under bare soil. In addition, rye reduced </span>NO<sub>3</sub><sup>-</sup> leaching during spring and summer after termination by promoting N immobilization, thus leading to -57% lower annual leaching losses compared to mustard.<span> Our study confirms the potential of CCs to reduce </span>NO<sub>3</sub><sup>-</sup><span> leaching, but it also highlights that their residue can increase N losses once terminated and that they may cause yield reductions. DLF application method modified N-loss pathways, but not the cumulative yield-scaled N losses. Overall, these insights contribute to inform an evidence-based design of cropping systems in which nutrients are recycled more efficiently.</span></span></p>
Decomposing cover crops modify root-associated microbiome composition and disease tolerance of cash crop seedlings
Open the record for dataset details and reuse information.
Towards efficient N cycling in intensive maize: role of cover crops and application methods of digestate liquid fraction
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
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.