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44 results for “organic agriculture”
Italy Southern Regions organic waste stream, Agricultural, Forest and Municipal Solid Waste, years 2018 and 2030
<p>Southern Italy regions agricultural residues (straw, pruning) quantification, years 2018 and 2030</p> <p>Souther Italy regions above ground annual forest increment, 2018 and 2030 technical and environmental contraints</p> <p>Souther Italy regions Municipal Solid Waste separation 2018, and 2030 minimum target EU waste Directive 2018/851</p>
Soil grid data for 3 agricultural fields in Italy (Soil Moisture, soil organic carbon)
<p><span>Soil data collected in an agricultural area with annual crops in Italy (west-central Lombardia Po Valley, province of Pavia). The data refers to soil properties of 320 soil samples for Soil Moisture and 120 for SOC, collected in the topsoil (around 5-10 cm), considering a regular sampling grid, within three agricultural field with different crops (spring-summer cycle) and soils type, Rice-Loamy, Sorghum-Sandy and, Maize-Clay, in a period (before the seeding of the crops), when the soil was bare, in the framework of the EJP Steropes project.</span></p> <p><span>The aim of the collected dataset was to be able to analyse the influence of soil moisture in SOC (WP2 of the STEROPES project) prediction models from remote sensing.</span></p> <p><span>Data in the form of shape file (one shapefile for each agricultural field, for oth Soil Moisture and SOC), and pictures of the soil surface in .jpg format. </span></p>
Data to support the publication "Impact of agricultural management on soil aggregates and associated organic carbon fractions: Analysis of long-term experiments in Europe"
<p><strong>Raw data:</strong> Experimental plot ids and information, mass distribution of all aggregate fractions after wet sieving, Sand content of each fraction to conduct the sand correction, mass distribution of all fractions after isolating the micro-aggregates held within the macroaggregates, yields per treatment, carbon content per fraction (raw data)</p> <p><strong>All data per plot: </strong>SOC content, MAOM and POM content of each fraction presented in the fractionation scheme included in the manuscript, together with the mass of the relative fractions. </p> <p> </p>
Data and Code from: On-farm land management strategies and production challenges in United States Organic Agricultural Systems.
<p>This repository contains data and code used in:</p> <p>Isaac Mpanga, Russel Trondstad, Jessica Guo, David LeBauer, and John Omololu, 2021. On-farm land management strategies and production challenges in United States Organic Agricultural Systems. Current Research in Environmental Sustainability.</p> <p>It provides USDA Surveys of Agricultural Production from 2008-2019 to investigate state and national trends by state in organic farm area, number, and sales, as well to evaluate national trends in on-farm land-use practices and challenges facing US organic production.</p> <p>It also includes code used to transform, visualize, and analyze the data, and derived data products - notably organic farm area and sales with values imputed to correct for redacted state level measures.</p>
Organic and inorganic carbon concentration and stable isotope composition in poorly drained agricultural soils in Iowa, USA
We measured soil organic carbon (SOC) and inorganic carbon (carbonate) in samples collected along topographic gradients in agricultural fields in Iowa, USA, in 2018. We also measured stable isotopes of SOC, soil nitrogen, and carbon in respired CO2 to provide additional context for organic matter dynamics. Additional physical, chemical, and hydrologic variables were measured on these samples and in the field sites to understand mechanisms underlying patterns in soil organic and inorganic carbon.
Data for: Spillover effects of organic agriculture on pesticide use on nearby fields
<p><span>The environmental impacts of organic agriculture are only partially understood and </span><span>whether such practices have spillover effects </span><span>on pests or pest control activity </span><span>on nearby fields remains unknown</span><span>. Using </span><span>roughly 13,000 field observations per year from 2013-2019 in Kern County, CA , </span><span>we estimate that organic crop producers benefit from surrounding organic fields, decreasing overall pesticide use and pesticides targeting insect pests. </span><span><span>Conventional fields, in contrast, tend to increase pesticide use as the area of surrounding organic production increases.</span></span></p>
The role of nitrogen and iron biogeochemical cycles in the production and export of dissolved organic matter in agricultural headwater catchments
<p>Data on soil solutions collected in the riparian area at 15 cm depth in an agricultural catchment in Brittany (France) during one hydrological cycle. Zero-tension lysimeters were collected at a fortnightly frequency from October 2022 to June 2023. Measurements inlcude dissolved organic matter concentration and composition (3D flurorescence), nitrates, iron, and phosphorus.</p> <p>Data are published in Lambert et al., 2014, The role of nitrogen and iron biogeochemical cycles in the production and export of dissolved organic matter in agricultural headwater catchments, doi.org/10.5194/egusphere-2024-1212 (preprint).</p>
Agriculture and food system scenarios with particular focus on organic and agro-ecological farming practices in the EU
<p>This is a comprehensive dataset of the agriculture and food system scenarios co-developed with stakeholders with the agricultural land use model BioBaM-GHG 2.0 and presented in Deliverable 4.2 of the H2020 project UNISECO. It includes sub-national (NUTS1/2-level) data on agricultural production and consumption, land use, greenhouse gas emissions from livestock and agricultural activities, etc. for the base year 2012 and the scenario years 2030 and 2050. The scenarios include a Business as usual case and four scenarios with focus on organic and agro-ecological farming practices in the EU, based on different storylines. Further information is available from the above-mentioned deliverable.</p> <p>A detailed model description is provided in the paper "Exploring the option space for land system futures at regional to global scales: The diagnostic agro-food, land use and greenhouse gas emission model BioBaM-GHG 2.0", in which these scenarios are also presented as an exemplary application of the model BioBaM-GHG 2.0.</p> <p>This work was funded by the ERA-NET SusAn project 101243 AnimalFuture, as well as by the European Union’s Horizon 2020 research and innovation programme and its funding of the H2020 UNISECO project under grant agreement N°773901.</p>
Potassium fertilization effects on cereal yield and soil organic carbon in agricultural ecosystems at the global scale
<p>This dataset includes the raw data of a global meta-analysis study on the responses of cereal yield and soil organic carbon to potassium fertilization in agricultural ecosystems.</p>
"I was the class teacher at that time. It was a class trip, usually organized near the end of the schoolterm in summer. The pupils went there by bike to have a barbecue at the sandy banks of the river Rhine near Dusseldorf. The landscape around is mostly dominated by agriculture and glasshouse cultures. You find a mixture of former villages nowadays completely suburbanized. The population finds jobs in the nearby urban centers like Dusseldorf, Neuss and other big cities. The reason why Irecorded the scene is simply because Iam interested in collecting sounds in general by doing recordings in different surroundings like nature, cities and everything between. My memories about the event are that it was a relaxing and funny atmosphere, which is not always the case while teaching in a classroom" [Reinhard/reinsamba]15 in Collecting Sounds. Online Sharing of Field Recordings as Cultural Practice
"I was the class teacher at that time. It was a class trip, usually organized near the end of the schoolterm in summer. The pupils went there by bike to have a barbecue at the sandy banks of the river Rhine near Dusseldorf. The landscape around is mostly dominated by agriculture and glasshouse cultures. You find a mixture of former villages nowadays completely suburbanized. The population finds jobs in the nearby urban centers like Dusseldorf, Neuss and other big cities. The reason why Irecorded the scene is simply because Iam interested in collecting sounds in general by doing recordings in different surroundings like nature, cities and everything between. My memories about the event are that it was a relaxing and funny atmosphere, which is not always the case while teaching in a classroom" [Reinhard/reinsamba]15
Data for: Spillover effects of organic agriculture on pesticide use on nearby fields
Open the record for dataset details and reuse information.
Organic farming and seminatural habitats for multifunctional agriculture: a case study in hedgerow landscapes of Brittany
Open the record for dataset details and reuse information.
Data from: Leaching losses of dissolved organic carbon and nitrogen from agricultural soils in the upper US Midwest
<p>Leaching losses of dissolved organic carbon (DOC) and nitrogen (DON) from agricultural systems are important to water quality and carbon and nutrient balances but are rarely reported; the few available studies suggest linkages to litter production (DOC) and nitrogen fertilization (DON). In this study we examine the leaching of DOC, DON, NO<sub>3</sub><sup>-</sup>, and NH<sub>4</sub><sup>+</sup> from no-till corn (maize) and perennial bioenergy crops (switchgrass, miscanthus, native grasses, restored prairie, and poplar) grown between 2009 and 2016 in a replicated field experiment in the upper Midwest U.S. Leaching was estimated from concentrations in soil water and modeled drainage (percolation) rates. DOC leaching rates (kg ha<sup>-1 </sup>yr<sup>-1</sup>) and volume-weighted mean concentrations (mg L<sup>-1</sup>) among cropping systems averaged 15.4 and 4.6, respectively; N fertilization had no effect and poplar lost the most DOC (21.8 and 6.9, respectively). DON leaching rates (kg ha<sup>-1 </sup>yr<sup>-1</sup>) and volume-weighted mean concentrations (mg L<sup>-1</sup>) under corn (the most heavily N-fertilized crop) averaged 4.5 and 1.0, respectively, which was higher than perennial grasses (mean: 1.5 and 0.5, respectively) and poplar (1.6 and 0.5, respectively). NO<sub>3</sub><sup>-</sup> comprised the majority of total N leaching in all systems (59-92%). Average NO<sub>3</sub><sup>-</sup> leaching (kg N ha<sup>-1</sup> yr<sup>-1</sup>) under corn (35.3) was higher than perennial grasses (5.9) and poplar (7.2). NH<sub>4</sub><sup>+</sup> concentrations in soil water from all cropping systems were relatively low (<0.07 mg N L<sup>-1</sup>). Perennial crops leached more NO<sub>3</sub><sup>-</sup> in the first few years after planting, and markedly less after. Among the fertilized crops, the leached N represented 14-38% of the added N over the study period; poplar lost the greatest proportion (38%) and corn was intermediate (23%). Requiring only one third or less of the N fertilization compared to corn, perennial bioenergy crops can substantially reduce N leaching and consequent movement into aquifers and surface waters.</p>
Soil grid data for 4 agricultural fields in PT (ECe; soil organic carbon, pH)
<p>Soil data collected in an agricultural area with annual crops in Portugal (Lezíria Grande). The data refers to soil properties of 63 soil samples collected at a depth of 0-20 cm, considering a regular sampling grid, in four fields with varying soil salinity (field areas between 2 and 34 ha). The samples were collected at a period when the soil was bare, following the harvest of the annual crops, and pictures of the soil surface were taken for eventual correction of corresponding remote sensing imaging. The data includes: soil organic carbon (SOC) (Walkley-Black method), soil water content, electric conductivity of the saturated soil paste (ECe), EC1:5, and pH1:5. </p><p>The data may be representative of the soil conditions of the area, which is a highly productive agricultural low land, prone to the development of soil salinity as a result of the rise of saline groundwater and/or irrigation. The data can be used to establish relations between soil salinity (ECe) and other soil properties as well as build prediction models of the soil properties from remote sensing namely, for developing models for SOC prediction under the STEROPES project (WP5 (WP5-T3) and WP2 (WP2-T3)).The aim of the collected dataset was to be able to analyze the influence of soil salinity in SOC prediction from remote sensing.</p><p>Data in the form of MS Excel files (xlsx), pictures of the soil surface in jpg. format. </p>
Soil grid data for agricultural fields in Spain for STEROPES (EJP Soil) project (ECe, texture, soil organic carbon, pH)
<p><span>Soil data collected in an agricultural area with vegetable crops in Spain (Campo de Cartagena). The data refers to soil properties of 141 soil samples collected at a depth of 0-10 cm, considering a regular sampling grid, in different commercial fields with varying soil salinity. The samples were collected at a period when the soil was bare, during two consecutive summers, following the harvest of the annual crops, and pictures of the soil surface were taken for eventual correction of corresponding remote sensing imaging. The data includes: soil organic carbon (SOC) (Walkley-Black method), soil water content, electric conductivity of the saturated soil paste (ECe), EC1:5, soil texture, stone content and pH1:2.5. </span></p> <p><span> </span></p> <p><span>The data may be representative of the soil conditions of the area, which is an intensive productive agricultural low land, potentially prone to the development of soil salinity as a result of the rise of saline groundwater and/or irrigation. The data can be used to establish relations between soil salinity (ECe) and other soil properties as well as build prediction models of the soil properties from remote sensing namely, for developing models for SOC prediction under the STEROPES project (WP3, WP5 and WP6).The aim of the collected dataset was to be able to analyze the influence of soil salinity in SOC prediction from remote sensing.</span></p> <p><span> </span></p> <p><span>Data in the form of MS Excel file (xlsx).</span></p> <p><span> </span></p> <p><span> </span></p>
Data from: A trait‒environment relationship approach to participatory plant breeding for organic agriculture
<p>The extent of intraspecific variation in trait‒environment relationships is an open question with limited empirical support in crops. In organic agriculture, with high environmental heterogeneity, this knowledge could guide breeding programs to optimize crop attributes. We propose a three-dimensional framework involving crop performance, crop traits, and environmental axes to uncover the multidimensionality of trait‒environment relationships within a crop. </p> <p>We modeled instantaneous photosynthesis (<em>A</em><sub>sat</sub>) and water-use efficiency (WUE) as functions of four phenotypic traits, three soil variables, five carrot (<em>D. carota</em>) varieties, and their interactions in a national participatory plant breeding program involving a suite of farms across Canada. We used these interactions to describe the resulting 12 trait‒environment relationships across varieties. </p> <p>We found one significant trait‒environment relationship for <em>A</em><sub>sat</sub> (taproot tissue density‒soil phosphorus), which was consistent across varieties. For WUE, we found that three relationships (petiole diameter‒soil nitrogen, petiole diameter‒soil phosphorus, and leaf area‒soil phosphorus) varied significantly across varieties. As a result, WUE was maximized by different combinations of trait values and soil conditions depending on the variety. </p> <p>Our three-dimensional framework supports the identification of functional traits behind the differential responses of crop varieties to environmental variation and thus guides breeding programs to optimize crop attributes from an eco-evolutionary perspective. </p>
Soil microbial diversity and community composition during conversion from conventional to organic agriculture
<p>It is generally assumed that the dependence of conventional agriculture on artificial fertilizers and pesticides strongly impacts the environment, while organic agriculture relying more on microbial functioning may mitigate these impacts. However, it is not well known how microbial diversity and community composition change in conventionally managed farmers' fields that are converted to organic management. Here, we sequenced bacterial and fungal communities of 34 organic fields on sand and marine clay soils in a time series (chronosequence) covering 25 years of conversion. Nearby conventional fields were used as references. We found that community composition of bacteria and fungi differed between organic and conventionally managed fields. In the organic fields, fungal diversity increased with time since conversion. However, this effect disappeared when the conventional paired fields were included. There was a relationship between pH and soil organic matter content and the diversity and community composition of bacteria and fungi. In marine clay soils, when time since organic management increased, fungal communities in organic fields became more dissimilar to those in conventional fields. We conclude that conversion to organic management in these Dutch farmers' fields did not increase microbial community diversity. Instead, we observed that in organic fields in marine clay when time since conversion increased soil fungal community composition became progressively dissimilar from that in conventional fields. Our results also showed that the paired sampling approach of organic and conventional fields was essential in order to control for environmental variation that was otherwise unaccounted for.</p>
Effects of land clearing for agriculture on soil organic carbon stocks in drylands: A meta-analysis
<p><span>To improve our understanding of clearing natural ecosystems for cropland on soil organic carbon stocks in drylands, we searched for related peer-reviewed research papers published from 1980 to 2022 on the Web of Science (<a href="https://www.webofscience.com">https://www.webofscience.com</a>) and the Scopus Database (<a href="https://www.scopus.com">https://www.scopus.com</a>) (accessed on 30th April 2022). Then, we screened papers for </span><span>integrity, relevance, and scientific merit under the following criteria: (1) We made sure all studies were independent and based on field-measured data; (2) Each study had to report paired SOC stocks of cropland and adjacent natural ecosystems with the same or a similar suite of environmental factors; (3) Studies need to explicitly present results on SOC stocks or concentrations for certain depths and areas; (4) Studies have specified the types of natural ecosystems that were converted to cropland, which are used as criteria for defining CNEC types. Finally, we winnowed results to a total of 159 scientific journal articles, comprising 242 sites with 1379 paired soil layer observations from 601 paired soil profiles.</span></p>
Dataset - Biogas composition from agricultural sources and organic fraction of municipal solid waste
<p>Data in this file compiled by H. Madi, A. Calbry-Muzyka, F. Rüsch-Pfund, M. Gandiglio, and S. Biollaz as Supplementary Information for "Biogas composition from agricultural sources and organic fraction of municipal solid waste", 2021. Table format in this file adapted from D. Papadias et al. at Argonne National Labs, www.cse.anl.gov/FCs_on_biogas/Impurities%20-%20LFG.xls and www.cse.anl.gov/FCs_on_biogas/Impurities%20-%20WWTP.xls (see also doi.org/10.1016/j.energy.2012.06.031).</p>
Reducing pesticides without organic certification? Potentials and limits of an intermediate form of agricultural production
<p><span>A growing number of farmer cooperatives cultivate crops without chemical pesticides, but also without organic certification. How does this intermediate form of agriculture between conventional and organic production function? What are the outcomes of this production form on cropland biodiversity? How does this model contribute to the transition toward more sustainable forms of agriculture? We address these research questions using original data collected in the AgroBioDiv project from the farmers' cooperative "KraichgauKorn" based in the German State of Baden-Württemberg. This cooperative is a collection of conventional farmers, who refrain from pesticide use during cultivation periods for KraichgauKorn grains, with products being produced without pesticide inputs in the growing season. Our study finds higher levels of weed species biodiversity on KGK cereal fields compared to conventional fields, but lower than organic fields. In addition, more endangered wild species monitored by the State of Baden-Württemberg were found on KGK fields than on conventional fields, with organic fields exhibiting the highest presence of endangered flora. We conclude that such kinds of enterprises may indeed contribute substantially to a successful transformation toward sustainable agricultural systems. </span></p>
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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.