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64 results for “Farming system”
European consumers ́ preference and willingness to pay for food products labelled as obtained by a circular farming system -in relation to environmental attitudes and consumption behaviours
<p>Data was collected with questionnaire-based research carried out in Belgium, Croatia, Hungary, Italy, Poland, and Spain as part of a European project. The survey questions were designed to obtain the Willingness to pay using 2 different methodologies the discrete choice experiment and the open-end choice experiment. The survey also included questions about consumers environmental attitudes, and consumption behavior (purchase, use and recycling), to identify if them have influence on preferences towards more sustainable food products. The 3 analyzed food products were pork meat, milk and bread, all of them obtained through different agricultural production systems (circular, conventional, and organic agriculture). The sample was stratified in terms of gender and age to be representative to the average population in each country. Furthermore, respondents included in this study were those that are mainly, or in part responsible for the household food shopping. The questionnaire was translated to the languages of the countries involved in the data collection and pre-launched using a pilot sample of 50 consumers in each case study country. Finally, a total of 5,362 validated questionnaires were obtained. Data was collected online using the Qualtrics market research company, and Net panel market company for Hungary from June 2021 to January 2022.</p>
Dataset for the article "Barriers and Opportunities for Sustainable Farming Practices and Crop Diversification Strategies in Mediterranean Cereal-Based Systems"
<p>Datasets from the surveys applied for the article "Barriers and Opportunities for Sustainable Farming Practices and Crop Diversification Strategies in Mediterranean Cereal-Based Systems" <a href="https://doi.org/10.3389/fenvs.2022.861225">https://doi.org/10.3389/fenvs.2022.861225</a></p>
Farming Practices and Systems
<p>The Pesticides (use) database includes data on the use of major pesticide groups (Insecticides, Herbicides, Fungicides, Plant growth regulators and Rodenticides) and of relevant chemical families. Data report the quantities (in tonnes of active ingredients) of pesticides used in or sold to the agricultural sector for crops and seeds. Information on quantities applied to single crops is not available.</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>
Germination of crop species in response to whole-soil inoculants that originate from conventional vs organic farming systems
<p>Dataset of manuscript entitled “Germination of crop species in response to whole-soil inoculants that originate from conventional vs organic farming systems”. This manuscript includes the results of WP2 from the SOFT project (ref. 890874).</p>
Database on the Performance of Current Agro-Ecological Farming Systems (AEFS) as an Input to the Modelling in WP4
<p>This database contains farm data (e.g. yields) and results (indicators) from assessments with the three decision support tools in the UNISECO case studies: SMART (www.fibl.org/en/themes/smart-en.html), Cool Farm Tool (coolfarmtool.org) and COMPAS (www.thuenen.de). This version (2.0) was developed as a benchmark for the assessment of exemplary cases of how the core dilemmas of agro-ecological transitions may be overcome at farm level and as an input to the modelling at territorial level in WP4.</p> <p>This database was created in the course of the H2020 project UNISECO. The project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 773901.</p>
Policy brief on intergenerational renewal in EU-farming systems. What can policy do?
<p>For a resilient farming system, smooth and sufficient intergenerational renewal is crucial, and it has been defined as one of nine goals for the CAP post-2020. Before implementing specific policy measures and instruments, however, policy makers must determine the degree and nature of the generational renewal problem that needs to be addressed. Also, policies need to focus on increasing the attractiveness of farming as an occupation and lifestyle, as many non-entry decisions are made before measures aimed at the young farmer start to play a role. Further policy directions include increasing the mobility of land and labour, supporting the management of extreme calamities as they involve a great risk of exit and non-entry and facilitating the provision of personal and farm-specific advice and coaching. The power and responsibility of national and regional governments to address these issues is often underestimated and overlooked.</p>
Description of tools for the sustainability assessment of farms and farming systems
<p><strong>The “summary” table shows the papers and names of the tools and the link to the main publication as well as the use of the paper in each part of the analysis. We presented the variables for all the methods in a table called “method” with the result of the classification. In the table “dimension”, we presented the extraction of the dimension of sustainability and classification of methods. We did the same for the “themes” with a colour that we used for providing the descriptive statistics on the number of themes per dimension. We used three tables for each indicator that present the name of the indicator as extracted in the publication.</strong></p>
Assessment of dairy cow welfare in small-scale farming systems dataset
<p>This database was created as preparatory work for the Scientific Opinion on the assessment of dairy cow welfare in small-scale farming systems (EFSA, 2015) to collect data for the description and the categorisation of European Small-Scale Dairy Farms (SSDF) based on size, farming system and husbandry practices and (ii) to analyse the feasibility in SSDF of animal-based measures usually used for intensive farming. The Scientific Opinion was necessary to address specific expectations of consumers on locally produced food and acceptable animal welfare conditions in the context of the EU Strategy for the protection and welfare of animals 2012-2015.</p> <p>The on-farm survey was run to collect data for welfare assessment covering Austria, France, Italy and Spain. A total of 124 farms with up to 75 cows were selected based on three criteria reflecting use of local resources or enrolment in a certification scheme: (1) the type of enterprise (ownership and workers), (2) the use of inputs in the production process, including the use of local feed and local breeds, and (3) the production type (certification schemes). From 124 dairy farms visited 119 were considered as SSDF. Among the 119 farms included in the survey as non-conventional, some of them had a very small herd size (44 had less than 25 cows and one had only 10 cows) and some of them had more animals (19 farms had between 51 and 75 dairy cows).</p> <p>The database includes 53 continuous and categorical farm descriptor variables, 23 continuous and categorical risk-factor variables and 47 animal-based measures in small-scale farms. The final data model used was based on data collection at farm/herd level, pen level and animal level.</p>
Dataset supplementing Lichtenberg et al. (2017) A global synthesis of the effects of diversified farming systems on arthropod diversity within fields and across agricultural landscapes. Global Change Biology
<p>This dataset contains data and scripts that supplement the publication</p> <p>Lichtenberg et al. (2017) A global synthesis of the effects of diversified farming systems on arthropod diversity within fields and across agricultural landscapes. Global Change Biology. DOI: 10.1111/gcb.13714</p> <p> </p> <p>Please cite the above article if you use any of the included data or code.</p> <p> </p> <p>Files are described in README.md.</p>
Empowering Coffee Farming Using Counterfactual Recommendation based RNN-IoT Integrated Soil Fertility Control System
Open the record for dataset details and reuse information.
Fig. 2 in Effects of Farming Systems on Insect Communities in the Paddy Fields of a Simplified Landscape During a Pest-control Intervention.
Fig. 2. Two-dimensional NMDS ordination of 40 insect communities sampled under different farming systems in northern Taiwan (stress = 0.18).
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>
Figure 4 in Relative abundance of oribatid mites (Sarcoptiformes: Oribatida) in two tillage systems of irrigated and rain-fed wheat farms of Khodabandeh County, Iran
Figure 4. Means comparison of shannon-wiener index of oribatid mites in four systems (Different letters on the top of the bars indicate significant difference at P <0.05 by Student Newman-Keuls test).
Figure 3 in Relative abundance of oribatid mites (Sarcoptiformes: Oribatida) in two tillage systems of irrigated and rain-fed wheat farms of Khodabandeh County, Iran
Figure 3. Means comparison of diversity of oribatid mites in sampling times (Different letters on the top of the bars indicate significant difference at P <0.05 by Student Newman-Keuls test).
Figure 2 in Relative abundance of oribatid mites (Sarcoptiformes: Oribatida) in two tillage systems of irrigated and rain-fed wheat farms of Khodabandeh County, Iran
Figure 2. Means comparison of species richness of oribatid mites in four systems (Different letters on the top of the bars indicate significant difference at P <0.05 by Student Newman.
Figure 1 in Relative abundance of oribatid mites (Sarcoptiformes: Oribatida) in two tillage systems of irrigated and rain-fed wheat farms of Khodabandeh County, Iran
Figure 1. Means comparison of species richness of oribatid mites in sampling times (Different letters on the top of the bars indicate significant difference at P <0.05 by Student Newman–Keuls test).
FIG. 18. — A-C in First in situ middle Pliocene cercopithecoid fossils from the Palaeokarst System of Bolt's Farm (South Africa)
FIG. 18. — A-C, Left lower molar of Papionina indet., specimen BPB 14: A, buccal view; B, lingual view; C, occlusal view; D-F, right lower fourth premolar (p/4) of Papionina indet., specimen BPB 15: D, buccal view; E, lingual view; F, occlusal view; G, H, lower left deciduous first incisor (di/1) of Papionina indet., specimen BPB 27: G, labial view; H, lingual view. Scale bar: 10 mm.
FIG. 22. — A, B in First in situ middle Pliocene cercopithecoid fossils from the Palaeokarst System of Bolt's Farm (South Africa)
FIG. 22. — A, B, Distal part of the ascending ramus of a right mandible of Cercopithecidae indet., specimen BPB 8: A, lateral view; B, distal view; C, D, distal part of the ascending ramus of a right mandible of Cercopithecidae indet., specimen BPB 26: C, lateral view; D, medial view; E, F, right intermediate manual phalanx of Cercopithecidae indet., specimen BPB 19: E, dorsal view; F, volar view. Scale bar: 10 mm.
FIG. 6 in First in situ middle Pliocene cercopithecoid fossils from the Palaeokarst System of Bolt's Farm (South Africa)
FIG. 6. — Teeth of Parapapio broomi Jones, 1937, specimen BPB 1: A, occlusal view of the right tooth row P4/-M3/; B, oblique-lingual view of M2/ and M3/. Scale bar: 10 mm.
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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
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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.