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118 results for “cropping systems”
GHG Dataset for the frontiers publication "Soil Nitrous Oxide Emission and Methane Exchange from Diversified Cropping Systems in Pannonian Region"
<p>GHG Dataset used in the Frontiers Publication "Soil Nitrous Oxide Emission and Methane Exchange from Diversified Cropping Systems in Pannonian Region". Additionally including CO2 besides N2O and CH4. Includes 3 cropping seasons.</p> <p>The data is also available online on the GHG flux visualisation and calculation tool "gasflxvis": https://sae-interactive-data.ethz.ch/gasflxvis/</p> <p>Further details on the calulation are provided both on gasflxvis and the Frontiers publication. Calculation procedure according the following PLOS ONE publication: http://dx.doi.org/10.1371/journal.pone.0200876</p>
Leaf Area Index on the GLBRC Biofuel Cropping System Experiment at the Kellogg Biological Station, Hickory Corners, MI (2009 to 2017)
Dataset AbstractThe leaf area index was measured to estimate the phenology and growth patterns of the different biofuel crops.original data source http://lter.kbs.msu.edu/datasets/225
Trace Gas Fluxes on the Main Cropping System Experiment at the Kellogg Biological Station, Hickory Corners, MI (1991 to 2019)
Dataset Abstract Trace gases (nitrous oxide, methane, and carbon dioxide) have been measured on the LTER Main Site since 1991 and on Successional and Forest sites since 1993. Trace gas fluxes are measured twice monthly or monthly until the ground freezes using permanently-installed, in-situ static chambers. CH4 and N2O are analyzed with gas-chromatography and CO2 with an infrared gas analyzer. Soil moisture and temperature are measured during sampling. original data source http://lter.kbs.msu.edu/datasets/16
Soil Moisture on the Main Cropping System Experiment at the Kellogg Biological Station, Hickory Corners, MI (1989 to 2019)
Dataset Abstract Measurements of soil moisture began in 1989 for all treatments on the LTER main site and in 1993 on the successional and forest sites. Soil moisture is analyzed on the baseline soil samplings which are collected twice monthly or monthly during the growing season. The percent gravimetric moisture content is calculated on a dry weight basis. Other datasets from the baseline soil samplings include Inorganic nitrogen and Total N and Total C. original data source http://lter.kbs.msu.edu/datasets/18
Annual Net Primary Production on the Main Cropping System Experiment at the Kellogg Biological Station, Hickory Corners, MI (1990 to 2018)
Dataset Abstract Aboveground annual net primary production (ANPP) has been measured on the LTER main site since 1990 and on the successional and forested sites since 1993. ANPP is measured at peak biomass for a given treatment. In some systems with multiple harvests or complex communities that have peaks occurring at different times of the year, measurements are taken at multiple times per year. Additional ANPP measurements are made where appropriate using leaf litter traps, estimates of diameter from tree basal diameter and for the poplar treatment occasional destructive harvests. See the ANPP protocol for descriptions of the sampling and measurement methods for each of the treatments. original data source http://lter.kbs.msu.edu/datasets/22
Soil Inorganic Nitrogen on the Main Cropping System Experiment at the Kellogg Biological Station, Hickory Corners, MI (1989 to 2018)
Dataset AbstractMeasurement of soil inorganic nitrogen began in 1989 for all treatments on the LTER Main Site and 1993 on the Successional and Forest sites. Ammonium and nitrate are analyzed twice monthly or monthly during the growing season on baseline soil samplings. Additional datasets from the Baseline Soil Samplings include soil moisture, total N and total C.original data source http://lter.kbs.msu.edu/datasets/24
Insect Population Dynamics on the Main Cropping System Experiment at the Kellogg Biological Station, Hickory Corners, MI (1989 to 2019)
Dataset Abstract Plant dwelling insect occurrence in the LTER main site (all treatments) of the KBS-LTER has been recorded since 1989 and in the successional and forest sites since 1993. The effort has focused on characterizing the temporal and spatial abundance and diversity of a set of insects representative of a higher order insect trophic level, the herbivore predators. The insect database contains more than 400,000 records and consists of counts of adult insects of fourteen species of Coccinellidae, one species of Chrysopidae, and one species of Lampyridae from 30 sample sites in each of the seven treatments in the LTER Main Site. The standard method used to measure these organisms is a yellow sticky trap. Sampling is conducted weekly during the growing season as described in the sampling protocol. original data source http://lter.kbs.msu.edu/datasets/26
Main Cropping System Experiment Field Logs and treatment descriptions at the Kellogg Biological Station, Hickory Corners, MI (1988 to 2020)
Dataset Abstract This dataset includes information about the LTER main site treatments, agronomic practices carried out on the treatments and approved site use requests. Most long-term hypotheses associated with the KBS LTER site are being tested within the context of the main cropping systems study. This study was established on a 48 ha area on which a series of 7 different cropping systems were established in spring 1988, each replicated in one of 6 ha blocks. An eighth never-tilled successional treatment, is located 200 m off-site, replicated as four 0.06 ha plots. Cropping systems include the following treatments: T1. Conventional: standard chemical input corn/soybean/wheat rotation conventionally tilled (corn/soybean prior to 1992) T2. No-till: standard chemical input corn/soybean/wheat rotation no-tilled (corn/soybean prior to 1992) T3. Reduced input: low chemical input corn/soybean/wheat rotation conventionally tilled (ridge till prior to 1994) T4. Biologically based: zero chemical input corn/soybean wheat rotation conventionally tilled (ridge till prior to 1994) T5. Poplar: Populus clones on short-rotation (6-7 year) harvest cycle T6. Alfalfa: continuous alfalfa, replanted every 6-7 years (converted to switchgrass in 2018) T7. Early successional community: historically tilled soil T8. Mown grassland community: never-tilled soil. For specific crops in a given year see the Annual Crops Summary Table. In 1993 a series of forest sites were added to the main cropping system study to provide long-term reference points and to allow hypotheses related to substrate diversity to be tested. These include: TCF. Coniferous forest: three conifer plantations, 40-60 years old TDF. Decidious forest: three deciduous forest stands, two old-growth and one 40-60 years post-cutting TSF. Mid-successional forest: three old-field (mid-successional) sites 40+ years post-abandonment. All share a soil series with the main cropping system treatments, and are within 5 km of all other sit
Optimal elevated agrivoltaic system design and key performance indicators across Europe based on three crop light levels
<p>Optimal elevated (stilted) agrivoltaic system design (PV coverage ratio) is given on a European gridded level (25km grid and NUTS3 regions) based on three light levels: shade-loving crops (daily light integral (DLI) of 12 mol/m²day), shade-tolerant crops (DLI of 12 mol/m²day) and shade-intolerant crops (DLI of 25 mol/m²day)</p> <p>Estimations of other performance indicators are given: power capacity (kWp/ha), energy production (MWh/ha), levelized cost of electricity (€/MWh) and land equivalent ratio (LER -).</p> <p>The assumptions and methodology of this dataset can be found in the article "Geospatial assessment of elevated agrivoltaics on arable land in Europe to highlight the implications on design, land use and economic level."</p> <p>Interactive maps can be found on https://iiw.kuleuven.be/apps/agrivoltaics/maps.html</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>
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>
Global Crop Type Validation Data Set for ESA WorldCereal System
<p>This dataset was created by using a new IIASA tool, called “Street Imagery validation” (<a href="https://svweb.cloud.geo-wiki.org/">https://svweb.cloud.geo-wiki.org/</a>) where users could check street level images (e.g., Google Street Level images, Mapillary etc.) and identify the crop type where it is possible. The advantage of this tool is that there are plenty of georeferenced images with dates, going back in time. The disadvantage is that users need to check plenty of images where only few will clearly show cropland fields that are mature enough to be identified. To make the data collection more efficient, we provided our experts with preliminary maps of points in agricultural areas where street level images are available for the year 2021. Then, the experts checked those locations in an opportunistic way. The dataset is completely independent from all the existing maps and the reference datasets.</p> <p>There are 3 main data records uploaded:</p> <ol> <li>sv_croptype_poly.zip – an archive with a shapefile containing all the collected polygons with crop type information. Not all the polygons correspond to actual field boundaries.</li> <li>sv_croptype_validations.csv – a table with crop type observations with centroid coordinates in WGS84</li> <li>sv_worldcereal_validation.csv – a table with a subset of crop type observations used in validation of WorldCereal crop type maps for 2021.</li> </ol> <p>Fields:</p> <ul> <li>"id" – unique observation identifier;</li> <li>"imgSource" – source of imagery used for visual inspection;</li> <li>"imgLoc" – image location;</li> <li>"svImgDate" – image date;</li> <li>"imageIdKey" – image unique identifier;</li> <li>"submitedAt" – date of submission of crop type observation;</li> <li>"cropType" - crop type observation;</li> <li>"irrType" – irrigation type;</li> <li>"x", "y" – centroids of submitted polygons in WGS84.</li> </ul>
Raw Data for Publication "Desmodium Volatiles in "Push-Pull" Cropping Systems and Protection Against the Fall Armyworm, Spodoptera frugiperda"
<p>This repository contains all raw and processed data related to the publication titled "Desmodium Volatiles in "Push-Pull" Cropping Systems and Protection Against the Fall Armyworm, Spodoptera frugiperda" written by Daria M. Odermatt, Frank Chidawanyika, Daniel M. Mutyambai, Bernhard Schmid, Luiz A. Domeignoz-Horta, Collins O. Onjura, Amanuel Tamiru and Meredith C. Schuman.</p> <p>The data is subdivided in four sections:</p> <ol> <li>Volatile sampling of Desmodium intortum, D. incanum, and maize headspaces</li> <li>Oviposition bioassays comparing moth egg-laying preferences on maize vs. Desmodium (direct and indirect exposure)</li> <li>Choice assays evaluating moth behavior in response to maize alone vs. maize with Desmodium volatiles</li> <li>No-choice assays evaluation moth attraction toward maize alone, maize + D. intortum and maize + D. incanum</li> </ol> <p>More detailed information is available in the README files located within each folder.</p>
Data and results for manuscript "Multi-frequency electrical impedance tomography as a non-invasive tool to characterize and monitor crop root systems "
<p>Root systems are essential in nutrient uptake and translocation, but are difficult to characterize non-invasively with existing methods. We propose electrical impedance tomography (EIT) as a new tool for the imaging and monitoring of crop root systems. In a laboratory experiment we demonstrate the capability of the method to capture physiological responses of root systems with high spatial and temporal resolution. We conclude that EIT is a promising functional imaging technique for crop roots.</p> <p>This package contains measured raw EIT data, electrical imaging results, spectral results from the Debye decomposition, and the Python scripts used to generate the plots in the manuscript.</p>
Data from: Earthworms do not increase greenhouse gas emissions (CO2 and N2O) in an ecotron experiment simulating a realistic three-crop rotation system
<p><span>Earthworms are known to stimulate soil greenhouse gas (GHG) emissions, but the majority of previous studies have used simplified model systems or lacked continuous high-frequency measurements. To address this, we conducted a two-year study using large lysimeters (</span><span>5 m<sup>2</sup> area and 1.5 m soil depth) </span><span>in an ecotron facility, continuously measuring ecosystem-level CO<sub>2</sub>, N<sub>2</sub>O, and H<sub>2</sub>O fluxes. We investigated the impact of endogeic and anecic earthworms on GHG emissions and ecosystem water use efficiency (WUE) in a simulated agricultural setting. Although we observed transient stimulations of carbon fluxes in the presence of earthworms, cumulative fluxes over the study indicated no significant increase in CO<sub>2</sub> emissions. Endogeic earthworms reduced N<sub>2</sub>O emissions during the wheat culture (-44.6%), but this effect was not sustained throughout the experiment. No consistent effects on ecosystem evapotranspiration or WUE were found. Our study suggests that earthworms do not significantly contribute to GHG emissions over a two-year period in experimental conditions that mimic an agricultural setting. These findings highlight the need for realistic experiments and continuous GHG measurements.</span></p>
263 MAG annotations for three nested metagenomic studies describe crop-shrub-microbe interactions in an agroecology system in the Sahel
<p>The Sahel region of West Africa is a vulnerable eco-region, where climate change induced drought and a rapidly growing population pose serious threats to food security and contribute to soil degradation. Local and biologically based systems are necessary to maintain crop yields and soil health, and intercropping with native woody shrubs Guiera senegalensis has been discovered as a solution. We have previously shown that soil microbial communities are significantly altered by the presence of shrubs, and that these organisms may have plant growth promoting properties. Here, we augment those data with metagenomic and metatranscriptomic data across three nested experiments: a landscape scale experiment across a rainfall and soil type gradient, a long-term experimental site, and a growth chamber simulated drought experiment. We recovered 263 95% ANI dereplicated metagenome-assembled genomes (MAGs) of medium and high quality to evaluate their relative enrichment and what their encoded metabolisms reveal about mechanisms of microbiome millet support. These data contribute to our understanding of the role of the microbial community crop drought resilience in the Sahel and in semi-arid cropping systems globally. Here we present the DRAM annotations of each MAG, all associated metadata, viral genes and vOTUs from the Optimized Shrub Intercropping Study (OSS), and eukaryotic contigs from the OSS</p>
Supporting dataset for manuscript "Estimating the microarthropod diversity in cropping systems by comparing ecological indices across Europe" by Bigiotti et al. 2025
<p>This dataset contains counts of mesofauna individuals classified as Biological Forms (BF). It represent the raw data used for all indices calculation in the manuscript entitled "Microarthropod communities' diversity for soil health assessment: comparing several ecological indices across Europe" by authors Gaia Bigiotti, Francesco Vitali, Stefano Mocali, Giovanni L’Abate, Eligio Malusà, Dawid Kozacki, Irena Bertoncelj, Morgane Ourry, Massimo Pugliese, Heinrich Maisel, Expedito Olimi, Maria Grazia Tommasini, Carlo Jacomini, and Lorenzo D’Avino.</p>
RICE WHEAT CROPPING SYSTEMS-CONSTRAINTS AND STRATEGIES : A REVIEW
<p>The rice-wheat cropping system (RWCS) in the Indo-Gangetic plains (IGP) of South Asia with the help of Green<br> Revolution in the early 1970’s greatly contributed to India's food self-sufficiency and livelihood of millions of<br> peoplethus, became the country's primary source of food-grain production. However, deterioration of soil health and<br> quality, ground water depletion, water stress, labour shortage, introduction of new weeds and pests particularly<br> Phalaris minor, Scirpophaga incertulas and climate change have all contributed to a major production standstill and<br> deterioration in recent years by which the sustainability of rice wheat cropping system is now at jeopardy. Traditional<br> agronomic practices had various negative implications on the sustainability of rice wheat cropping system with the<br> introduction of HYVs. So, a paradigm shift is required to achieve long-term productivity, sustainability and allow<br> farmers to minimise inputs, optimise yields, enhance profitability, maintain the natural resource base and reduce risk<br> owing to both environmental and economic issues through resource-conserving technologies (RCTs) including<br> zero/minimaltillage, PUSA decomposer, bed planting, crop residue management, mechanical rice transplanter (MRT)<br> and crop diversification. This article focuses some of the issues that need to be addressed in the RWCS in order to<br> achieve the goal of increasing regional productivity and assuring food security while maximising the effective use of<br> natural resources, enhancing rural livelihoods and aiding in poverty alleviation.</p>
Field margins and cropping system influence natural enemies of bean aphids
<p>The data presents beneficial effects of field margin vegetation on natural enemies with reduced aphid infestation in lablab field plots and higher grain yield. The data further shows that cropping system have some influence on natural enemy diversity and abundance.</p>
Figure 7. The outcomes of the Monitoring and Control of the Greenhouse soil and climate Conditions for tomato crops-Design and Development a Control and Monitoring System for Greenhouse Conditions Based-On Multi Agent System
<p>In the past generation greenhouses it was enough to have one cabled measurement point in<br> the middle to provide the information to the greenhouse automation system. The system itself was<br> usually simple without opportunities to control locally heating, lights, ventilation or some other<br> activity, which was affecting the greenhouse interior climate. The optimal greenhouse climate and<br> soil adjustment can enable us to improve productivity and to achieve remarkable energy savings. In<br> this paper we proposed a multi-agent methodology for integrated management systems in<br> greenhouses. In this regards wireless sensor networks play a vital role to monitor greenhouse and<br> environment parameters. Each controlled process of the greenhouse environment is modeled as an<br> autonomous agent with its own inputs, its own outputs and its own interactions with the other<br> agents. Each agent acts autonomously, as it knows a priori the desired environmental set-points. In<br> this way, any possible conflicting decisions of conventional environmental control methodologies<br> are resolved through negotiations between the agents so that the possible optimal integrated solution<br> is achieved. The developed system is simple, cost effective, and easily installable.</p>
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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.