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118 results for “cropping systems”
Yield data for "Sanford, G. R. et.al. 2016. Comparative productivity of alternative cellulosic bioenergy cropping systems in the North Central USA. Agriculture, Ecosystems and Environment 216:344-355."
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Profitability, energetics and GHGs emission estimation from rice-based cropping systems in the coastal saline zone of West Bengal, India
<p>This study compares thirteen rice-based cropping systems in the coastal part of West Bengal, India in terms of productivity, profitability, energetics, and emissions. Information on the crop management practices of these systems was collected on 60 farms through a questionnaire survey.</p>
Data from: Census parcels cropping system classification from multitemporal remote imagery: a proposed universal methodology
A procedure named CROPCLASS was developed to semi-automate census parcel crop assessment in any agricultural area using multitemporal remote images. For each area, CROPCLASS consists of a) a definition of census parcels through vector files in all of the images; b) the extraction of spectral bands (SB) and key vegetation index (VI) average values for each parcel and image; c) the conformation of a matrix data (MD) of the extracted information; d) the classification of MD decision trees (DT) and Structured Query Language (SQL) crop predictive model definition also based on preliminary land-use ground-truth work in a reduced number of parcels; and e) the implementation of predictive models to classify unidentified parcels land uses. The software named CROPCLASS-2.0 was developed to semi-automatically perform the described procedure in an economically feasible manner. The CROPCLASS methodology was validated using seven GeoEye-1 satellite images that were taken over the LaVentilla area (Southern Spain) from April to October 2010 at 3- to 4-week intervals. The studied region was visited every 3 weeks, identifying 12 crops and others land uses in 311 parcels. The DT training models for each cropping system were assessed at a 95% to 100% overall accuracy (OA) for each crop within its corresponding cropping systems. The DT training models that were used to directly identify the individual crops were assessed with 80.7% OA, with a user accuracy of approximately 80% or higher for most crops. Generally, the DT model accuracy was similar using the seven images that were taken at approximately one-month intervals or a set of three images that were taken during early spring, summer and autumn, or set of two images that were taken at about 2 to 3 months interval. The classification of the unidentified parcels for the individual crops was achieved with an OA of 79.5%.
MAgPIE model input data sets: Climate change-driven global land-use system adaptation under CMIP6-based crop model projections
<p>These MAgPIE input data sets include harmonized crop yield projections from several crop models (9 crop models and 5 climate models). Additionally, regional, validation, and calibration data sets are also reported.</p>
FIGURE 1 in New species and records of earthworms (Annelida, Oligochaeta) in plantain cropping systems in Colombia's coffee-growing region
FIGURE 1. Distribution of farms in Quindío department, Colombia.
Data from: Cover crop root contributions to soil carbon in a no-till corn bioenergy cropping system
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Data from: Census parcels cropping system classification from multitemporal remote imagery: a proposed universal methodology
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Reveal seasonal climatic variations affect terpenes, norisoprenoids, and green leaf volatiles accumulation in four grape varieties under a double cropping system
GEO Series GSE168785. Vitis vinifera. 36 samples. Type: Expression profiling by high throughput sequencing.
Plant virus diversity in invasive weeds and crop plant varying between plant species and management systems
GEO Series GSE132755. Medicago sativa; Erigeron annuus; Solanum tuberosum; Erigeron canadensis; Zea mays; Solidago canadensis. 6 samples. Type: Expression profiling by high throughput sequencing.
Which pitfall traps and sampling effort to choose to evaluate cropping system effects on spider and carabid assemblages?
<p>Dataset and example of the script (R) used in the simulation approach.</p>
LTM_AC_crop: dataset of Long term monitoring of crop yield in young arable alley cropping systems in Belgium
<p>Dataset including results from crop yield and crop quality measurements obtained on a set of six alley cropping fields in Belgium during the first decade after their establishment. Sampled crops include maize, wheat, barley and potato. Measurements started in 2015 and are at present still continued. A transect approach is used in wich crop production is monitored at fixed distances from the trees (2m, 5m and 12m). Ton dry matter is assessed as well as crop specific quality parameters (a.o. for winter cereals: protein content & thousend kernel weight, silage maize: protein content & digestability, potato: under water weight and diameter fractions). For a detailed description of methodologies used see also: Pardon et al. (2018) (<a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.agsy.2018.08.008" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.agsy.2018.08.008</span></span></a>).</p>
Data for : EU Green Deal improves food system sustainability with unequal economic impacts on consumers and producers of crops and livestock
<p>Data for an article in Communications Earth Environment - soler et al-SM3 file presents the economic model used to simulate the impacts of changes in agricultural practices, food waste and consumers' diets in the framemork of the European Green Deal proposed by the European Commission. It displays the data used to calibrate the economic model, the coefficients used to calculate the non-market environmental and nutritional impacts, and the detailed results of simulated scenarios. It provides the list of variables and parameters used in the model. The data sources used for the calibration process are detailed, as well as the status of each variable (endogenous vs exogenous). The model calibration process aims at determining (reproducing) the baseline scenario that represents the current situation; it checks that production, consumption, and price estimates calculated with the economic model are equal to those currently observed. </p> <p>soler et al-SM4 provides sensibility tests for different parameter sets</p>
Dissecting the Variations of Ripening Progression and Flavonoid Metabolism in Grape Berries Grown under Double Cropping System
GEO Series GSE103226. Vitis vinifera. 36 samples. Type: Expression profiling by high throughput sequencing.
Estimation of crop yield and profit of agrivoltaics under both half-density and full-density PV system scenarios
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Advanced Biofuel Value Chains Sourced by New Cropping Systems with Low iLUC Risk
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Dissecting the Variations of Transcriptome in Grape Berries Grown under Double Cropping System
GEO Series GSE122411. Vitis vinifera. 36 samples. Type: Expression profiling by high throughput sequencing.
Contribution of wheat and maize to soil organic carbon in a wheat-maize cropping system: a field and laboratory study
<ol> <li>Retention of crop biomass is widely recommended to improve soil organic carbon (SOC). However, the magnitude of contribution of aboveground residues and belowground roots from C3 and C4 crops to SOC is unclear.</li> <li>Data from a 10-year field experiment and a 60-day laboratory incubation were synthesized to identify the respective contribution of C3 (e.g., wheat) and C4 (e.g., maize) residues and roots to SOC, as well as its underlying mechanisms under no-till (NT) using <sup>13</sup>C labelling trace in wheat-maize rotations.</li> <li>The field experiment showed that residue retention significantly increased SOC accumulation, and SOC derived from wheat was 126.0% higher than that from maize. Conversion to NT promoted SOC derived from wheat and thus accumulated 17.6% higher SOC stock compared with plow tillage (PT) under residue returning at 0-20 cm soil depth (<em>P</em><0.05). The data from laboratory incubation revealed the mechanisms that lower priming effects at 0-10 cm depth decreased total mineralization by 91.8% after inputs of wheat residues and roots compared with that of maize residues and roots, especially under NT compared with PT. Priming effects were negatively correlated with enzyme activities associated with the C recycle, SOC, and total nitrogen (TN) contents (<em>P</em><0.01). NT increased enzyme activities, SOC, and TN contents and thus reduced priming effects and improved residual carbon.</li> <li><em>Synthesis and applications.</em> These results suggested that wheat may contribute more to SOC accumulation than maize, and carbon increment efficiency in farmland could be enhanced by considering the crucial roles of C3 crops in SOC accumulation. NT practice sustains the benefits of C3 crops to SOC sequestration in the upper soil depths.</li> </ol>
Data from "Crop yields fail to rise in smallholder farming systems in sub-Saharan Africa"
<p>All micro-data used to undertake analysis is present in this dataset.</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)
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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.