CIRAD Dataverse
Not a member yet
921 research outputs found
Sort by
SARS-CoV-2 serological results of five roe deer (Capreolus capreolus) populations in France sampled between 2010 and 2022
No full textThis dataset contains SARS-CoV-2 serological results obtained on the sera of roe deer (Capreolus capreolus) longitudinally monitored from december 2009 to march 2022 in 5 populations in France (the Chizé Integral Biological Reserve [46°05’N, 0°25’W], the Trois-Fontaines Territory of Experimental Study [48°43’N, 4°55’E], the 'Zone Atelier' PYGAR [a CNRS labeled study area, 43°16’N, 0°53’E], the Gardouch INRAE research station [43°22’, 1°40’E], and the private Praillebard Domaine [45°57’N, 4°55’E]).
The file `dataset_roedeer.csv` contains 2,563 rows and 16 columns compiling individual and serological information
Dataset on pesticidal plants for the control of cabbage pests
No full textThe aim of this work was to build a pesticide plant dataset of sufficiently reasonable size to produce numerous rules with variable support. To this end, we have extracted tables 3, 4, and 5 from Mondédji et al. (2021) and completed data in order to have a dataset that respects the data model. The resulting dataset describes a review of successful essays of pesticidal plants used to protect Brassicaceae against insect pest. Listed insect pests vary according to spatial location. For West Africa, all insect pests are listed. For Africa outside West Africa, pests are Plutella xylostella, Hellula undalis, and aphids (i.e., Lipaphis erysimi and Brevicoryne brassicae). Outside Africa, pests are P. xylostella, H. undalis and aphids (i.e., L. erysimi, B. brassicae, and Lipaphis pseudobrassicae) outside Africa. For each species (including pest), it is indicated whether it is used as medical care and whether it is consumed by human
Land cover maps for the district of Murewa in Zimbabwe, for the year 2023
No full textThis dataset consists of land cover maps for the district of Murewa in Zimbabwe, for the year 2023.
The dataset was created as part of the RAIZ (Resilience building through agroecological intensification in Zimbabwe) project FOOD/2021/424- 933 (https://raiz.org.zw/), founded by the European Union.
The land cover maps were generated using PlanetScope mosaics provided by the NICFI Program. Monthly mosaics, covering the period from June 2022 to June 2023, are provided at a 5m spatial resolution.
A deep learning model based on a 3D convolutional neural network (CNN) was used to process the satellite images. The images of the different dates are concatenated, and patches of 17x17 pixels are used as input, with the model predicting the class of the central pixel. This approach enables the model to learn spatial patterns in the images as well as temporal information. The inputs to the model included all available bands (blue, green, red, and near infrared) as well as the Normalized Difference Vegetation Index (NDVI).
Land Use Classes:
• Dense Woodlands (0): Areas with a dense canopy where grass is not visible from above. Trees are typically over 2 meters tall.
• Cropland (1): Land used for agricultural purposes, including fields and farms for crop cultivation.
• Grassland (2): Areas dominated by grass, with occasional shrubs and trees covering less than 20% of the area. These are primarily open grasslands.
• Open Woodlands (3): Savanna woodlands with a sparse canopy of trees (over 2 meters tall) and scattered shrubs.
• Mineral Soils (4): Rocky areas, including granitic mountains and hills, locally referred to as "Dwalas."
• Built-up Surface (5): Urbanized areas that include buildings, roads, and other man-made structures.
• Bare soil (6): Areas characterized by exposed earth with minimal to no vegetation
• Grassland Vlei (7): Wet grassland areas, typically found in low-lying or floodplain regions, where water accumulates seasonally.
• Water (8): Bodies of water such as rivers, lakes, and ponds
IRC lexicon for FNSSA - International Research Consortium lexicon for Food and Nutrition Security and Sustainable Agriculture
No full textThe Consortium Europe-Africa on Research and Innovation for Food Systems Transformation (CEA-FIRST) is a bicontinental effort put together to operationalise the International Research Consortium (IRC) as a long-term platform on Food and Nutrition Security and Sustainable Agriculture (FNSSA). One of the objectives of Work Package 2 of this project is to consolidate the existing FNSSA knowledge management system (KMS) tools to facilitate public access and knowledge sharing on relevant research activities and results. In this context, we have built the IRC lexicon to be integrated into the IRC knowledge management platform to fulfil semantic analysis and indexing needs.
IRC lexicon aims to encompass the relevant themes in relation to the FNSSA roadmap. The lexicon is the combination of 4 existing semantic resources, i.e. inputs to construct the final lexicon:
The FNSSA database keywords, corresponding to the keywords used by SLU librarians to tag the documents’ topics
The LEAP4FNSSA lexicon, built during the first stage of the project (https://www.sciencedirect.com/science/article/pii/S235234092200885X)
KEOPS lexicon, built to address specific thematic in side-projects (climate change, food security)
ASSET lexicon, dealing with agroecology (https://dataverse.cirad.fr/dataset.xhtml?persistentId=doi:10.18167/DVN1/TVN3AC)
These lexicons were merged and organized through several iterative steps involving two librarians (AL and AO), two researchers in text-mining (MR and SV) and a specialist in Information Management and KMS tools (TH). AL and AO validated the final version, ensuring that all keywords were categorized into their proper concept.
The IRC lexicon is divided into 25 concepts containing a total of 1779 keywords, including 17 priority concepts (priority themes in the roadmap) :
Agricultural intensification: 75 keywords
Agroecology: 129 keywords
By-products: 33 keywords
Crops: 134 keywords
Economy: 65 keywords
Food product: 29 keywords
Food security: 33 keywords
Food value chains and market: 113 keywords
Innovation: 68 keywords
Land use: 60 keywords
Livestock and animal production: 52 keywords
Nutrition: 60 keywords
Plant and soil health: 106 keywords
Research and knowledge sharing: 79 keywords
Types of agriculture: 53 keywords
Water management: 85 keywords
Weather conditions: 41 keywords
and 8 non-priority concepts (themes less relevant to address the FNSSA roadmap) :
Climate change: 78 keywords
Climate science: 51 keywords
Crisis: 105 keywords
Energy: 21 keywords
General: 73 keywords
Infrastructure: 13 keywords
One Health: 110 keywords
Social and cultural: 113 keywords
</ol
Determination of starch yield and hydrogen cyanide (HCN) for fresh grated cassava root at NaCRRI, Uganda.
No full textStarch yield and hydrogen cyanide (HCN) were assessed on 29 accessions of cassava in a preliminary yield trial (2023_PYT_B_Namulonge) using a gravimetric assay for starch yield and picrate assay for HCN
Ants from the Solicaz Kering Biodiversité Project
No full textRevegetation of mine site (AEX Crique Nuage
Traditional agroforestry systems in Timor-Leste can store large amounts of carbon in both soil and biomass
No full textThis dataset was collected in 30 agroforestry plots between June and August 2021, in two communities of communes (suco Gariuai and suco Samalari) in the Baucau region of Timor Leste. The raw data was collected mainly by two students from the agronomy department of the UNTL (Universidade Timor Lorosa'e) university, and inventory data used to calculate the above-ground tree biomass associated with 5 types of agroforestry system (SAF), identified in the study area (repetition of 3 plots per type of SAF and per suco).
There are four data files:
DATA_BIOMASS_TL_LARGE.xlsx: complete tree inventory data;
DATA_BIOMASS_TL_SHORT.xlsx: tree inventory data used in the analyses (report and scientific article);
RAW_DATA_SOIL_LARGE_TL.xls: complete soil data;
RESUME_DATA_SOIL_SHORT_TL.xls: soil data used in the analyses.
Each data file is accompanied by a data dictionary named "DDD_[file name].pdf".
traditional_afs_carbon_timor_manuscript.Rmd is the main script that creates the manuscript, including text, figures and tables. It uses "references.bib" for citations, and "renv.lock" for R package management.
The technical report submitted to the donors, presenting the main results, is also included
NIRS Calibration for hardness, cohesiveness as textural properties of Fufu dough at NRCRI, Umidike, Nigeria.
No full textThe textural properties of fufu dough samples were evaluated for potential good calibration and prediction equation models using handheld NIRS equipment. Seventy (70) cassava genotypes from Umudike and Otobi locations from Crossing block and Advanced Yield Trials (AYT) of NextGen were assessed for textural properties. Near-infrared spectra models were developed in “Win ISI 4 Project Manager”, by using the modified partial least squares (MPLS) regression and cross-validation techniques. Calibrations were done and the coefficient of determination in calibration for textural properties (R²cal) was 0.52 for hardness, while the coefficient of determination in calibration for textural properties (R²cal) was 0.54 for cohesiveness. Also, the coefficient of determination in prediction (R2pred) was 0.52 with SEP of 2.46 and RPD of 2.6
Genotyping data of “Candidatus Liberibacter asiaticus”, the bacterium that causes citrus Huanglongbing, in three outermost regions of the European Union
No full textRaw data for Pruvost et al., 2024. Evolutionary Applications. Genetic signatures of contrasted outbreak histories of “Candidatus Liberibacter asiaticus”, the bacterium that causes citrus Huanglongbing, in three outermost regions of the European Union. The dataset includes tandem repeat data of outbreak strains from Guadeloupe (n=148), Martinique (n=129) and Réunion (n=509) sampled from 2013 to 2022
QDA data, Instrumental textural data by TPA, Instrumental Color data for extraction of RTB genotypes with superior matooke quality traits from RTB breeding populations, at NARL, Uganda.
No full textThe selection of matooke clones with end-user acceptable traits is critical for ensuring consumer satisfaction and market competitiveness. This study evaluated various matooke clones based on sensory attributes, textural profile analysis (TPA), and colorimetric assessments using a Chroma meter. A 12-member panel of trained assessors conducted sensory evaluations, while instrumental analyses using a TMS-Pilot texture analyzer and a Chroma meter provided quantitative measures of texture and colour parameters (L*, a*, b* values) respectively. The findings indicate significant variations (p<0.05) among the clones in terms of firmness, adhesiveness, and cohesiveness, which correlate with consumer preferences. Additionally, colorimetric assessments highlight significant differences in appearance, an essential factor influencing consumer choices. The integration of sensory and instrumental analyses in this study identifies superior matooke clones with optimal textural and colour qualities