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NIRS Database on Fresh Cassava, Wet Mashed Fufu & Dried Fufu Flour for Dry matter, Starch & Amylose Calibrations at NRCRI, Nigeria
No full textThe dataset contains spectra data of samples of fresh cassava roots and fufu mash from the Uniform Yield and NCRP Trials harvested in Umudike and Otobi in Nigeria obtained using QualitySpec Trek: S-10016 used to predict starch, dry matter and amylose
Caractérisation fonctionnelle d'espèces adventices pour évaluer leur nuisibilité en canne à sucre à La Réunion
No full textJeux de données intégrant la caractérisation de 13 espèces d'adventices via des traits fonctionnels aériens et racinaires sur des individus prélevés en parcelles de canne à sucre, les relevés floristiques avec recouvrement global et par espèces d'adventices selon le protocole de notation de P.Marnotte (note de 1 à 9), le suivi de biomasse et hauteur de canne durant le cycle et à récolte dans un essai comprenant deux modalités témoins (totalement désherbées ou totalement enherbées durant tout le cycle) et 3 modalités de couverts d'adventices sélectionnés (vivaces, dicotylédones, lianes)
NIRS Database on boiled Matooke mash at NaCRRI & IITA, Uganda
No full textOne of the definitive features of products from banana or “matooke” is the change in product characteristics after processing. With this understanding, it is imperative to understand whether processed product profile has a bearing on defining consumer acceptability. To understand this, spectra acquisition from boiled and mashed banana was undertaken using the ASD quality Spec. A total of 104 spectra were acquired from 34 genotypes from IITA breeding population after mashing the boiled bananas. In addition, reference information for these samples 42 determination of dry matter content was generated. Continuous spectra acquisition and reference information generation is being undertaken to allow for the use of NIRS in prediction of consumer acceptability and quality traits such as tokeness
High resolution map of plant available water content for Burkina Faso, derived from iSDA Africa 30m soil properties maps using USDA Rosetta3 model
No full textPurpose:
The purpose of this dataset is to provide a high resolution map of available water content for Burkina Faso derived from 30m soil properties maps using the iSDA Africa dataset and the USDA Rosetta3 model. The map can be used to notably support spatialized crop simulation models to determine potential crop yields across West Africa.
Nature and extent of data:
The dataset consists of a high resolution map of plant available water content derived from four soil property datasets from iSDA Africa. The soil properties include sand, clay, silt and fine-earth bulk density, and were predicted at a 30m resolution for 0-20 cm and 20-50cm depth intervals. The USDA Rosetta model was used to compute soil water retention properties from four iSDA layers (sand, clay, silt content, and fine-earth bulk density), including the van Genuchten parameters of residual water content, saturated water content, 'alpha' shape parameter, 'n' shape parameter, and saturated hydraulic conductivity. From these parameters, the volumetric water content at field capacity and permanent wilting point was computed using the van Genuchten-Mualem model. The output map has been filled with nearest neighbor interpolation where NaN values were present. Finally, available water content integrated over the soil profile down to 50cm and to the bedrock depth was calculated.
Location and coverage:
The dataset covers the country of Burkina Faso in West Africa at a 30m resolution.
Temporal scope:
The dataset was created using soil property data and models from iSDA Africa and USDA Rosetta3, respectively, and covers the temporal scope of the original datasets.
Archive formats / unzipping:
Some of the archive files are separated in multiple parts, as indicated by their numeral file extensions (i.e. *.001, *.002, etc). To unzip these files, please consider using an unzipping software such as 7zip, that will manage file concatenation and unzipping given that all parts are stored under the same folder in your file system
A global database to quantify the impacts of agricultural management practices on terrestrial biodiversity
No full textThis dataset gathers mean effect sizes on the effects of agricultural management practices on biodiversity, extracted from a list of meta-analyses obtained with a systematic review process. We applied no geographical or temporal restriction.
Details on the methods and content of the database is available in the associated DataPape
North Chin - Myanmar - 2020-2021 - Land cover map
No full textThe land cover maps published here were produced for four regions of the northern part of Chin state in Myanmar: Hakha, Falam, Tedim and Thantlang. This work was carried out as part of the ALIVE FNS project to monitor land use (forests, cultivated land, built-up areas, etc.). We used the Moringa processing chain, which is based on satellite imagery (Sentinel 2 free of charge time series and SPOT6-7 very high spatial resolution) and a supervised classification algorithm (Random Forest) trained on a reference database made of polygons associated with a land cover class. Generally, this database comes from ground GPS surveys, but it can be replaced by photo-interpretation of very high spatial resolution images if field collection is unavailable or impossible, as it is the case here in the State of Chin. The database was therefore obtained by photo-interpretation of Spot6/7 images acquired as part of the Dinamis programme.
The nomenclature includes 4 crop classes (irrigated crops - mainly rice, shifting cultivation, new shifting cultivation, old shifting cultivation) and 6 non-crop classes (open spaces with little or no vegetation, herbaceous vegetation, shrubland, wooded vegetation, water, built-up areas). The maps are available, for the years 2020 and 2021, at a spatial resolution of 1.5 m over the parts covered by SPOT6/7 imagery (approximately half of the study area) and at a spatial resolution of 10m using only Sentinel-2 imagery over the whole area comprising the 4 regions: Hakha, Falam, Tedim, Thantlang.
The overall and class accuracies (f-score) of the maps are available in a text file included in the archive containing the maps.
Les cartes d'occupation du sol diffusées ici ont été produites sur quatre régions situées au Nord de l’état du Chin au Mynanmar : Hakha, Falam, Tedim, Thantlang. Ces travaux ont été réalisés dans le cadre du projet ALIVE FNS pour observer l'occupation des sols (forêts, terres cultivées, surfaces bâties, etc.). Nous avons utilisé la chaine Moringa qui s'appuie sur l'imagerie satellite (Sentinel 2 et SPOT6-7) et un algorithme de classification supervisée entraîné à partir d'une base de données de référence représentative de l'occupation des sols. Généralement, cette base de données est constituée à partir de relevés GPS sur le terrain, mais elle peut être remplacée par une photo-interprétation sur des images à très haute résolution spatiale si la collecte sur le terrain n'est pas disponible ou impossible, comme c'est le cas ici dans l'État de Chin. La base de données a donc été obtenue par photo-interprétation d’images Spot56/7 acquises dans le cadre du dispositif Dinamis.
La nomenclature comprend 4 classes de cultures (cultures irriguées - principalement le riz, cultures itinérantes, nouvelles cultures itinérantes, anciennes cultures itinérantes) et 6 classes de non-cultures (espaces ouverts avec peu ou pas de végétation, végétation herbacée, zones arbustives, végétation boisée, eau, surfaces bâties). Les cartes sont disponibles, pour les années 2020 et 2021, à une résolution spatiale de 1,5m sur les parties couvertes par l'imagerie SPOT6/7 (non gratuites) et à une résolution spatiale de 10m utilisant uniquement des images Sentinel-2 (gratuites) sur une zone plus grande comprenant l’ensembles dans 4 régions : Hakha, Falam, Tedim, Thantlang.
Les précisions globales et par classes des cartes sont disponible dans un fichier texte inclus dans l’archive contenant les cartes
Indice de sécurité alimentaire avec données satellitaires au Burkina Faso
No full textCe jeu de données décrit les indicateurs de score alimentaire (SCA et SDA) couplés avec différentes données satellitaires donnant des informations sur la végétation, les cultures, le climat au Burkina Faso, de 2010 à 2020
Gendered Food Mapping Data on Boiled and Pounded Yam generated by NRCRI in Nigeria
No full textThis dataset contains data generated during the Activity 3 or Step 2 - Gendered food mapping performed by the NRCRI team in Nigeria on Boiled and Pounded Yam, within the RTBfoods project (following the Methodological Guidance).
This dataset may contain diverse types of anonymized data (e‧g. questionnaires, cleaned and processed data) which is to be available on open access following a 2-years embargo after the end of the RTBfoods project (embargo ending date: 15 March 2025)
This dataset may also contain non-anonymized data (e‧g. raw data, consent forms signed by interviewees) which cannot be made publicly available, at any time; non-anonymized data is contained in the .tar‧gz file. For more information about the content of the .tar‧gz file, you are invited to contact the authors mentioned in the metadata
Geographic coordinates of the uçá crab (Ucides cordatus) fishing grounds located in the mangroves of the coastal zone of Pará, Brazil, in the years 2019 and 2020
No full textNames and geographic coordinates of the fishing grounds of uçá crab (Ucides cordatus), located in the mangrove swamps of the coastal zone of Pará. These data were obtained through participatory mapping in focus groups carried out with uçá crab fishermen from the municipalities of Quatipuru, Tracuateua, Bragança and Augusto Corrêa, in coastal zone of the State of Pará, Brazil, between October 2019 and January 2020
Consumer Testing Data on Boiled Cassava generated by NaCRRI in Uganda
No full textThis dataset contains data generated during the Activity 5 or Step 4 - Consumer Testing in Rural and Urban Areas performed by the NaCRRI team in Uganda on Boiled Cassava, within the RTBfoods project (following the Methodological Guidance and its supplement).
This dataset may contain diverse type of anonymized data (e‧g. questionnaires, cleaned and processed data) which is to be available on open access following a 2-years embargo after the end of the RTBfoods project (embargo ending date: 15 March 2025)
This dataset may also contain non-anonymized data (e‧g. raw data, consent forms signed by interviewees) which cannot be made publicly available, at any time; non-anonymized data is contained in the .tar‧gz file. For more information about the content of the .tar‧gz file, you are invited to contact the authors mentioned in the metadata