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Record W4200478738 · doi:10.1007/s42452-021-04898-6

Okra (Abelmoschus esculentus) in a refugee context in East Africa: Kitchen gardening helps with mineral provision

2021· article· en· W4200478738 on OpenAlexafffund
Desta Woldetsadik, Eulogio J. Llorent‐Martínez, Solomie Gebrezgabher, Mary Njenga, Ruth Mendum, Roxana Castillo-López, M.L. Fernández-de Córdova, Hillette Hailu, Colby T. Evans, Nelly Madani, Tamlyn P. Mafika, David Fleming

Bibliographic record

VenueSN Applied Sciences · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Micronutrient Interactions and Effects
Canadian institutionsMount Allison University
FundersCentro de Instrumentación Científico-Técnica, Universidad de JaénNatural Sciences and Engineering Research Council of CanadaNational Institute of Food and AgricultureConsortium of International Agricultural Research CentersJunta de AndalucíaUniversidad de JaénU.S. Department of AgricultureBundesministerium für Wirtschaftliche Zusammenarbeit und EntwicklungMount Allison University
KeywordsRefugeeGeographyInductively coupled plasma mass spectrometryChemistryMass spectrometryArchaeology

Abstract

fetched live from OpenAlex

Abstract Kitchen gardening is considered a way to reconnect with agriculture and complement the cereal-based relief food offered to refugees in East Africa. This work aimed at profiling mineral content of okra in four refugee camps and settlements located in Ethiopia and Uganda and its contribution to adequate intake (AIs) or recommended dietary allowances (RDAs) for young children and pregnant and lactating women (PLW). The study also evaluated the applicability of portable X-ray fluorescence (PXRF) as compared with inductively coupled plasma mass spectrometry (ICP-MS) for mineral profiling of okra powder samples. The contents of minerals (mg kg −1 ) from the ICP-MS readings were in the following ranges: K (14,385–33,294), Ca (2610–14,090), P (3178–13,248), Mg (3896–7986), Cu (3.81–19.3), Fe (75.7–1243), Zn (33–141) and Mn (23.1–261). Regardless of geographic origin, at low-end consumption probability (17 g day −1 for young children and 68 g day −1 for PLW), okra could contribute ˂ 15% (2.7–12.9%) AI for macro-minerals (K and Ca). In addition, the contributions to RDA values for Fe and Zn, elements of known public health interest, ranged from 4.5 to 34.7% for young children. Interestingly, regression lines revealed strong agreement between ICP-MS and PXRF readings for Mn and Zn, with R 2 values > 0.91. This information is useful in support of nutrition-sensitive kitchen gardening programs through scaling culturally important crops in refugee settings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.772
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.209
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2021
Admission routes2
Has abstractyes

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