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Record W1892374970 · doi:10.5539/jfr.v4n5p81

Occurrence of Aflatoxin in Some Food Commodities Commonly Consumed in Nigeria

2015· article· en· W1892374970 on OpenAlexvenueno aff
Ima O. Williams, S. A. Ugbaje, Godwin Oju Igile, Onot Obono Ekpe

Bibliographic record

VenueJournal of Food Research · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycotoxins in Agriculture and Food
Canadian institutionsnot available
Fundersnot available
KeywordsAflatoxinArachisFood scienceBiologyHorticulture

Abstract

fetched live from OpenAlex

Aflatoxicosis is a public health problem in Nigeria like other tropical and sub-tropical regions of the world. Control of aflatoxin contamination requires thorough risk assessment, monitoring, quality control and empirical data. This study assayed total aflatoxin levels, identified and quantified four aflatoxin types in five food commodities commonly consumed in the six geopolitical zones of Nigeria. The food materials: <em>Zea mays, Colocynthis citrullus, Capsicum frutescens, Irvingia gabonensis</em> and <em>Arachis hypogea</em> were obtained from Watt market in Calabar urban. ELISA method was used for total aflatoxin, HPLC for aflatoxin types, AOAC for moisture. All (100%) the samples were contaminated with aflatoxin. Contamination was highest in<em> Irvingia gabonensis</em> (63.40 ± 1.79 µg/kg) and least in <em>Zea mays</em> (3.20 ± 0.12 µg/kg) (p < 0.05). Except for <em>Irvingia gabonensis</em> and <em>Colocynthis citrullus</em>, total aflatoxin was within safe intake level of the Nigerian regulatory authority (National Agency for Food and Drug Adminstration and Control {NAFDAC}). All four aflatoxin types occurred in <em>Irvingia gabonensis</em>, <em>Capsicum frutescens</em> and <em>Colocynthis citrullus</em>; none was detected in <em>Arachis hypogea</em>. AFB<sub>1</sub> contamination was highest in<em> Irvingia gabonensis</em> (11.71±0.10 µg/kg) followed by <em>Capsicum frutescens</em> (1.21 ± 0.01 µg/kg); AFB<sub>2</sub> ranged from 0.00 ± 0.00-2.43 ± 0.05 µg/kg, AFG<sub>1 </sub>0.00 ± 0.00-3.73 ± 0.04 µg/kg, and AFG<sub>2</sub> 0.00 ± 0.00-0.54 ± 0.01 µg/kg (p < 0.05). Only<em> Irvingia gabonensis</em> exceeded the limit of AFB<sub>1</sub> specified by NAFDAC for human foods. Moisture content varied widely (3.23 ± 0.03%-10.37 ± 0.19%).<strong> </strong>The trend in the occurrence of aflatoxins in the food samples was directly proportional (r = 0.91) to their moisture contents. Food<strong> </strong>commodities sold in Calabar carry potential health hazard. Improved handling through food processing, preservation and storage can minimize aflatoxins in foodstuffs and ensure sustainable quality of food supply.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 science0.0010.000
Research integrity0.0000.001
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 head0.167
GPT teacher head0.339
Teacher spread0.172 · 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 designObservational
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

Citations12
Published2015
Admission routes1
Has abstractyes

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