The Impact of Using Polluted Benue River and Shinko Waters on Irrigated Vegetables at Geriyo, Nigeria
Bibliographic record
Abstract
Water pollution and scarcity are identified as the major challenge affecting food production through irrigation in a sahelian region of Africa. However, the impact of using polluted water for irrigation on soil and edible crops and the associated risk from heavy metals loaded in polluted water, soil and crops on consumers remains uncertain. A typical case of this is in Yola, Adamawa State, Nigeria where high quality irrigation water is scarce. To close this gap, this PhD research studied the impact of polluted river and lake water characteristics, and heavy metal concentration levels in water, soils and irrigated vegetables. Health risk index for consumption of heavy metals in polluted vegetables were estimated on adult and children through the water – soil – plant food chain transfer pathway from two irrigation sites of Geriyo catchment area using standard methods. The result of water characteristics and heavy metals indicated significantly high level of pollutants with most of the parameters above the threshold levels set by FAO/WHO and FEPA Standards for irrigation water uses. Heavy metal concentration levels in soil across the two sites indicated significant difference in concentration of heavy metals with Shinko Lake site soil higher than River Benue site. Heavy metal concentration levels in soils of the two sites have been impacted due to accumulation of metals in water and soil, with most of the values above the international critical threshold levels set by EU, USA, Canada and UK. The calculated metal pollution index (MPI) of the two soils revealed severe contamination of soil, to severe pollution of soil with heavy metals; with potentials of effecting plant growth and ground water contamination. The evaluated heavy metal transfer factor from soil into vegetables which is a key component of metal exposure was observed to be higher due to high percentage of sand fraction and low soil pH. Vegetables showed evidence of bioaccumulation of heavy metals from both sites; with their maximum values above permissible level of heavy metals in vegetable set out by FAO/WHO (2007) standard. The evaluated food chain transfer of heavy metals via the consumption of contaminated vegetables based on determined daily intake rate of 345g/day and 232g/day for adults above 18 years of age with body weights category of 60, 50, and 40 kg; and children below 18 years of age, with body weights of 32.5, 22.5 and 12.5kg using health risk index tool (HRI) revealed that health risks of heavy metals in vegetables are due to Cu and Pb elements. For adults consumers of vegetables with body weights of 60, 50, and 40 kg; the estimated health risk index range from 1.112 - 1.114, 1.0850 – 1.3358 and 1.0630 – 1.6697 are due to ingestion of Pb and Cu in cabbage, amaranthus and tomatoes. For children with body weights category of 32.5, 22.5 and 12.5kg, estimated health risk index range of 1.1180 – 1. 3830, 1.6218 – 1.9983 and 1.0294 – 3.5969 are due to Pb and Cu in vegetables. The results indicated that children with body weights under 12.5kg are more prone to heavy metal exposure from intake of these vegetables, as their estimated health risk index are higher than other body weights of consumers. The long time toxic effect of food chain transfer and accumulation of Cu and Pb on human body organs, such as liver, kidneys, spleen and lungs to cause defects is a serious source of concern. Urgent integrated health risk management and risk education need to be taken by local authority in the area.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".