Consumers and farmer awareness and perception of heavy metal contamination in rice: Implications for food safety and sustainability
Bibliographic record
Abstract
Abstract Despite the growing concern for food safety and environmental conservation, empirical studies on public awareness and perception concerning heavy metal poisoning are limited. This study examines the awareness, perceptions, and factors influencing awareness of heavy metal contamination in rice ( Oryza sativa L.) among farmers and consumers in Ghana. Using data collected by multistage sampling from 275 rice farmers and 185 consumers in three municipalities in the Ashanti Region of Ghana, the study employed perception indices and ordered logit regression models in the analyses. Results indicate significant demographic differences between farmers and consumers, with low and moderate awareness of heavy metal contamination issues among farmers and consumers, respectively. Both groups expressed strong concern about the existence of heavy metals in agrochemicals, including bioaccumulation, long‐term health risks, and environmental pollution. Factors influencing awareness levels for farmers included age, education, credit access, participation in farmer‐based organizations, rice consumption frequency, extent of agrochemical usage, and training in handling agrochemicals. For the consumers, major factors influencing awareness levels were age, education, rice preference, consumption frequency, and household size. The study recommends the implementation of comprehensive educational programs, enhancing access to resources for farmers, strengthening regulatory frameworks, and promoting sustainable agricultural practices to address the challenges of heavy metal contamination in rice production and consumption. These findings provide valuable insights for policymakers and stakeholders to improve food safety and sustainability in the rice sector in sub‐Saharan Africa.
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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 | 0.000 | 0.000 |
| 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".