Effects of brewery sludge on soil chemical properties, trace metal availability in soil and uptake by wheat crop, and bioaccumulation factor
Bibliographic record
Abstract
Brewery sludge is the solid residue obtained from agro-industrial processing. It is possible to utilize the waste products in an environment friendly and economical way to replace mineral fertilizer due to its sufficient macronutrients and organic carbon content. However, its use is limited due to heavy metal concentration that may contaminate crops and then the food chain. The objective of this study was to assess the suitability of brewery sludge for using to grow bread wheat ( Triticum aestivum L.) by determining the effect of brewery sludge (7 levels: 0, 3, 6, 9, 12 and 15 t ha −1 , and 1 recommended rate of NPS only) on soil chemical properties, bioaccumulation factor, and heavy metal absorption in the soil and in the bread wheat grain using a Randomized Blocks Design field experiment conducted at two sites during the 2018 cropping season. Amendment of brewery sludge at a rate of 15 t ha −1 led to substantial variations in soil chemical properties except for Mg 2+ content at both study sites. Concentrations of the studied heavy metals (except Zn in the soil) increased with increasing brewery sludge application rate in the soil and in the wheat grain. However, heavy metal uptake by wheat grain and heavy metal concentration in the soil were below the allowed limits. The bioaccumulation factor in the wheat grain was <1.0 for the studied heavy metals. The findings of the study suggest that brewery sludge at a rate of 15 t ha −1 could be recommended due to its high nourishing effect for soil and for promoting nutritional quality of wheat crop and is safe for human consumption. However, since sludge application may lead to increase in the amount of trace metals in the soil-plant system, a long-term study is recommended.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".