Using Treated Wastewater Sludge to Improve Soil and Growth characteristics of Rain-fed Wheat under Semi-Arid Conditions
Bibliographic record
Abstract
Sludge is an increasingly growing concern in Lebanon given the absence of proper treatment and disposal methods. As a solution, this two-years study proposes the valorization of sludge as an organic amendment on soil cultivated with rainfed wheat (Triticum icaversea) and itsimpact on soil properties, microbial activity, wheat yield and grain quality. Baseline characterization of sewage sludge collected from secondary treatment plant (SS) and tertiary treatment plant (TS) in Bekaa, Lebanon, showed that both sludge types can be classified as suitable for restricted agricultural use (Class B), which cannot be used on soils to grow fruits or vegetables that are eaten raw as per the Lebanese guidelines for sludge use. Post-harvest analysis of the amended soils revealed a significant enhancement in organic matter (OM), organic carbon (OC), soil moisture, wheat yield and grain quality in both seasons SS and TS amended soils compared to the control. All the tested heavy metals were much lower than the allowable limits for agricultural soils, except for zinc (Zn).  Wheat biomass and grain quality assessment revealed a significant increase of 30% in grain yield in both treated soils (SS: 74 g/m2, TS: 81 g/m2) compared to the control (46 g/m2). Notably, TS treatment exhibited the highest protein content (14.5%) and ash (1.9%) in the first season, while both SS and TS treatments showed a significant increase in grain moisture in the second season. Soil microbial analysis were not consistent in the two seasons, but showed a potential risk of total coliforms contamination with SS application in the second season. This research provides valuable insights into the positive effects of sewage sludge application on soil fertility, microbial communities, and wheat grain quality. The findings emphasize the potential benefits of sewage sludge in sustainable agriculture, underscored by numerical improvements in various parameters. Although promising soil quality improvement and yield increase were observed in this study, further research is still needed to assess the potential soil microbial contamination and heavy metal accumulation over the long term.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".