Impacts of Irrigation with Reclaimed Wastewater on Forages Production, Nutrients, and Heavy Metals Content
Bibliographic record
Abstract
In order to investigate the effect of reclaimed wastewater (RWW) on soil chemical properties and heavy metal uptake of selected forages, an experiment was carried out at Dhaid Research Station, UAE during three growing seasons (2014-2016). Alfalfa, Rhodes and Buffel grass were irrigated by RWW and grown in a randomized complete block design with four replications. Composite soil samples were collected from the experimental site before starting the study and every six months from planting date to test the macro and heavy elements concentration in soil and forages tissues. Chemical analysis for soil, crops and wastewater were analyzed. RWW irrigation has significantly increased the soil salinity (1 to 8 dSm-1) in 2014 but soon these values were declined in 2015 and 2016 growing seasons due to the enhanced irrigation water quality and the use of good water management.Results revealed that UAE (Sharjah) domestic RWW is suitable to be reused for irrigate forages as its quality match international standards for RWW irrigation except its Na and Cl content. The results of the plants tissues analysis during 2014 season indicated a rise in the nutrients concentration, particularly nitrogen, potash, iron and boron, compared with the critical limits. While, the results have also shown a significant increase of zinc (Zn) and copper (Cu), especially in Buffel grass and Alfalfa tissues during the third season (2016) which exceeded the critical limits.The highest mean yearly dry weight yield during the study period were recorded for Buffel grass (50.5 ton ha-1) followed by Rhodes (44.5 ton ha-1) and Alfalfa (11.1 ton ha-1). It can be concluded that regular monitoring of recycled wastewater, soil and appropriate management are needed to mitigate the negative impacts of sodium and salts accumulations.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".