Use of dry olive-mill wastewater like organic amendment in soil for horticultural greenhouse crop
Bibliographic record
Abstract
The elimination of olive-mill wastewater (OMW) is one of the main environmental problems related to the olive oil industry of Mediterranean countries. The OMW is collected in lagoons with the aim of reducing the volume by evaporation to obtain the dry olive-mill wastewater (DOMW). To solve the problem of OMW elimination, both purification and recycling processes have been the most suitable procedure. Manure application as organic amendment of horticultural crops under greenhouse cultivation could be substituted by DOMW. This material is an unbalanced fertilizer. However, by means of fertigation the soil solution can be balanced. The experiment was carried out by growing pepper plants (Capsicum annuum L. Lamuyo var. Drago) in a polyethylene-covered greenhouse located in La Canada, Almeria, Spain. The trial included three replications of four amendment treatments:1) W without organic material, 2) DOMW dry extract of olive milk wastewater (13.1 kg m - 2 ), 3) DOMW (6.5 kg m - 2 ) + peat (4.6 kg m - 2 ) and 4) M manure (10 kg m - 2 ). Water fraction, organic material and mineral elements in amendment materials (DOMW, peat and manure) and their saturated extracts were analyzed. During the crop production irrigation water, nutrient solution and soil solution obtained by suction cups were analysed forpH, E.C., nitrate, phosphate, sulphate, chloride, potassium, calcium, magnesium and sodium. Fruit production was evaluated by quality. It was concluded that DOMW is sustainable as soil amendment for horticultural greenhouse crops without reduction in the production, and even improves the fruit size. DOMW amendment produces a moderate reduction in the soil solution pH, potassium and chloride concentrations are similar, calcium higher and sodium lower than by manure application.
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) | 0.001 | 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".