The Effect of Salinity and Irrigation Regimes on the Level of Fatty Acids in Olive Flesh Oil
Bibliographic record
Abstract
<p>Olive trees have the capability of growing under semi-arid regions, where drought and salinity are the major concerns. Two years field experiments were carried out to investigate the interaction effects of natural saline well water and irrigation levels on the quantity and quality of fatty acids in the olive flesh fruits (“Roghani” cultivar). A factorial layout within a randomized complete blocks design with three replications of five irrigation levels (I<sub>1</sub> to I<sub>5</sub> as 0.25, 0.5, 0.75, 1 and 1.25 ET<sub>c</sub>) and three saline water levels (S<sub>1</sub> to S<sub>3</sub> as 100%WW, 50%WW+50%FW and 100%FW) were considered. The fresh and brackish irrigation water were withdrawn from two different natural wells (fresh water (FW) and saline water wells (WW)). <em>Results revealed that <strong>increasing salinity and decreasing irrigation water levels caused significant increment in the ratio of unsaturated fatty acids, palmitic acid to the percentage of oil and oil percentage in olive flesh fruit</strong></em>. It is found that as water<em> </em>salinity increased from lowest to the highest level, the oleic acid trends to its highest value of 23.68% in I<sub>1</sub>S<sub>1</sub>. Mean values of palmitic acid in 2013 were 27.52% and decreased to 19% in 2014. <em>It is concluded that highest percentage of oleic, linoleic, linolenic and palmitic acids obtained under high saline and less applied irrigation treatment (S<sub>1</sub>I<sub>2</sub>) yielding to improve the olive oil quality.</em></p>
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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 | 0.002 | 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 | 0.000 |
| 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".