Effects of watertable depth, irrigation water salinity, and fertilizer application on root zone salt buildup
Bibliographic record
Abstract
Patel, R.M., Prasher, S.D. and Bonnell, R.B. 2000. Effects of watertable depth, irrigation water salinity, and fertilizer application on root zone salt buildup. Can. Agric. Eng. 42: 111-115. Salt buildup due to irrigation water salinity and fertilizer application was studied in field Iysimeters planted with green peppers (Capsicum annuum).Waterwas applied by subirrigation, and the fertilizers were incorporated at the soil surface. Three subirrigation water salinities, I, 5, and 9 dS/m and two watertable depths, 0.4 and 0.8 m, were used. The soil salinity was determined by first measuring the bulk soil salinity by time domain reflectometry (TDR) and then converting it to soil solution salinity (ECsw)' It was found that the salinity of the subirrigation water affected ECsw in the upper soil profile when the watertable was maintained at 0.4 m depth. The subirrigation water also affected the lower half of the soil profile when the watertable was maintained at 0.8 m depth; however, it did not affect any salt buildup in the upper half. Also, the addition of N, P, and K fertilizers did not contribute to the salt buildup in the soil. Although watertable depth and subirrigation water salinity affected ECsw' they did not affect the green pepper yield. The experiment was conducted using field Iysimeters filled with a sandy soil and covered with a plastic sheet to simulate arid conditions. Therefore, caution should be exercised in extrapolating the results of this study to field conditions and other soils. L'accumulation de sel dans Ie sol due a l'irrigation avec de l'eau saline et aI'utilisation de fertilisants, a ete etudie au champs dans des Iysimetres OU ont ete semes des plants de piment vert (Capsicum annuum). Un systeme d'irrigation souterraine a ete utilize, et les fertilisants ont ete incorpores ala surface du sol. Nous avons teste trois
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 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 | 0.000 |
| 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 | 0.001 |
| 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 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".