Effects of different drip irrigation regimes on saline–sodic soil nutrients and cotton yield in an arid region of Northwest China
Bibliographic record
Abstract
A field experiment was conducted on a saline wasteland in Xinjiang, Northwest China, during 2008–2010 to evaluate the nutrient behavior and cotton yield during reclamation, applied by different drip irrigation regimes. The experiment included five treatments in which the soil matric potential (SMP) thresholds at 20 cm depth were controlled at −5, −10, −15, −20 and −25 kPa. The results indicated that both soil salinity and sodicity declined significantly at 0–40 cm depth and greater reductions were achieved at higher SMP thresholds (−5 and −10 kPa) than in other treatments. The distributions in soil inorganic nitrogen (N) and available phosphorus (P) and potassium (K) in the soil profile were mainly influenced by the point-source characteristic of drip irrigation , drip irrigation regime and fertilization mode. With the reclamation of both soil chemical and physical properties, there were dramatic increases in soil N, P and K concentration by the end of 2010. The soil nutrient concentrations in N, P and K were all proportional to the SMP thresholds, as higher SMP could result in greater reductions in soil salinity and sodicity. Since crop growth became more vigorous during reclamation, there was also a considerable increase (9.7–31.9%) in soil organic carbon by the end of 2010, and the concentrations were also proportional to SMP thresholds. The highest cotton yield was obtained in S1 (−5 kPa) treatment for both 2009 (2.87 Mg ha −1 ) and 2010 (3.60 Mg ha −1 ). Additionally, the soil C:N ratios were inversely proportional to the SMP thresholds in 2009 and 2010. Considering the soil reclamation efficiency, soil nutrient stocks and cotton yield, SMP thresholds of −5 and −10 kPa could be used as effective measures to trigger irrigation in the first 3 years of saline–sodic soil reclamation in Xinjiang, Northwest China.
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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 | 0.000 |
| 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".