Combined Effects of Mulch and Tillage on Soil Hydrothermal Conditions under Drip Irrigation in Hetao Irrigation District, China
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Bibliographic record
Abstract
Soil hydrothermal condition is one of the most important factors affecting crop growth in arid regions. This study aimed to investigate the effect of mulching and tillage on moisture and temperature variations in soil under drip irrigation in the arid Hetao Irrigation District, northwest China. Four treatments were included: (1) alternating ridges (40 cm wide and 20 cm high) and furrows (40 cm wide) with plots fully mulched with plastic film (RFM); (2) alternating ridges (40 cm wide and 20 cm high) and furrows (40 cm wide) with partial film mulch (only the plant rows mulched) (RPM); (3) flat tillage with plots fully mulched with plastic film (FFM); and (4) flat tillage with partial film mulch (only the plant rows mulched) (FPM). The ridge tillage and plastic film increased soil temperature and significantly conserved soil water, and thus increased the maize yield and water use efficiency (WUE). The RFM treatment had a greater effect than the RPM, FFM, and FPM treatments on the soil moisture and water storage over 0–70 cm in depth during the entire growing period in 2014 and 2015, indicating that full transparent plastic film mulch increased soil water status and promoted deep water percolation, and ridge tillage further enhanced water redistribution to deep soils. Furthermore, RFM proportionally increased soil temperature by 0.36 °C, 1.49 °C, and 1.27 °C above the temperatures under RPM, FPM, and FFM, respectively, in 2014 and by 1.19 °C, 1.62 °C, and 0.35 °C, respectively, in 2015. During the drought year of 2014, tillage influenced temperature more than mulching; however, mulching played a more important role in preserving thermal conditions than tillage during the humid year of 2015. Consequently, RFM increased the maize yield and WUE significantly. We conclude that a combined system of full plastic film mulch and ridge tillage creates beneficial soil hydrothermal conditions under drip irrigation and thus promotes the growth and performance of field crops.
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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 it