Analysis of Leaf Area Index Dynamic and Grain Yield Components of Intercropped Wheat and Maize under Straw Mulch Combined with Reduced Tillage in Arid Environments
Bibliographic record
Abstract
Knowledge on effect of yield formation under straw combined with plastic film mulch is important in highlighting the importance of cultivating high-efficient and high-yield crops in the arid environments. In this study, we developed a ‘double-mulching’ system, i.e., plastic film coupled with straw mulch, integrated together with intensified strip intercropping. We determined (i) the responses of leaf area index improvement to the integrated double mulching system, and (ii) Its effects on yield formation process and mechanism of intercropped wheat and maize under the integrated systems. Experiments were carried out in northwest China in 2009 to 2011. Results showed that wheat-maize strip intercropping in combination with plastic film and straw covering on the soil surface (i.e., NTS) increased maize yield by 27 to 42% compared to conventional monoculture maize, and increased wheat yield by 149 to 160% compared to conventional monoculture wheat. The crops on NTS had higher harvest index of maize, an increase of 8.2 to 21.6% than that of conventional monoculture maize. NTS system increased spike number (i.e., SN) by an average of 30.4%, increased kernel number per spike (i.e., KNS) by an average of 10.8%, and increased thousand-kernel weight (i.e., TKW) by an average of 7.0% of intercropped wheat in comparison with conventional monoculture wheat. Similarly, there was an average increase of 5.7% of SN, 23.8% of KNS, and 7.5% of TKW under intercropped maize in comparison with conventional monoculture maize. Moreover, the treatment on NTS had greater leaf area index (i.e., LAI) an average increase of 64.1% than that in conventional monoculture maize. Similarly, LAI had an average increase of 29.3% than conventional monoculture wheat. Path analysis exhibited that straw mulching combined with reduced tillage increased the grain yield of intercropped wheat by improving KNS, and increased the grain yield of intercropped maize by improving SN. We conclude that the intercropping system in combination with plastic film and straw mulching can be an effective system for boosting crop productivity via improving yield components and LAI under limited resources in arid enviroments.
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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) | 0.000 | 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 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".