Effects of Cumin/Maize Intercropping on Crop Productivity, Interspecific Interaction and Water Use Efficiency in the Semi-arid Area of Northwest China
Bibliographic record
Abstract
In the semi-arid areas of Xinjiang in China, the agricultural community is facing long-term challenges in improving crop productivity and economic profits. A potential way to improve crop productivity is by intercropping food crops with cash crops. In this two-year field experimental study, we analyzed the advantages of the cumin/maize intercropping system as compared to cultivating them separately from three perspectives: crop growth, interspecific interactions, and water use efficiency. At the experimental site, each cropping systems (i.e., the cumin/maize intercropping system, monocropping cumin system, and monocropping maize system) had three replicates. In the experimental of 2019 and 2020, the three cropping systems showed significant differences in plant height, stem diameter, and leaf area index (LAI). The yields of the cumin/maize intercropping system were both lower than monocropping maize and cumin. However, the cumin/maize intercropping system had a higher land equivalent ratio (LER) than either of the monocropping systems, with a two-year average value of 1.65. Intercropped cumin was less dominant; as shown by aggressivity (Acm; averaging—0.22) and relative crowding coefficient (Rcm; averaging—3.15). In addition, the cumin/maize intercropping system significantly improved the Water equivalent ratio (WER) as compared to the monocropping systems, with a two-year average value of 1.67. Therefore, the cumin/maize intercropping system is a promising agricultural strategy to improve the utilization rate of agricultural resources and economic benefits in Xinjiang.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".