Effects of Different Planting Patterns on the Growth and Yield of Maize and Soybean in Northwest China
Bibliographic record
Abstract
Aboveground and belowground interactions are crucial in the over-yielding of intercropping systems. However, the relative effects of aboveground and belowground interactions on yields in maize (Zea mays L.) and soybean (Glycine max) intercropping systems are still unclear. Field experiments, including measurements of plant height, soil-plant analysis development (SPAD) value, photosynthetically active radiation (PAR), root length density (RLD), root volume density (RVD), and grain yield, were conducted in 2018-2019 to analyze the advantages and effects of above-ground and belowground inter-species interactions. This study adopted three different planting patterns: mono-cropping maize (MM), mono-cropping soybeans (MS), and maize-soybean intercropping (IM and IS). This study showed that intercropping promotes the growth of maize and makes maize have a better photosynthetic environment, while the growth of intercropping soybeans is inhibited and the photosynthetic environment becomes worse. In the upper layer (0-40 cm) and close to the plants, the root growth and distribution of intercropped maize increased, resulting in greater root length density and volume density, while the root growth and distribution of intercropped soybean decreased, resulting in lower root length density and volume density. The intercropping increased the maize yield by 18.52-19.8%, and reduced the soybean yield by 55.87-57.44%. The results indicated that intercropping improves the competitiveness of maize and reduces the competitiveness of soybeans. The increase in maize yield made up for the loss of soybean yield and led to an overall significant advantage in the maize-soybean intercropping system.
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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".