Evaluation of the Association and Rotation of Maize with Legumes, in Direct Sowing in the Democratic Republic of Congo
Bibliographic record
Abstract
A study was carried out to find, in the intercropping system, the combination for optimizing maize production put into the direct seeding mulch-based cropping systems (DMC).Eight varieties of maize and two legumes were put into intercropping and rotated systems respectively in first and second season, following a factorial system with four replicates.In the second season, maize was sowed on mulch from sole crops and intercrops of first season.The results showed that in the first and second seasons, maize sole crop and maize on maize + cowpea mulch were more productive (2350.19kg•ha -1 and 2974.82kg•ha -1 respectively) than maize on maize + soybean mulch.But, Mudishi 3-soya and 07SADVE variety on maize + cowpea mulch obtained the greatest benefit for the various association systems (cost/benefit ratio = 4.04 and 2.01 respectively).Maize varieties have doubled, tripled or quadrupled their yields when rotated with cowpea and soybean, and the high yields observed in this study resulted in significant benefits in increasing their ratios whether in combination or in rotation.These new agricultural production techniques could free the farmer from tillage by leaving the cover plants to ensure equivalent work (DMC).
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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 | 0.001 |
| 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) | 0.001 | 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".