Evaluation of Different Maturity Groups of Soybean (Glycine Max L. Merrill) Grown Sole and Intercropped with Maize (Zea Mays L.) for Yield and Yield Components at Bako, Ethiopia
Bibliographic record
Abstract
Different maturity of soybean genotypes interact differently either in sole or intercropping system. Therefore, screening of the genotypes under various environment is paramount important for variety recommendation. The experiment was conducted to evaluate different soybean genotypes in intercropping and sole cropping systems. Fifteen genotypes were evaluated in using randomized complete block design with three replications. The result revealed nodule number and plant height was significantly affected by genotypes variation in both systems. A total of 32-73% reduction in nodule number was recorded when compared with soles due to shading of maize. However, late and early types had higher number of nodules as opposed to medium type. Late type was generally taller than early and medium ones. Significant differences in grain yield were also recorded in both systems. But maize shading effect considerably reduced the yield though population difference is also another factor. Promoveria (3826 kg ha-1), IAW-13-1(3747 kg ha-1) and Pr-145-2-1 (3620 kg ha-1) genotypes resulted the highest grain yield and productivity, while the lowest yield was obtained from Pr-145-2 (2144 kg ha-1) when grown in soles. However, IAW-13-1 (690 kg ha-1) and AGX-129-2 (672 kg ha-1) produced the highest grain yield in intercropping systems. Comparing each maturity groups, significant variation both in nodule number and grain yield was also recorded. As general, most of the tested genotypes that were performed well in intercropping were not so far released. AGS-129-2 genotype was released recently in sole cropping systems, but now it is also well performed in intercropping systems. For unreleased pipelines it is important to consider as variety verification trial to confidently recommend for the end users.
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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".