Analysis of Adaptive Response of Maize (<i>Zea mays</i>) Varieties from DR-Congo to Water Stress
Bibliographic record
Abstract
Maize production in tropical Africa is often negatively affected by drought. The main objectives of the present study were to 1) analyze the impact of water stress on the agro-morphological performance of two varieties of Quality Protein Maize (QPM) compared to two normal maize varieties and 2) assess their adaptive response in contrasting water environments. Agro-morphological responses to water deficiency of maize (Zea mays L.) were assessed in controlled experiments using four maize varieties, two normal maize (Zm725 and Mus1) and two quality protein maize (Mudishi1 and Mudishi3) varieties. They were subjected to three water regimes (100%, 60%, 30% water retention capacity) at the beginning of the bloom stage, using a Fischer block design with four replications. Significant differences (p < 0.05) among varieties, water regimes and their interactions for plant growth and production parameters were observed. Reduction of water supply to plants caused changes in aerial and underground plant growth. Plant stem height, foliar expansion, and root system development characterizing vegetative growth showed variation in varietal response to water regimes. Mus1 (normal maize variety) was the best adapted to variations in water regimes because they developed an important root volume to adapt to the effects of water deficit while maintaining their morphological and productive characteristics.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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".