Comparative Evaluation of Water Deficit Tolerance Capacity of Extra-early and Early Maize Genotypes under Controlled Conditions
Bibliographic record
Abstract
Maize is an important staple food crop in Tropical Africa including Nigeria. However, the production of the crop is constrained by inadequate soil moisture resulting from erratic rainfall distribution. There is therefore the need to breed and select for drought tolerant genotypes for production especially in the southern Guinea savannah ecology responsible for over 60% of maize production in Nigeria. Controlled experiments using potted plants were therefore conducted during the dry periods between November 2007 and April 2008. The study evaluated moisture deficit tolerance capacity of two maize maturity groups, consisting of 15 extra-early and 12 early genotypes along with two local checks, subjected to two moisture levels 25% (stressed) and 100% (unstressed) soil available moisture) determined gravimetrically. Crop establishment parameters (% germination and mean germination time (MGT), morphological growth parameters (number and area of leaves, plant height, flowering characteristics), physiological growth indices (leaf area index, crop growth rate, relative growth rate, net assimilation rate and leaf area ratio) were measured during growth. Yield components (harvest index, shelling percentage and number of kernels per cob) and grain yield were determined at harvest. The data were analyzed using the general model of ANOVA and significant means were separated by the Least Significance Difference (LSD) at 5% probability level. The results showed that there were no appreciable differences between the two maturity groups for most measured parameters. However, across the two groups, crop establishment parameters, morpho-physiological growth parameters, yield components and grain yield were significantly reduced by soil moisture deficit, while flowering characteristics were significantly delayed by soil moisture stress with significant variable genotypic responses. Grain yield reduction due to water stress was significantly related to drought susceptibility index (DSI) of the genotypes in the two maturity groups. Conclusively, whereas extra-early genotypes showed good yield potentials but poor drought tolerance which suggested poor yield stability and therefore may not be suitable for the southern Guinea savanna (SGS) ecology in the event of severe stress. However, early genotypes, though showed lower yield potential, had good yield stability and hence are promising genotypes for the SGS ecology.
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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 | 0.000 |
| 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".