PHYSIOLOGICAL AND BIOCHEMICAL PARAMETERS OF SOYBEAN GENOTYPES UNDER DIVERSE WATER REGIMES
Bibliographic record
Abstract
This study pursued tests on 17 local and exotic soybean (Glycine max L. Merr.) cultivars with two different water regimes. In the optimal irrigated condition (control), the soybean plants gained five times irrigation in the scheme of 1:3:1 during the vegetation period, with the total volume of water used for that irrigation being 5000–5500 m3 /ha. For the water deficit condition, irrigation was only three times on the scheme 1:1:1, using a total volume of water at 3000–3500 m3 /ha. In the optimal irrigated condition, water provision was only once during the formation of soybean leaves, three times during the budding period, and once again at the beginning of the blooming period. In that condition, the provision of an artificially created water deficit condition and drought with one irrigation ensued at the beginning of the blossoming period. According to the results, chlorophyll "b" pigment was more sensitive to water deficit conditions than chlorophyll "a.” The increase in chlorophyll "b" under drought conditions increased chlorophyll’s protection function, the primary photosynthetic pigment, with its reception of photons from sunlight. Stress enzyme activity increased to different extents compared with optimal water supply conditions in the soybean cultivars under water deficit conditions. The number of chloroplast pigments in plant leaves and the activity of peroxidase, catalase, and superoxide dismutase enzymes in leaves strongly influenced local and exotic soybean genotypes during the blooming-harvest period under drought conditions. With water deficit conditions, the number of pods per plant and 1000-grain weight reduced from 8.6% to 63.7% and 1.7% to 12.8% in the local and 3.8% to 28.3% and 5.6% to 58.8% in exotic soybean cultivars compared with water optimal conditions.
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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".