Growth, gas exchange and competitive ability of <i>Sorghum halepense</i> populations under different soil water availability
Bibliographic record
Abstract
Leguizamón, E. S., Yanniccari, M. E., Guiamet, J. J. and Acciaresi, H. A. 2011. Growth, gas exchange and competitive ability of Sorghum halepense populations under different soil water availability. Can. J. Plant Sci. 91: 1011–1025. Different studies have determined that environmental variation is a key factor determining the outcome of competition within plant communities. Considering the importance of the resource water in non-irrigated lands of Argentina, the aim was to determine the effects of water deficit on relative growth rate (RGR), root length ratio (RLR), gas exchange and competitive ability of Sorghum halepense populations collected in humid and subhumid regions of the Pampa plains. Under semi-controlled conditions, we compared plants of seven S. halepense populations subjected to three different levels of soil water availability during 3 wk: Field capacity (FC), 75% FC and drought (D). Moreover, total above-ground biomass of S. halepense and Zea mays plants growing together in competition was determined. It was found that those plants collected in humid or subhumid regions had greater RGR, gas exchange and RLR under FC and D, respectively. Zea mays achieved a higher competitive ability than S. halepense under FC, but plants collected in humid regions out-competed the crop when grown at 75% FC. Sorghum halepense plants collected in subhumid regions dominated under D. Root length ratio may have favored the maintenance of high levels of gas exchange and also high RGR, thus contributing to sustain a competitive hierarchy under soil water stress.
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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) | 0.001 | 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".