Salinity effects on perennial, warm-season (C<sub>4</sub>) grass germination adapted to the northern Great Plains
Bibliographic record
Abstract
Schmer, M. R., Xue, Q. and Hendrickson, J. R. 2012. Salinity effects on perennial, warm-season (C4) grass germination adapted to the northern Great Plains. Can. J. Plant Sci. 92: 873–881. Limited information is available on the germination of perennial C4grasses adapted to the northern Great Plains under saline conditions. Big bluestem (Andropogen gerardii Vitman), indiangrass [Sorghastrum nutans (L.) Nash], prairie cordgrass (Spartina pectinata Link), and switchgrass (Panicum virgatum L.) seeds were evaluated under non-saline and saline conditions corresponding to electric conductivity (EC) values of 0, 4, 8, 12, 16, and 20 dS m−1, respectively. Ten cultivars were evaluated to determine salinity tolerance differences among and within species. Seeds were monitored for 21 d and analyzed for final germination percentage (GP), germination rate index (GRI), corrected germination rate index (CGRI), and germination velocity (GV). Differences among species were observed for all indices tested (P<0.01). Indices showed within species variation for big bluestem, indiangrass, and switchgrass. Big bluestem had the highest germination rates under increased salinity levels while prairie cordgrass had the lowest germination rates under non-saline and saline conditions. Indiangrass showed higher seed germination than switchgrass under low EC levels (0 to 4 dS m−1) but declined at a higher rate when EC levels exceeded 16 dS m−1. Results from this study suggest grassland reestablishment from seed on variable saline soils will be dependent on both the species chosen and the specific cultivar used.
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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".