Some 'high sugar grasses' don't like it hot
Bibliographic record
Abstract
Cultivars of Lolium perenne with high concentrations of water soluble carbohydrates (WSC) are seen as desirable for the reduction of nitrogen losses and greenhouse gases (notably N2O) produced from grazing by livestock, as well as offering some opportunities for increasing meat and milk production. These benefits have been shown consistently in the UK, but here we report a series of investigations which suggest the high sugar grass (HSG) trait may not be so consistently or readily expressed in field conditions in New Zealand. First, the cultivars AberDart (HSG) and Fennema (control) were grown in paddocks in the Manawatu (Aorangi) and studied from July 2001 to October 2002. Total WSC levels in the harvestable component (leaf snips) increased during spring in both cultivars, but the differences between the HSG and control were smaller than seen in the UK and were only marginally significant (P = 0.063). Likewise, no consistent differences in WSC in leaf blades were found in a second trial, grown this time in pots outdoors, where water and nutrients were more controlled. This second trial included not just AberDart, but the original HSG, AberDove, which had been the focus of many successful trials in the UK. An analysis of the environmental factors that might be relevant to the expression of the quality trait 'high sugar', and of possible differences between UK and NZ climates and trials, led us to a third series of experiments, conducted in NZ, in controlled environment chambers. Total WSC became substantially greater (> 2fold) in all three cultivars when grown at 10oC (day and night) than at 20oC but only at 10 oC did one HSG, AberDove, show a small, but significantly greater WSC, than Fennema (P < 0.05). However, significantly higher levels of WSC (P < 0.05) were expressed in leaf blades of both AberDart and AberDove, compared to Fennema, when grown at temperatures of 20oC day / 10oC night (14h day), and especially (68% and 46% respectively) when this followed a period of cold (10 weeks at 5oC) and short days. Our findings suggest that low temperatures, either low night temperatures, or previous periods of sustained cold (
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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".