Biomass Production by Warm‐Season Grasses as Affected by Nitrogen Application in Ontario
Bibliographic record
Abstract
There is little information on the production levels of prairie C 4 perennial grasses in the biomass context in eastern Canada. The objective of this study is to evaluate the effect of species/cultivar entries and N fertilizer application on biomass production of prairie perennial biomass grasses. Two switchgrass ( Panicum virgatum L.) cultivars, two big bluestem ( Andropogon gerardii Vit.) cultivars and one indiangrass ( Sorghastrum nutans Nash.) cultivar were seeded in 2009 in eastern Ontario to evaluate their biomass production potential. The crops were seeded in a silt loam soil at 1000 pure live seeds m −2 . No fertilizer was added in 2009 or 2010. In 2011 and 2012 treatment N50 received 50 kg N ha −1 while treatment N0 was kept as an unfertilized control. The crop biomass production, canopy height, leaf SPAD absorbance, leaf area index, and harvest moisture content were determined. Switchgrass production exceeded big bluestem and indiangrass, especially in the first 2 yr after establishment. Despite the drought, dry matter production for the different entries in 2012 ranged between 5.07 and 8.13 Mg ha −1 . Biomass production was improved by N application only for big bluestem and indiangrass but not for switchgrass. However, N application increased leaf SPAD absorbance and leaf area index for all entries. Moisture content at harvest was species dependent. Our results suggest that switchgrass might need lower N levels than big bluestem and indiangrass. With the stands reaching their peak production, this study shows the high production potential for some of these grasses under Ontario 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".