Supplemental data for: An improved understanding of phosphorus dynamics and fertility management in forage production systems
Bibliographic record
Abstract
This dataset includes the supplemental data for the Masters thesis "An improved understanding of phosphorus dynamics and fertility management in forage production systems" and consists of forage fertility and pot trial data. Forage fertility trial: Soil fertility is vital for crop yields, but forage fertility often receives less attention compared to annual cash crops. In Ontario, producers typically apply 100 lbs acre-1 of 19-19-19 (N-P-K) fertilizer to forages, though its benefits are unclear. With new forage varieties like Festulolium, Ontario's recommendations have not changed since the 1980s. A three-year field trial aimed to determine the effect of fertility on the yield, quality, and profitability of 19 forage entries available on the Ontario market. The trial included three fertility treatments: 1) no fertilizer (control), 2) one-time spring application of 19-19-19 NPK, and 3) fertilization based on OMAFRA guidelines, alongside 19 different forage entries. The OMAFRA-recommended fertilization yielded the best results consistently, with yield differences between this and other treatments growing over time. By year 3, 100 lbs of 19-19-19 did not improve yields compared to no fertilizer. Grass-legume mixtures were more cost-effective and productive than pure grass mixtures. Red clover-based mixtures initially yielded more, but alfalfa-based mixtures were more productive overall. Mixtures outperformed single species for pure grasses. Lower tissue potassium (K) levels suggest K's critical role in yield, emphasizing the need for regular soil testing. Pot trial: Phosphorus (P) fertility recommendations for agricultural systems should be re-evaluated to increase P use efficiency. Current recommendations are based on soil test P (Olsen STP) concentrations indicating plant-available inorganic P but exclude organic P which can be made available over time through biological and biochemical mineralization of soil organic matter. This study explores whether P rates should be adjusted based on soil organic carbon (SOC) a key soil health indicator that is influenced by land use history. The aim was to understand the influence of SOC and other soil properties on crop response to added P using Lolium multiflorum in soils with varying SOC concentrations and contrasting land use histories (annual cropland or pasture). A 14-week growth room experiment investigated yield and P uptake using seven distinct field soils and five P application rates. Yield was positively correlated with soil P supply rate (using anion exchange probes) but not soil test P suggesting increased P supply from organic P mineralization in high SOC soils. This research highlights the importance of various soil health indicators including soil organic carbon and role of PSR in denoting plant-available P supply.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.556 | 0.163 |
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".