A Model of Critical Phosphorus Concentration in the Shoot Biomass of Wheat
Bibliographic record
Abstract
Critical nutrient concentrations are required for assessing the level of crop nutrition. Our objectives were to validate an existing model of critical phosphorus concentration (Pc = 0.94 + 0.107N) in the shoot biomass (SB) of wheat (Triticum aestivum L.) and to assess the alternative approach of expressing Pc as a function of SB rather than shoot N concentration (N). We applied four rates of P fertilizer (0, 10, 20, and 30 kg P ha−1) on soils with a low to medium available P concentration at four locations in three countries (Normandin [Canada; 2010, 2011, 2012], Brandon [Canada; 2010, 2012], Ylistaro [Finland; 2010, 2011], and Beijing [China; 2012]) for a total of 8 site‐years. Shoot biomass, and N and P concentrations were measured on five dates with 1‐wk intervals from vegetative to late heading stages of development, and grain yield was measured. Increasing P fertilization did not increase grain yield at any of the 8 site‐years and had little effect on SB. Under nonlimiting P conditions achieved in most cases with no applied P, the allometric relationship between Pc and SB differed among locations, while the relationship between Pc and shoot N concentration (Pc = −0.677 + 0.221N − 0.00292N2, R2 = 0.82, P < 0.001) was independent of locations. This model of critical P concentration predicts lower Pc values than that previously reported, mostly for high shoot N concentrations. This predictive model of Pc can be used to quantify the degree of P deficiency during the wheat growing season.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".