Effect of leaf nitrogen concentration versus CND nutritional balance on shoot density and foliage colour of an established Kentucky bluegrass (<i>Poa pratensis</i> L.) turf
Bibliographic record
Abstract
A 3-yr field study was conducted in a loam and a sand site to determine the effects of N, P, and K application rates on N status, shoot density and foliage colour of Kentucky bluegrass clippings and to derive critical N values. The experiment was arranged in a completely randomized block design with four replicates and three nutrients, N (0 or 50 to 300 kg ha-1 yr-1), P (0 or 21.8 to 87.3 kg P ha-1 yr-1), and K (0 or 41.7 to 250 kg K ha-1 yr-1), equally broadcast six times per growing season. We examined N concentration values, log-transformed N concentration values, and CND values for compositional nutrient simplexes comprising one (VN1), three (VN3), five (VN5), or 11 (VN11) macro- and micro-nutrients. Critical values for N expressions were obtained from linear relationships with targeted visual shoot density and foliage colour ratings that were closely related to each other (R2 = 0.92). The highest coefficients of determination (0.975 to 0.980) were obtained with VN5 and VN11. The VN5 values were consistent with literature data and across experimental sites, and were the most successful (99% success) in diagnosing N sufficiency in 328 qualified specimens from commercial sod farms. Compared with raw concentrations, the CND transformation reduced from 0.6 to 0.1 the degree of inter-correlation among nutrients in principal component analysis and was amenable to a χ2 distribution of CND indices. Using a critical imbalance index (CNDr2) of 5.6as χ2 value, and a critical CND IN2 index of 1.5 for a 5-nutrient simplex, we diagnosed as imbalanced 179 qualified specimens of which 110 specimens presented excessively high N level among the 328 qualified specimens in commercial stands. The proposed five-nutrient CND norms proved to be effective in diagnosing N status in Kentucky bluegrass clippings across experimental, literature, and survey data sets. Key words: Plant tissue nutrient diagnosis, DRIS, CND, Kentucky bluegrass nitrogen fertilization, turfgrass shoot density, turfgrass foliage colour
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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".