A Corn Nitrogen Status Indicator Less Affected by Soil Water Content
Bibliographic record
Abstract
The SPAD‐502 chlorophyll (Chl) meter and the Dualex device can estimate crop N status based on the measurement of leaf Chl concentration and polyphenolics (Phen) concentration, respectively. However, soil water status may confound such assessment of N status. This study compared the sensitivity of SPAD, Dualex, and SPAD/Dualex ratio as indicators for assessing corn (Zea mays L.) N status and the influence of soil water content (SWC) on the indicators in their absolute and nitrogen sufficiency index (NSI) expression. A greenhouse trial was conducted with five N fertilizer application rates (0, 50, 50+75, 50+150, and 200 kg N ha−1) and three SWC levels (high, medium, and low). A field trial also was performed with six N rates (0, 20+40, 20+80, 20+120, 20+160, and 250 kg N ha−1) and spatially variable SWC as a covariate. The responses of SPAD, Dualex, SPAD/Dualex ratio (and their corresponding NSI) to N rates and SWC levels were compared. The results showed that SPAD, Dualex, and SPAD/Dualex ratio were all influenced significantly by N rates and by SWC levels. When expressed as NSI, however, the parameters' relationships with N were essentially decoupled from SWC. The NSISPAD was more affected significantly by interactions among N, SWC, and DAS (days after sowing) than were 1/NSIDualex and NSISPAD/Dualex. The latter showed a greater sensitivity to N fertility levels than the other indicators, resulting in a better discrimination of N treatments and under variable SWC conditions in the two trials.
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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 | 0.001 |
| 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 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".