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 NSI SPAD was more affected significantly by interactions among N, SWC, and DAS (days after sowing) than were 1/NSI Dualex and NSI SPAD/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 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) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".