Characterization of Water and Nitrogen Stress of Maize by Laser Induced Fluorescence
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Bibliographic record
Abstract
<p class="1Body">Water and nitrogen are essential for the optimal development of corn plants. A deficiency of these elements leads to lower crop production. Also, the health status of a plant influences the photosynthesis process. The photosynthetic diagnosis of a plant from the chlorophyll fluorescence spectrum induced by laser is non-destructive to the sample, reliable and fast method. As part of this work, we showed that it is possible to detect the nitrogen and water deficiencies of corn from the chlorophyll fluorescence ratio at 690 nm and 740 nm, when the measurements are performed before the senescence phase.</p><p class="1Body">Indeed, we found that the R fluorescence ratio increases over time, for any stress on the plant. However, R decreases with the nitrogen stress and increases with increasing water loss.</p><p class="1Body">The measures should be performed 51 Days After Planting (DAP) to detect water deficiency and the suitable date for nitrogen deficiency detection is 61 DAP.</p><p class="1Body">Before each of these dates, the plants will be considered water deficient if the fluorescence ratio R ≤ 1.34 and will be nitrogen stressed if R &gt; 1.36.</p>
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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) | 0.000 | 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 it