DETECTION AND DISCRIMINATION OF NUTRIENT DEFICIENCIES IN SUNFLOWER BY BLUE-GREEN AND CHLOROPHYLL-<i>A</i>FLUORESCENCE IMAGING
Why this work is in the frame
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Bibliographic record
Abstract
Fluorescence imaging was utilized to demonstrate the potential of blue-green fluorescence (BGF) and chlorophyll-a fluorescence (ChlF) to discriminate nitrogen (N), phosphorus (P), and potassium (K) deficiencies in sunflower plant showing similar growth inhibition. Only K-deficient leaves displayed significant increase of the BGF intensity. The epidermal UV-transmittance estimated by the ratio of ChlF intensities induced by UV and blue excitations (ChlFUV/ChlFBLUE) markedly decreased in both N- and P-deficient leaves but only in the latter that we observed significant decrease of the ratio of red and far-red ChlF intensities (RF/FRF) (that is inversely related to leaf chlorophyll concentration). The BGF increase in K-deficient was limited at leaf apex and margins and was spatially correlated to localized RF/FRF increases. Images analysis allows a better interpretation of the fluorescence changes by showing the spatial relationships between BGF, the ChlFUV/ChlFBLUE and the RF/FRF ratios that are indicative of physiological disturbances occurring in leaves of nutrient deficient plants.
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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