Evaluation of Canopy Reflectance Technology Using a Delta Yield Approach
Bibliographic record
Abstract
Canopy reflectance measurements have been proposed as a method to variably apply N to corn ( Zea mays L.). This study was conducted to determine if normalized difference vegetation index (NDVI) is correlated with corn N response spatially across a field. Whereas most studies use fertilizer N strips to impose N response variation, the current study assesses ability of NDVI to predict N response against naturally occurring soil N levels. The experiment was conducted on commercial corn fields in southern Ontario, Canada in 2006 and 2007. A GreenSeeker System (NTech Industries, Inc., Ukiah, CA) was used to measure NDVI at the 6 to 7, 8, 10, and 11 to 12 leaf stages on 9 by 4.5 m subplots of two treatments receiving 0 and 30 kg N ha −1 starter, respectively. Delta yield estimates that spatially corresponded with NDVI subplot measurements were determined by bordering each subplot plot with a nonlimiting N rate subplot and a zero N rate subplot and measuring differences in yield. Corn response to N fertilizer, as measured by delta yield, was highly variable spatially across each field in both years. Delta yield values ranged between 100 and 7200 kg grain ha −1 in 2006, and −2300 and 5000 kg grain ha −1 in 2007. Similarly NDVI varied spatially with coefficient of variations ranging from 6 to 16% depending on leaf stage and year. Correlations between NDVI measurements and delta yield were not significant at any leaf stage. The relationship between N response and NDVI may be determined by factors other than N or by N mineralization occurring beyond the 11 to 12 leaf stage.
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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 | 0.001 | 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 teacher head, 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".