Water and Nitrogen Effects on Active Canopy Sensor Vegetation Indices
Bibliographic record
Abstract
Much of the previous evaluation of active crop canopy sensors for in‐season assessment of crop N status has occurred in environments without water stress. The impact of concurrent water and N stress on the use of active crop canopy sensors for in‐season N management is unknown. The objective of this study was to evaluate the performance of various spectral indices for sensing N status of corn ( Zea mays L.), where spectral variability might be confounded by water‐induced variations in crop reflectance. The study was conducted in 2009 and 2010 with experimental treatments of irrigation level (100 and 70% evapotranspiration [ET]), previous crop {corn–corn or soybean [ Glycine max (L.) Merr.]–corn} and N fertilizer rate (0, 75, 150, and 225 kg N ha −1 ). Crop canopy reflectance was measured from V11 to R4 stage using two active sensors–a two band (880 and 590 nm) and a three band (760, 720, and 670 nm). Among the indices, the vegetation index described by near infrared minus red edge divided by near infrared minus red (DATT) and Meris terrestrial chlorophyll index (MTCI) were the least affected by water stress, with good ability to differentiate N rate with both previous crops. The chlorophyll index using amber band (CI), normalized difference vegetation index using red edge band (NDVI_RE) and the normalized vegetationi using the red band (NDVI_Red) showed more variation due to water supply, and had only moderate ability to differentiate N rates.
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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) | 0.000 | 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 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".