Detection of Fungal Infection in Canola using Near-Infrared Hyperspectral Imaging
Bibliographic record
Abstract
Near-infrared (NIR) hyperspectral imaging was used to detect the presence of fungal infection in stored canola. Artificially fungal infected (Aspergillus glaucus group) canola was subjected to single kernel imaging every two weeks after incubation using an NIR imaging system in the wavelength range of 1000 to 1600 nm at 60 evenly distributed wavelengths. Three wavelengths 1100, 1230 and 1300 nm were identified as significant wavelengths and used in the analysis. Statistical discriminant classifiers (Linear and Quadratic) were used to classify healthy, two–, four–, six–, eight–, and ten–week fungal incubated samples. The linear and quadratic statistical classifiers gave maximum accuracy of 99% for healthy samples and 100% for fungal infected samples at later stages of infection levels and 90 to 95% for the first four weeks of A. glaucus infected samples.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".