Measuring Camellia Petal Color Using a Portable Color Sensor
Bibliographic record
Abstract
The color of petals of flowering plants is often determined by comparing one or more of the petals to various Royal Horticultural Society (RHS) Colour Chart cards until a color match is found. However, these cards are susceptible to fading with age and can also provide inaccurate results if lighting is not optimal. The cards also rely on the human eye to determine a match, which introduces the possibility of human error. The objectives of this study were to determine camellia (Camellia japonica L.) petal color using the RHS Colour Chart, to determine camellia petal color with the NixTM Pro color sensor (Nix Sensor Ltd., Hamilton, Ontario, Canada), and to compare these measurements using different color measuring approaches. Color measurements of camellia flower petals using the NixTM Pro color sensor were compared to published CIELAB values from the Royal Horticultural Society (RHS) Colour Chart. Forty-five petal color samples were collected from fifteen different camellia shrubs. The RHS Colour Chart was used for each of the petals, and the RHS identifications were recorded. Measurements using the NixTM Pro color sensor were compared to RHS-provided CIELAB values that corresponded with the recorded identification for each petal to determine accuracy. The NixTM Pro color sensor’s measurements were also compared to a mean of the values, multiple measurements on the same petal location, and multiple measurements on different petal locations to determine precision and variation. The Nix™ Pro color sensor’s readings were precise in petal color determination and provided more nuanced differences between petals of the same plant and plants of the same variety in each of the color categories. The RHS Colour Chart provided an accurate depiction of most petals, but it was difficult to use with petals that had wide color variation over the entire petal. The Nix™ Pro color sensor’s measurements appeared to have more variation in the b* color space. However, overall, the Nix™ Pro color sensor L*, a*, and b* values were highly correlated with the provided RHS values (p < 0.01), showing that the sensor can be used as an accurate and precise substitute for the RHS Colour Chart. The Nix™ Pro color sensor can be a useful, cost-effective tool to measure the petal color of camellia and other flowering plants and rectifies many of the problems associated with the RHS Colour Chart.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".