Brown Bead of Broccoli. II. Relationships of the Physiological Disorder with Nutritional and Meteorological Variables
Bibliographic record
Abstract
In order to investigate their relationships with brown bead, a data set composed of 48 variables characterizing the developmental rate, climate, and nutrients in the soil and in the tissues of heads of broccoli ( Brassica oleracea L., Italica group) was collected from 328 plots (41 experimental fields over 3 year× 4 N fertilization level× 2 blocks). The four N treatments were 85-0-0, 85-54-0, 85-54-54, and 85-54-108, the first number indicating the N level (kg·ha -1 ) applied before planting; the second, N level applied 5 weeks after planting; and the last, N level applied 7 weeks after planting. Broccoli plants were either direct-seeded (26 experimental fields) or transplanted (15 experimental fields). Whether direct-seeded or transplanted, fast-developing broccoli plants showed a lower incidence of brown bead. More particularly, heads of transplanted broccoli plants experiencing warmer temperatures had a lower brown bead incidence and severity. A regular supply of water decreased the incidence and severity of the physiological disorder in both direct-seeded and transplanted broccoli plants. Low levels of Ca and high levels of Mg and K in mature broccoli head tissues were associated with a higher incidence of brown bead. Multiple-regression models were developed to predict the percentage of broccoli heads with brown bead for direct-seeded plants ( R 2 = 0.76; n = 104), and for transplanted plants ( R 2 = 0.69; n = 44). For direct-seeded broccoli, solar radiation between the button stage (head diameter of 2.5 cm) and maturity (head diameter of 10 cm), as well as soil and tissue Mg content, were among the first variables to enter the regression models. In general, more solar radiation and less precipitation translated into more heads showing brown bead symptoms. For transplanted broccoli plants, the minimum temperature from the button stage to maturity was a key variable in the prediction of the percentage of heads with brown bead and the corresponding index of severity.
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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 | 0.001 |
| 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".