The Ionomics of Lettuce Infected by Xanthomonas campestris pv. vitians
Bibliographic record
Abstract
Bacterial leaf spot (BLS) caused by Xanthomonas campestris pv. vitians (Xcv) places a major constraint on lettuce production worldwide. The most sustainable strategy known to date for controlling BLS is the use of resistant cultivars. The nutrient elemental signature (ionome) of ten lettuce cultivars with three levels of resistance was analyzed by inductively coupled plasma optical emission spectroscopy (ICP-OES) to determine which nutrient balances are linked to resistance to BLS, and to assess the effect of Xcv infection on the ionome. The elemental concentrations were preprocessed with isometric log-ratios to define nutrient balances. Using this approach, 4 out of 11 univariate nutrient balances were found to significantly influence the resistance of lettuce cultivars to BLS (P < 0.05). These significant balances were the overall nutritional status balancing all measured nutrients with their complementary in the dry mass, as well as balances [Mn | Zn, Cu], [Zn | Cu] and [S, N | P]. Moreover, the infection of lettuce cultivars mostly affected the lettuce ionome on the [N,S | P] balance, where infection tended to lean its balance toward the N, S part relatively to P. This study shows that nutrient uptake in lettuce can be affected by BLS infection, and that nutrient status influences resistance to BLS infection.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".