Effect of Replant Disease on Growth of Malus x domestica ‘Ligol’ Cultivated on P-series Apple Rootstocks
Bibliographic record
Abstract
The study was conducted in 2009 and repeated in 2010. Its aim was to determine the effect of replant disease on the growth vigour of Malus x domestica ‘Ligol’ grafted on P-series rootstocks (P 2, P 14, P 16, P 22, P 59, P 60, P 66, P 67 and P 68) and rootstocks M.7, M.9, M.26, MM.106, CG 16. Plant material for the study was produced by winter grafting the scions of ‘Ligol’ on the above rootstocks. In mid-April, mineral soil was collected from a field where for the previous 25 years an apple orchard had been cultivated. The soil was collected from two soil layers: the arable layer (0-20 cm) and the sub-arable layer (20-40 cm), and mixed at a ratio of 1:1 by volume. The mixed soil was divided into two parts: one part was pasteurized with steam (95°C for 30 minutes), the other part was not pasteurized. Plastic containers (5 litre) were filled with both types of soil and the grafts were planted. Each treatment involved 20 trees. Two weeks after planting, a slow-release fertilizer was added (20 g per container) and a drip irrigation system installed. The containers were placed outdoors and the trees were grown until late October when stem height and fresh weight of the root system were recorded. Regardless of the rootstock, ‘Ligol’ trees in sterilized soil grew less vigorously than the trees in ‘sick’ soil; however, those trees produced a significantly larger root system.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".