Short communication: Tolerance of Vineland apple rootstocks to waterlogging and <i>Phytophthora</i> infestation
Bibliographic record
Abstract
Hampson, C. R., Randall, P. and Sholberg, P. 2012. Short communication:Tolerance of Vineland apple rootstocks to waterlogging and Phytophthora infestation. Can. J. Plant Sci. 92: 267–269. The Vineland (V) apple (Malus) rootstock series has displayed a range of dwarfing potential and fire blight resistance in research test plots. Knowledge of their resistance to crown and root rot, incited by Phytophthora spp., is desirable before recommending them for on-farm testing, but information on this subject is lacking. Therefore, we tested the response of V.1, V.2, V.3 and V.4 clonal rootstocks to Phytophthora (P. cactorum and P. cryptogea) and waterlogging (0, 24 or 48 h per week for 4 mo) in a factorial greenhouse experiment on potted plants, using M.9 (moderately resistant to Phytophthora) and MM.106 (susceptible) as standards for comparison. Root fresh weight was reduced equally by both pathogens relative to uninoculated controls; rootstocks differed in their response to flooding but not to pathogen treatment. Shoot fresh weight was depressed by flooding in a rootstock- and pathogen-dependent manner. In general, all four V rootstocks had better root and shoot growth than MM.106 in the flooding treatments, and all grew as well as, or better than M.9.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".