Cold Temperature Tolerance of Trunk and Root Tissues in One- or Two-year-old Apple Rootstocks
Bibliographic record
Abstract
Winter injury to the root systems of fruit trees can cause significant tree losses and yield reductions in the northern regions of the United States and Canada. To compare the root and trunk cold temperature tolerance, a series of experiments were conducted using ungrafted apple rootstocks. ‘Geneva® 11’ (G.11), ‘Geneva® 30’ (G.30), ‘Geneva® 41’ (G.41), ‘P.2’, and ‘Budagovsky 9’ (B.9) apple ( Malus × domestica Borkh.) rootstocks had root tissue hardiness similar to ‘M.26’, but ‘Geneva® 935’ (G.935) had greater cold-hardiness than M.26 when based on shoot regrowth in ungrafted trees. The LT 50 of M.26 and P.2 roots ranged from –12 to –14 °C. The LT 50 was –13 °C for B.9, –13.4 to –14.6 °C for G.30, and –12 °C for G.11. The LT 50 of G.41 was one of the highest in one experiment, –8 °C, and one of the lowest in another, colder than –15.0 °C. The LT 50 of G.935 roots was the lowest and ranged from –16 to –19 °C. Compared with M.26, trunk cold-hardiness in December was greater in B.9 and P.2 and was similar in G.30. Cold-hardiness of G.11 in December was mixed with less injury in the xylem but more injury in the phloem compared with M.26. In October, M.26 and G.935 trunks had little injury after exposure to –24 °C.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".