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A study of introduced apple cultivars according to the main components of winter hardiness by simulating damaging factors under controlled conditions

2022· article· en· W4224233051 on OpenAlexaboutno aff
А М Галашева, Н. Г. Красова, Z. E. Ozherelieva

Bibliographic record

VenuePROCEEDINGS ON APPLIED BOTANY GENETICS AND BREEDING · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Physiology and Cultivation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCultivarFrost (temperature)HorticultureSowingHardiness (plants)CambiumBiologyBark (sound)CropAgronomyGeographyXylemEcology

Abstract

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Background. Most of the plantings of fruit crops in Russia are located in the zone of risky agriculture. In the European part of Russia, in winter, fruit crops are affected by the impacts of weather conditions (spring frosts, droughts, early frosts, low-temperature stress, a short growing season, and thaws). Frosts cause 98% of the damage to fruit trees.Methods. One-year-old branches were frozen in a Japanese Espec PSL-2KPH climate chamber after prehardening under –5°C and –10°C for 5 days, and damaging factors of the winter period were simulated.Results. The bioresource collection of the All-Russian Research Institute of Fruit Crop Breeding (VNIISPK) contains 730 appletree cultivars from various domestic and foreign institutions. Apple cultivars from Ukraine, Belarus, Latvia, Moldova, USA, France, Czech Republic, Sweden and Canada were analyzed for frost resistance components. The resistance of plants to early frosts of–25°C without hardening and after hardening in early winter (Component I) showed that the main tissues (bark, cambium and wood) suffered minor damage in all studied cultivars. In cv. ‘Belarusskoye Sladkoye’, the damage to the bark scored 2.3 points. Among the studied apple cultivars whose one-year-old branches were frozen at –38°C and –40°C (Component II), ‘Coremolda’ (Moldova) showed the highest frost resistance to the negative mid-January temperature of –38°C (damage to the buds and main tissues scored 0.3–1.0 points). Under–40°C (Component II), ‘Coremolda’ (Moldova) and ‘Aivaris’ (Latvian breeding) demonstrated bark, cambium and wood resistance with damages at the level of 2.0 points. These cultivars can be used in breeding programs as sources of frost resistance. Freezing of one-year-old branches under –25°C after a 3-day artificial thaw at +2°C revealed bud and tissue resistance in the American cv. ‘Red Free’ and in cv. ‘Coremolda’ (Component III).

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.033
GPT teacher head0.246
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

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Citations2
Published2022
Admission routes1
Has abstractyes

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