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Record W7116778157 · doi:10.71318/apom.2020.74.4.182

Budagovsky, Geneva, Pillnitz, and Malling AppleRootstocks Affect ‘Honeycrisp’ Performance Over Eight Years in the2010 NC-140 ‘Honeycrisp’ Apple Rootstock Trial

2020· article· W7116778157 on OpenAlexaboutno aff
Wesley R. Autio, Terence L. Robinson, Suzanne Blatt, D. R. F. Cochran, Poliana Francescato, Emily Hoover, Mosbah M. Kushad, Gregory Lang, Jaume Lordan, Diane Miller, Ioannis S. Minas, R. Parra Quezada, M. Stasiak, Hao Xu

Bibliographic record

VenueJournal of American Pomological Society · 2020
Typearticle
Language
FieldAgricultural and Biological Sciences
TopicPlant Physiology and Cultivation Studies
Canadian institutionsnot available
FundersUniversity of Massachusetts AmherstNational Institute of Food and AgricultureU.S. Department of Agriculture
KeywordsRootstockOrchardclone (Java method)Yield (engineering)Seed orchardTree (set theory)

Abstract

fetched live from OpenAlex

In 2010, an orchard trial of apple rootstocks was established at 12 locations in the United States, Canada, and Mexico using ‘Honeycrisp’ as the scion cultivar. Rootstocks included two named clones from the Budagovsky series (B.9, B.10), six unreleased Budagovsky clones (B.7-3-150, B.7-20-21, B.64-194, B.67-5-32, B.70-6-8, and B.71-7-22), four named Cornell-Geneva clones [Geneva ®11 (G.11), Geneva ®41 (G.41), Geneva ®202 (G.202), and Geneva ®935 (G.935)], nine unreleased (at initiation of the trial) Cornell-Geneva clones (CG.2034, CG.3001, CG.4003, CG.4004, CG.4013, CG.4214, CG.4814, CG.5087, and CG.5222), one named clone from the Pillnitz series (Supp.3), one unreleased Pillnitz clone (Pi PiAu 51-11), and three Malling clones as controls (M.9 NAKBT337, M.9 Pajam 2, and M.26 EMLA). For trees on G.41 and G.935, there were both stool-bed-produced (N) and tissue-culture-produced (TC) liners used for trees. All trees were trained as Tall Spindles. After 8 years, the greatest mortality was for trees on CG.3001 (31%), CG.4814 (24%), CG.5222 (17%), CG.2034 (16%), and G.935N (16%). Rootstocks were partitioned into size classes from sub-dwarf to large semi-dwarf. B.7-3-150, B.7-20-21, B.64-194, B.67-5-32, and B.70-6-8 resulted in large semi-dwarf trees with comparably low cumulative yield efficiency and projected cumulative yield per hectare. CG.4004, CG.5222, and PiAu 51-11 produced moderate semi-dwarf trees. The most yield efficient trees in this group were on CG.4004. Trees on CG.3001 and CG.4013 were in the small semi-dwarf category. Projected cumulative yields were statistically similar. The large dwarf category included G.41N, G.202, G.935N, G.935TC, CG.4214, CG,4814, CG.5087, M.9 Pajam 2, and M.26 EMLA. Trees on CG.4214, G.41N, G.935N, CG.5087, and G.935TC were the most yield efficient and had the highest projected per-hectare cumulative yield for their size category. Trees on B.10, G.11, G.41TC, Supp.3, and M.9 NAKBT337 were moderate dwarfs. Trees on G.11, G.41TC, and B.10 were the most yield efficient and had the highest potential yield per hectare in this size category. The small dwarf category included B.9, CG.2034, and CG.4003. These three rootstocks produced trees which were similarly yield efficient and had similar projected per-hectare yields. B.71-7-22 was classified as a sub-dwarf, and produced a tree which was only moderately yield efficient, with a low projected per-hectare yield.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.704
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.254
Teacher spread0.224 · 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 teacher head, not a consensus.

Study designObservational
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".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

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