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Record W2892156719 · doi:10.1139/cjps-2018-0193

Postharvest quality implications of preharvest treatments applied to enhance Ambrosia™ apple red blush colour at harvest

2018· article· en· W2892156719 on OpenAlexafffundvenue
P.M.A. Toivonen, Changwen Lu, Jared Stoochnoff

Bibliographic record

VenueCanadian Journal of Plant Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPostharvest Quality and Shelf Life Management
Canadian institutionsAgriculture and Agri-Food Canada
FundersMinistry of Agriculture, Food and Rural AffairsAgriculture and Agri-Food CanadaOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsPreharvestHorticulturePostharvestAgronomyPhosphorusEnvironmental scienceBiologyChemistry

Abstract

fetched live from OpenAlex

Two approaches for enhancing red blush in Ambrosia™ apple were evaluated: (i) reflective row covers or (ii) application of foliar phosphorus-rich sprays, both applied several weeks before anticipated harvest. Two experiments were conducted, the first to evaluate a white reflective row cover versus foliar phosphorus spray, and the second to evaluate two types of reflective row cover, one made of a woven white polyethylene sheet and the other a solid silvered Mylar ® . The comparative effects of these preharvest treatments on at-harvest fruit quality and quality after storage were assessed in both experiments. It was determined that foliar phosphorus sprays or one of the two types of reflective row covers resulted in similar enhancement of red blush colour, with no negative effects on at-harvest quality. However, in the first experiment it was found that after 8 mo of controlled-atmosphere storage (1 kPa O 2 + 1 kPa CO 2 at 0.5 °C), apples from the phosphorus foliar spray treatment developed greasiness and sooty blotch compared with those from the reflective row cover or control treatments. In the second experiment, after 5 mo of air storage at 0.5 °C, the apples from the silvered Mylar ® reflective row cover treatment developed severe soft scald and soggy breakdown compared with the control and white reflective row cover treatments, which developed lower or very slight incidence of soft scald, respectively, and no soggy breakdown. These results indicate that when preharvest treatments are applied to apples, post-storage quality effects should be evaluated.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.924
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.284
Teacher spread0.247 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations5
Published2018
Admission routes3
Has abstractyes

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