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Record W4323319384 · doi:10.1007/s10341-023-00842-7

The Effect of Aminoethoxyvinylglycine and Dynamic Controlled Atmosphere on the Storage of ‘Bartlett’ Pear

2023· article· en· W4323319384 on OpenAlexafffund
A. Harrison Wright, Robert K. Prange

Bibliographic record

VenueErwerbs-Obstbau · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPostharvest Quality and Shelf Life Management
Canadian institutionsUniversity of GuelphNova Scotia Department of AgricultureAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsPEARPreharvestPyrus communisHorticultureSofteningAcetaldehydeControlled atmosphereChemistryFleshCold storageBotanyPostharvestBiologyEthanolMathematics

Abstract

fetched live from OpenAlex

Abstract Storage trials of 4 and 8 months’ duration, using ‘Bartlett’ pear ( Pyrus communis ) fruit treated with and without aminoethoxyvinylglycine (AVG) and stored using ultra low oxygen (ULO) storage (1.5 kPa O 2 ) versus dynamic controlled atmosphere (DCA) (≈ 0.6–0.7 kPa O 2 ) based on chlorophyll fluorescence were conducted over 2 years. AVG applied preharvest and DCA storage produced pears with significantly lower respiration, ethylene, acetaldehyde, ethyl acetate and ethanol post-storage compared to the other treatment combinations. Lower volatiles reflected a higher level of fruit quality. AVG + DCA also exhibited greater green color and firmness retention than the other treatment combinations. There were few disorders in both years of study, with no correlation with field and storage treatments, with the exception of pear scuffing, which was only present in year 2. The incidence of scuffing was positively associated with both fruit softening and yellowing, with DCA + AVG showing the lowest incidence (10%) and ULO + control, the highest (65%). Softening occurred during the shelf life period, as required, and was not an issue for any treatment combination. However, uneven degreening was a concern for fruit treated with DCA + AVG (mainly when firmness at harvest was > 85 N). Future research on higher maturity levels at harvest or reduced AVG rates could address this concern.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.830
Threshold uncertainty score0.220

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.011
GPT teacher head0.232
Teacher spread0.221 · 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 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

Citations3
Published2023
Admission routes2
Has abstractyes

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