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Record W4387396984 · doi:10.1139/cjps-2023-0007

Variability of index of absorbance difference (<i>I</i><sub>AD</sub>) to indicate fruit maturity at harvest for major apple cultivars in Ontario

2023· article· en· W4387396984 on OpenAlexafffundvenueabout
Younes Mostofi, Jennifer R. DeEll

Bibliographic record

VenueCanadian Journal of Plant Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Physiology and Cultivation Studies
Canadian institutionsMinistry of Agriculture, Food and Rural Affairs
FundersAgriculture and Agri-Food Canada
KeywordsCultivarStarchHorticultureMaturity (psychological)BiologySignificant differenceBotanyMathematicsFood scienceStatistics

Abstract

fetched live from OpenAlex

The overall objective of this study was to evaluate the index of absorbance difference ( IAD) of four major apple cultivars in Ontario (‘Honeycrisp’, ‘Ambrosia’, ‘Gala’, and ‘McIntosh’) during the harvest window over multiple seasons (≥4 years), as well as its relationship with fruit firmness, internal ethylene concentration, and starch index values. IAD values differed among the four cultivars, with ‘McIntosh’ having the highest IAD (1.03–1.33) overall and ‘Gala’ having the lowest (0.19–0.56). Principal component analysis showed that the cultivars were separated into distinct groups. ‘Honeycrisp’ was clustered with starch and ethylene, while ‘Gala’ and ‘McIntosh’ were mainly clustered with firmness and IAD, respectively. Variable correlations between IAD and other maturity indices were found over the years. The negative relationship between IAD and ethylene for ‘Gala’ showed variability with R2 ranging from 0.008 in 2012 to 0.47 in 2018. The correlation between IAD and starch for ‘Gala’ was very strong ( rs = −0.82****) in 2018, whereas it was not significant in any year for ‘McIntosh’. Overall, IAD may relate to harvest maturity, but it did not correlate closely or consistently with other maturity indices, varied greatly year to year, and was cultivar dependent. IAD measures are not consistently related to fruit maturity every year, making reliability difficult to attain.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.390

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.214
Teacher spread0.187 · 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 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 routes4
Has abstractyes

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