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Record W4327715332 · doi:10.1002/ppp3.10368

Cuticular waxes affect fruit surface color in blueberries

2023· article· en· W4327715332 on OpenAlexafffund
Yifan Yan, Michael Dossett, Simone D. Castellarin

Bibliographic record

VenuePlants People Planet · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Surface Properties and Treatments
Canadian institutionsWSP (Canada)Abbotsford Veterinary ClinicUniversity of British Columbia
FundersMitacs
KeywordsWaxPigmentBotanyHorticultureBiologyFood scienceChemistryBiochemistry

Abstract

fetched live from OpenAlex

Societal Impact Statement In blueberry, fruit color is one of the most important quality traits affecting consumers' choices. Both pigments and waxes impact fruit color; however, their roles have not been clearly elucidated. Here, the contributions of waxes and anthocyanins to fruit color are characterized. A higher content of β‐diketones—the second largest wax group in blueberries—determines a lighter fruit color; hence revealing that, at harvest, waxes contribute more than anthocyanins in determining variations in fruit color among blueberry varieties. Summary Fruit color is one of the major quality traits determining the marketability of fruits by affecting consumers' choices. In blueberries, although fruit surface color is mainly determined by pigments (e.g., anthocyanins), cuticular waxes also play a role in modulating the surface color, and a lighter color given by a dense wax bloom is normally preferred by consumers. This study investigated the content and composition of cuticular waxes and their roles in modulating fruit surface color in 12 (seven northern highbush, three southern highbush, and two hybrids) blueberry genotypes at harvest (H1, representing the first commercial pick, and H2, representing the second commercial pick). The ultrastructural morphology of cuticular waxes was analyzed in four selected genotypes by scanning electron microscopy. The level and profile of anthocyanins and their contributions to the color were also assessed. Total cuticular wax content ranged from 27.7 to 95.8 μg cm −2 among genotypes at H1 and decreased by an average of 23.9% from H1 to H2. Triterpenoids (62.5% of the total cuticular waxes on average) and β‐diketones (22.9% on average) were the first and second largest wax groups in all genotypes, respectively. β‐Diketones were previously proven to affect leaf surface color in wheat; in this study, their content strongly correlated with the lightness of the blueberry surface. Scanning electron microscopy revealed distinct wax morphologies among genotypes. No significant relationships were found between total or individual anthocyanin concentrations and fruit surface color. Our results suggest that, at harvest, variation in the fruit surface color among blueberry genotypes is more closely related to the content and composition of cuticular waxes than the level and profile of anthocyanins, with β‐diketones being particularly important. This study provides new insights for blueberry breeding programs aiming to improve the surface color in order to meet the market demand.

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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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.021
GPT teacher head0.210
Teacher spread0.189 · 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

Citations25
Published2023
Admission routes2
Has abstractyes

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