Metabolomics changes in ‘Honeycrisp’ apple during cold storage in association with soft scald disorder development and delayed cooling treatment
Bibliographic record
Abstract
Soft scald is a common physiological disorder in ‘Honeycrisp’ apples that develops during cold storage and reduces fruit quality and marketability. Delayed cooling prior to cold storage and dynamic management of fruit storage temperature have been used to mitigate the development of soft scald with variable success. To explore biochemical changes associated with the development of soft scald and to identify mechanisms by which delayed cooling reduces its development, we conducted an untargeted metabolomics with data independent acquisition (DIA) on a liquid chromatography-mass spectrometry. Changes in ‘Honeycrisp’ apple metabolites were investigated during storage and in response to delayed cooling for two seasons. In total, 1212 features were detected and quantified. An ANOVA revealed significant changes in 114 metabolites at the metabolomic level. An ANOVA and orthogonal PLS-DA combined approach further showed 8 and 20 features changed significantly in association with development of soft scald features and in relationship to the delayed cooling treatment, respectively. Fifteen of these features were putatively identified indicating their role in soft scald development and mitigation. A group of flavonol compounds including isoquercitrin and rutin that increased during delayed cooling treatment were identified providing evidence that they may contribute to alleviate the disorder development. This study provides new evidence that metabolites associated with phenolic metabolism are involved in relation to soft scald disorder development and respond to delayed cooling treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".