Seasonal Changes in Amylose and Starch Compositions in ‘Ambrosia’ Apples Associated with Rootstocks and Orchard Climatic Conditions
Bibliographic record
Abstract
The dynamics of amylose (AM) and total starch content (TSC) have been studied in several apple varieties; however, their responses to environmental variables and rootstocks are less understood in new low-climacteric varieties. In addition, the pertinence of AM and TSC to fruit dry matter content (DMC), fruit quality at harvest, and quality retention after storage is little understood. In this study, we investigated the seasonal changes in AM and TSC of ‘Ambrosia’ apples grafted onto dwarfing rootstocks Malling 9 (M.9) and Budagovsky 9 (B.9) in two consecutive years, 2016 and 2017, in the Okanagan-Similkameen Valley, British Columbia, Canada. Enzymatic methods with Megazyme® kits were used to analyze the fruit samples collected from four orchards in the growing season. In 2016, the orchard microclimate exhibited cooler nights and greater diurnal temperature ranges (DTRs) compared to 2017. As a result, the AM content and AM portion in TSC were significantly higher in 2016, with levels peaking over 40% compared to the values observed in 2017. However, there were no significant differences in peak values of TSC between the two years. Additionally, the apples grown on the B.9 rootstock consistently showed higher levels of AM and AM percentage compared to those grown on the M.9 rootstock. The study also used Felix 750 Produce Quality Meter, a handheld infrared spectrometer, to assess the dry matter content (DMC) of growing fruit, which showed a strong correlation with AM content (r > 0.8). After being harvested at commercial maturity and stored in controlled atmospheric chambers (CA) for 8 months, fruit quality analysis suggested that the AM level and its percentage in TSC played an important role in determining ‘Ambrosia’ apple quality after long-term storage.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".