Accumulation of degree-days and chilling hours for ‘Eva’ apple tree production in temperate climate
Bibliographic record
Abstract
The cultivation of apple tree is highly dependent on meteorological variables, especially temperature. The link between accumulation of degree-days (DD) and accumulation of chilling hours (CH) are determinant to field success, in the context of climate change. The objective of this study was to quantify the accumulation of DD necessary during the reproductive phenological stages for cultivar IAPAR 75 Eva, considering the accumulation of CH during the period of dormancy. The study was carried out at the Experimental Station from the Rural Development Institute of Paraná IAPAR-EMATER, in the municipality of Palmas, Paraná State, Brazil. The evaluations were from 2013 to 2019, showing for each three days, the phenological phases and the value of DD and CH. The results were submitted the simple and multiple correlation by the R® software. We verified the influence of the increase in temperature on the cycle acceleration, in addition, it was verified a tendency of less requirement for DD to advance the cultivar cycle. Were verified the value of chilling hours as 281, 156, 84, 326, 96, 76 and 11 hours of chill, respectively, and the consequent accumulation of DD to breaking dormancy was appointed as 1093, 1156, 1574, 1157, 1834, 1096 and 1838 DD, respectively. We concluded that CH causes impact in DD accumulation to development of apple tree. Higher temperatures accelerate the apple tree development. With the information of CH accumulation in dormancy, it is possible estimate the quantity of DD to develop the phenological phases. This information contributes to agricultural planning for cultivar Eva farmers
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".