Influence of Rootstocks (Gisela 5, Gisela 6, MaxMa, SL 64) on Performance of ‘0900 Ziraat’ Sweet Cherry
Bibliographic record
Abstract
This study was carried out in order to determine the effect of rootstocks (Gisela 5, Gisela 6, MaxMa 14 and SL 64) on performance of sweet cherry cultivar ‘0 900 Ziraat’ during 2010-2013 years. The trail in randomized block design was established as to factorial design. Each graft combination included 20 trees. The trees was trained as Spanish Bush training system. At the end of study, effect of rootstocks on vegetative growth was found significant. It has been determined that the trees grafted on SL 64 and MaxMa 14 rootstocks were more vigorous than the those grafted on Gisela 5 and Gisela 6. The rootstocks formed significant differences at the precocity. While the first blooming on the trees grafted on Gisela 5 and Gisela 6 rootstocks occurred at the second year after planting, the first blooming on the trees on MaxMa 14 and SL 64 rootstocks occurred at fourth year after planting. It has been determined that occur significant differences on yield per tree and yield efficiency among rootstocks. In terms of yield per tree and yield efficiency, While the lowest value was in SL 64 rootstock, the highest value was recorded in Gisela 5, and it has been determined that the differences between three rootstocks (Gisela 5, Gisela 6 and MaxMa 14) were not significant. While fruits weight varied according to the rootstock used in study, the trees grafted on Gisela 5 had the smallest fruit. Accompanied with differences between MaxMa 14 and SL 64 rootstocks were not significant, the biggest fruits were produced on trees grafted on SL 64 rootstock. As a result of the statistical analysis, it has determined that the rootstocks that used in trial did not create significant differences on soluble solids content (SSC) value. One of the most significant diagnosis was 6 % mortality rate that occurred on trees grafted Gisela 5 and Gisela 6 rootstocks.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".