Performance of Thompson Seedless Grape and ITS Clones on Dog RIDGE Rootstock
Bibliographic record
Abstract
Afield trial was conducted at the R&D Farm of Maharashtra State Grape Growers’ Association, Pune, India to assess the performance of Thompson Seedless and its clones, namely Tas-A-Ganesh and Sonaka on Dog Ridge rootstock. Brix-yield the ultimate measure of productivity in grape, particularly in raisin grapes, was more in Sonaka compared to the rest, which were at par. Dominance of yield/vine over Brix content was evident in determining the brix yield. Vine yield was more in Sonaka compared to other varieties because of more number of clusters in spite of less bunch weight. Factors impairing shoot maturity namely, shoot length and rate of shoot growth were more; NO 3 -N status was more and K status less after back pruning in Sonaka. Fruitfulness of buds as indicated by the cluster/cane ratio was more resulting in more clusters/vine in Sonaka, though the canes/vine was less. Yield increase in Sonaka was mediated through more cane diameter, shoot length on the 45 th day and shoot growth rate during 30-45 days after back pruning; less number of shoots/vine and shoot length at veraison. Results of this trial revealed that Sonaka is the best variety on Dog Ridge for obtaining high yield of quality grapes and that the viticultural practices that increase the cane diameter, shoot length on the 45 th day and shoot growth rate during 30-45 days after back pruning; and reduce the number of shoots/vine and shoot length at veraison might help increase the yield in Thompson Seedless and Tas-A-Ganesh.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".