Determination of Malting Barley Cultivars Suitable for Tokat-Kazova Conditions
Bibliographic record
Abstract
This study was conducted to determine suitable malting barley cultivars for Kazova plain in Tokat province in 2001-02 and 2003-03 growing periods. Two Turkish cultivars, Tokak 157/37 and Bülbül-89, a high quality Canadian malting barley cultivar, Harrington, and 15 other foreign cultivars evaluated by Efes Pilsen malting company throughout Turkey were used. Most cultivars had grain yields over five tons per hectare, 1000-seed weights of 40-50 g and test weights of 68-70 kg in 2001-02 period in which precipitation during the growing period was similar to long term average. However, some cultivars including the two Turkish cultivars seriously lodged in this year. In 2002-03 period, in which precipitation was seriously lower than long term average, grain yields of most cultivars were around 3,0-3,5 tons per hectare, 1000-seed weights 40-50 g, and test weights 67-69 kg. Turkish cultivar Tokak 157/37 had yields similar to high yielding cultivars and quite good malting quality indications. Among cultivars of foreign origin, Anita, Lagoda, Prosa, Madras, Asso and Pacific seemed to be suitable for the region. However, in order to fully establish the malting barley production potential of the region, additional studies covering other ecologies of the region and including detailed malt analyses are necessary.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".