EVALUATION OF AGRONOMIC PERFORMANCE OF DOMESTIC AND EXOTIC SOYBEAN GERMPLASM IN CROATIA
Bibliographic record
Abstract
The collaboration and interchange of breeding materials between breeding programs worldwide is important and necessary to increase the amount of genetic diversity by incorporating unique exotic germplasm into existing domestic germplasm. The objective of this study was to measure and compare the agronomic performance of 15 soybean cultivars released by the Agricultural Institute Osijek (Croatia) (OS-cultivars) and 15 cultivars released by the University of Guelph (Canada) (CA-cultivars) in Croatia. Based on the comparison, parental combinations could be designed to introgress exotic germplasms from the CA-cultivars into Croatian. Agronomic performance was determined in field trials that were conducted at the experimental field of the Agricultural Institute Osijek during the period from 2002 to 2005. Quantitative traits were measured and analyzed for maturity, grain yield components, level and stability of grain yield, adaptability, lodging resistance and field tolerance to Peronospora manshurica. The results indicated higher agronomic performance of OS-cultivars compared to CA- cultivars. However, comparison of yield is only tentative because all but one OS cultivar were later maturing than the CA-cultivars. Among 15 tested CA-cultivars, five cultivars (OAC Millennium, OAC Champion, OAC Bayfield, OAC Auburn, OAC Wallace) were identified as the most favorable for parental combinations in hybridization with OS-cultivars. The results of this study will enable strategic incorporation of diversity from exotic Canadian germplasm into the domestic Croatian germplasm to develop segregating populations from which new, genetically more diverse improved soybean line, could be released.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".