Evaluation of the biological-economic and biochemical traits of promising Ribes nigrum hybrids in Estonia
Why this work is in the frame
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Bibliographic record
Abstract
The evaluation of promising hybrids of blackcurrant (Ribes nigrum L.) was carried out in 2016-2018 in South-Estonia at Polli Horticultural Research Centre of the Estonian University of Life Sciences. The objective of the Estonian blackcurrant breeding programme is to produce cultivars that are winter hardy, resistant to gall mite (Cecidophyopsis ribis Westw.) and gooseberry mildew (Sphaerotheca mors-uvae (Schw.) Berk.), well suited to machine harvesting, with good yield and quality of fruits. The evaluation plot was established in the autumn of 2014. Twenty-four blackcurrant promising hybrids from the Estonian blackcurrant breeding programme and a new Estonian cultivar 'Mairi' as the standard were evaluated for beginning of flowering and fruit ripening (expressed in growing degree-days, GDD), winter hardiness, resistance to diseases and pests (expressed in scores 1-9), number of fruits per cluster, yield (kg per bush), weight of fruit and content of the soluble solids (Brix). Fruits were analysed for titratable acids, ascorbic acid, anthocyanins and polyphenols. The evaluation revealed the best black-fruited genotypes to be Nos 3-08-1 ('Ben Alder' 'Titania'), 7-08-1, 7-08-2 ('Intercontinental' 'Pamyat Vavilova') and 15-09-1 ('Asker' free pollination), and the green-fruited genotype No. 8-09-3 ('jebyn' 'Mairi'). All these genotypes are winter hardy and visually resistant to gall mite and gooseberry mildew. The first four produced good yields and large fruits.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it