Characteristics of introduced lentil varieties (Lens culinaris Medik.) in the Southern Forest Steppe zone of Ukraine
Bibliographic record
Abstract
Purpose. To evaluate the introduced lentil varieties (Lens culinaris Medik.) originating from Canada and Spain in the conditions of the Southern part of the Forest-Steppe of Ukraine according to a complex of indicators of productivity and adaptability. Methods. During 2019–2021, in the conditions of the plant research station Ustymivka Experimental Station of Plant Production of the Plant Production Institute of the NAAS of Ukraine (Poltava Region, 49o18’21”N, 33o13’56”E), 26 new samples of lentils from Canada and Spain were studied. In the pod and seed ripening stage (BBCH 86–90), under field and laboratory conditions, indicators of yield, productivity, 1000 seed weight, early-ripening, plant height and height from the soil of the first pod, number of pods and seeds per plant, number of seeds in a pod, pod parameters. Results. In the process of studying the new lentil samples, it was found that their productivity varied from 127 to 258 g/m2, with the most productive varieties being ‘CDC Creenstar’, ‘CDC Cherie’ (Canada), ‘Angela’, ‘Amaya’ (Spain). Throughout the study period, the highest productivity, according to the indicator “seed weight per plant”, was shown by the plants of the following lentil varieties: ‘CDC Cherie’ (4.4 g), ‘CDC Creenstar’ (4.2 g), ‘CDC Greenland’ (4.5 g), ‘CDC Imigreen’ (4.4 g), ‘CDC QG-2’ (4.1 g), ‘CDC Impulse’ (4.0 g) (Canada), ‘Angela’ (4.6 g) (Spain). Plant productivity was high, both in terms of increased number of seeds and 1000 seed weight. The highest level of the indicator of the number of pods per plant was recorded in the lentil varieties ‘CDC Imax’ (64.4 pcs), ‘CDC Impala’ (65.5 pcs), ‘CDC QG-2’ (67.4 pcs), ‘CDC Creenstar’ (67.8 pcs), ‘CDC Cherie’ (75.2 pcs) (Canada), ‘Amaya’ (64.8 pcs), ‘Angela’ (75.1 pcs) (Spain). Almost all the examined samples were of medium ripeness (81–85 days) and optimal for the Southern Forest Steppe Zone of Ukraine. The Canadian varieties ‘CDC QG-2’, ‘CDC SB-2’, ‘CDC Impulse’, ‘CDC Imvincible’, ‘CDC Impact’ were the earliest (76 days). Varieties combining several valuable characteristics deserve special attention: ‘CDC Creenstar’, ‘CDC Greenland’, ‘CDC Impulse’, ‘CDC Impact’ (Canada), ‘Angela’ (Spain). Conclusions. The above mentioned varieties can be recommended as sources of valuable traits for practical use in breeding, and they are also suitable for cultivation in the Southern Forest Steppe Zone of Ukraine.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".