AGROBIOLOGICAL ASSESSMENT OF THE YIELD OF ASPARAGUS HYBRIDS IN DIFFERENT PHASES OF THE PRODUCTIVE PERIOD OF PLANTATIONS IN THE FOREST-STEPPE ZONE OF UKRAINE
Bibliographic record
Abstract
The purpose is to study the dynamics of yield changes in promising asparagus hybrids grown under the conditions of the Forest-Steppe zone using a ridge-free technology with drip irrigation during the phases of increasing plantation productivity and reaching maximum yield. Methods – general scientific, analytical, field, and statistical methods were applied. Results. The study examined the changes in asparagus yield during the phase of increasing plantation productivity (III–IV years of vegetation) and the phase of reaching maximum yield (V–VI years of vegetation). During the first three years of harvesting, a high rate of yield increase was recorded. By the sixth year of vegetation, the yield increase slowed down, which may be associated with the transition of plants to the stable yield phase. The obtained data on yield growth allowed us to identify the most promising hybrids for further cultivation in the Forest-Steppe zone of Ukraine. The hybrids consisting exclusively of male plants demonstrated the highest yield in this phase, surpassing hybrids that included female plants: Cumulus – 14.2 t/ha; Greenic – 13.6 t/ha; Guelph Equinox – 11.7 t/ha; Javalim – 11.6 t/ha; Prius – 11.1 t/ha. Among hybrids with an exotic spear color, attention should be given to the purple-colored Erasmus (7.5 t/ha) and the anthocyanin-free Xenolim (11.4 t/ha). An exception is the vigorous Atlas hybrid, bred by Walker Brothers Inc., which consistently provides high yields of green asparagus in the ecological conditions of Eastern Ukraine, despite containing both male and female plants. Conclusions – The study determined the peculiarities of green asparagus yield formation and the dynamics of yield increase over four years of vegetation, enabling the identification of the most promising hybrids for further cultivation in the Forest-Steppe zone of Ukraine. The obtained results can be used for further research on the adaptive potential of hybrids in the climatic conditions of Ukraine.
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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 | 0.000 | 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 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".