Crop yield of promising highbush blueberry cultivars in conditions of the Central Black Earth Region
Bibliographic record
Abstract
The research comprehensively assesses the yield of introduced highbush blueberry cultivars in conditions of the Central Black Earth Economic Region based on the results of a three-year observation. The study and the analysis of the components of plant productivity and yield were conducted on such foreign-bred cultivars as Bluecrop, Elliot, Duke, Denise Blue, Patriot, Liberty, Chandler. The study was undertaken in 2021–2023 on the highbush blueberry research and production plantation located on the territory of agricultural firm SadMashService LLC in the Michurinsky municipal district of Tambov Oblast. The plantation was established in the spring of 2018 with a planting pattern of 4x0.5 m. The planting material used to create the plantation comprised 3-year-old container-grown plants which had 3 to 5 strong branches. In the process of cultivating the experimental highbush blueberry plants, intensive technology elements were employed. These included a complex irrigation system on the plantation which transported water and nutrients to the plants (a drip irrigation system in conjunction with sprinkler irrigation); the use of peat with given acidity parameters as a substrate (its pH equaled 3.5) for planting experimental plants; the use of coniferous sawdust and wood chips as mulch. The yield was studied over the course of three years. Based on the data obtained, the cultivars under investigation were divided into three groups, namely low-yielding, medium-yielding, and high-yielding. The yield of the experimental plant cultivars in the third year of study varied from 1 to 4.4 kg/bush, and from 5 to 22 t/ha. The cultivars were grouped into two categories, i. e., with large and very large berries. The average berry weight ranged from 2.6 g to 5.9 g; their number varied from 340 to 740 berries per plant.
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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) | 0.001 | 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".