Growth and Development of Leaf Vegetable Crops under Conditions of the Phytotechnical Complex in Antarctica
Bibliographic record
Abstract
Ensuring the technical and technological possibility of regularly obtaining fresh, high-quality plant production in Antarctic stations is an urgent task of our time. This work is devoted to studying the growth and development of leaf vegetable crops and the main quality indicators of their edible parts when grown in the phytotechnical complex greenhouses at the “Vostok” Antarctic station and at the agrobiopolygon of the Agrophysical Research Institute (AFI). The plants, belonging to 13 varieties of 9 types of leaf vegetable crops (arugula, garden cress, cabbage, mustard, leaf radish, leaf lettuce, amaranth, dill, parsley leaf), were studied during five growing seasons at the “Vostok” station and at the AFI agrobiopolygon under controlled conditions (control). The experimental data obtained demonstrate the high productivity of the phytotechnical complex for most of the investigated crops per unit of useful area, with lower costs of electricity and water consumption per unit of production compared with a number of greenhouses at foreign Antarctic stations and greenhouse complexes with controlled conditions located on other continents. Lettuce crops were the most adapted to the growing conditions at the Antarctic station “Vostok”. They did not differ in their evaluated characteristics from the control. All other investigated crops, while not differing in their development rate and quality, had statistically significant (16–61%) decreases in their yield per 1 m2 per year. This may demonstrate the difference in the “genotype–environment” interaction in plants grown at the Antarctic station and AFI agrobiopolygon, probably due to the different barometric pressure and partial pressure of oxygen at the two locations. The positive psychological effects of the greenhouses were identified along with nutritional and other qualities of the plants.
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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 | 0.000 | 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 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".