Influence of Sowing Dates and Seeding Rates of Spring Triticale (Triticosecale Wittmack) on Yields and Crop Structure Elements
Bibliographic record
Abstract
One of the most important areas of development of the agro-industrial complex at the present stage is obtaining high and sustainable grain yields.Spring triticale plays a significant role in solving this problem, as one of the most productive grain crops.In this case, adjusting the seeding rate is an affordable and effective method for successfully managing the crop's productivity.The purpose of the study is to substantiate the optimal sowing dates and seeding rates of spring triticale in the zone of ordinary chernozems of Northern Kazakhstan, providing a maximum yield of grain products.The innovation of this article is that it presents data on the study of sowing dates and seeding rates of nontraditional spring triticale culture of two varieties -Dauren and Rossika in the conditions of the North Kazakhstan region.The results of the average yield of spring triticale varieties depending on the sowing period, seeding rates, and meteorological indicators of the growing season of 2019-2021 were provided.It was concluded that the most optimal sowing period is the end of the second ten daysthe third ten days of May, and the optimal seeding rate is in the range of 4.0-5.0 million germinable seeds per hectare.
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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".