Comparative study on production performance and nutritional quality of ten oat varieties in Inner Mongolia
Bibliographic record
Abstract
The aim of the experiment was to screen out high quality oat varieties suitable for planting in Tumet Right Banner, Inner Mongolia. Ten oat varieties were used as test materials, and their phenological period, agronomic characters, yield characters and nutritional quality were analyzed. The results showed that 10 oat varieties could complete the whole growth and development process in experimental area, and the growth period was 87~110 d. The plant height of Dingyan No.2 was significantly higher than that of other varieties (P<0.05), while the plant height of Mengyan No.1 was significantly lower than that of all other varieties (P<0.05). The grain yield of Bayou No.18 was the highest, followed by Bayan No.6, and Yuanza No.1 was significantly lower than that of other varieties (P<0.05). The hay yield of Dingyan No.2 and Bayou No.18 was significantly higher than that of other varieties (P<0.05), while that of Yuanza No.1 was significantly lower than that of all other varieties (P<0.05). GL381 had the highest crude protein content and Quebec had the lowest crude protein content. The highest crude fat content was Baoyou No.3, and the lowest was Mengyan No.1 and Dingyan No.2 crude fiber content was the highest, Bayou No.3 crude fiber content was the lowest. The crude ash content of Yuanza No. 1 was significantly higher than that of other varieties (P<0.05), and the crude ash content of Quebec was significantly lower than that of other varieties (P<0.05). Dingyan No. 2 had the highest acid detergent fiber content, which was significantly higher than that of other oat varieties except Quebec (P<0.05), and the lowest was Yuanza No.1. The neutral detergent fiber content of Dingyan No.2 was significantly higher than that of other varieties (P<0.05), and Bayou No.3 was significantly lower than that of other varieties (P<0.05). Bayou No.3 had the highest relative feeding value (107.67), while Dingyan No.2 had the lowest. The comprehensive analysis of grey correlation degree showed that Zhangyan No. 4, Bayou No.18 and Bayou No.3 had better performance in terms of production performance and nutritional quality. The study indicates that Zhangyan No.4, Bayou No.18 and Bayou No.3 are suitable for planting and promoting in Tumet Right Banner and its surrounding areas.
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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".