Productivity and nutritional value of oat crops mixed with legumes
Bibliographic record
Abstract
The results of field and laboratory studies into the cultivation of oats in single crops as well as mixed with legumes in the forest-steppe zone of Trans-Baikal during the period of 2014-2016 are presented. The studies were performed on meadow chernozem powdery carbonate soil. Agricultural technology used for fodder crop cultivation was common for this area. Mineral fertilizers were applied in the phase of pre-sowing cultivation. Fodder crops were planted in the optimum recommended period (in the second ten-day period of May). The objects of the research were the following recognized varieties: oats Metis, garden peas Batrak, spring vetch Novosibirskaya. The seeding rate of fodder in single-crop sowings was as follows: oats -5.0, peas - 0.8, spring vetch - 1.5 million of viable seeds/ha; in mixed sowings: oats - 65%, grain legumes - 40% of the total norm. The experiment was conducted in accordance with the common methodological guidelines for field experiments. Fodder crops were assessed in terms of their adaptability to growing conditions and by a set of economically valuable characteristics. Among leguminous plants, spring vetch agrocenoses was characterized by the highest productivity, which exceeded garden peas by 9-20%. The possibility of increasing the productivity and quality of fodder agrocenoses by using legumes in mixed crops was established. In terms of productivity and nutritional value, the green mass of mixed crops surpassed the single-crop cenoses of oats by 1.1-1.3 times, dry matter - by 1.5 times, feed units - by 1.5-1.6 times, digestible protein – by 3.1-3.4 times, gross energy - by 1.7 times. In mixed crops, the best results were achieved by mixings oats with spring vetch, whereby the yield of green mass was 20.9 t/ha, dry matter - 4.78 t/ha, content of digestible protein - 575.9 kg/ha, feed units -3.49 t/ha, gross energy - 51.1 GJ, availability of digestible protein - 165 g per feed unit.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".