ASSESSMENT OF BOTANICAL AND GENETIC COLLECTION OF SOYBEAN FOR MORPHOLOGICAL AND YIELD ATTRIBUTES AND THEIR IMPACT ON NODULE-ASSOCIATED BACTERIA AND SOIL FERTILITY
Bibliographic record
Abstract
Assessment of botanical and genetic collection of soybean cultivars transpired during 2021–2022, for morphological and yield-related traits and their impact on nodule bacteria and soil fertility, at the Dormon Scientific Experimental Station, Institute of Genetics, Academy of Sciences of the Republic of Uzbekistan, District Kibray, Tashkent region, Uzbekistan. The soybean cultivars, grown in a randomized complete block design, had a factorial arrangement with three replications. Results revealed that in the botanical collection, the highest seed yield per plant came from the soybean cultivar K-2600 (48.3 ± 1.30 g), 1000-grain weight from Bk-105 (215.9 ± 0.15 g), and the number of grains per plant from the genotype K-2600 (346.4 ± 6.48). Moreover, in the genetic collection, the high oil content resulted in the genotypes Gen-15 (20.11%), Gen-13 (19.46%), and Gen-11 (19.40%). The higher values of the total protein content emerged in the soybean cultivars, Ehtiyozh (34.09%) and Gen-9 (33.74%), Gen-19 (34.72%), and Gen-26 (33.08%). Among the two types of soybean collections studied, the most substantial number of root nodules appeared in the cultivar Sochilmas (96.65 ± 0.11) during the pod formation phase. The recorded highest amount of soil microelements, according to soil analysis, was at the sowing site of the soybean cultivar, Genetiс-1 and on average, the soil samples contained N-NO3 (28 mg/kg), mobile P2О (212.3 mg/kg), and volatile trace element K2О5 (36 mg/kg), found to remain in the soil after crop harvesting. The conclusion based on the results indicates that the local soybean cultivar Genetik-1 has a more positive effect on improving soil fertility versus the other genotypes in both collections.
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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".