Comparative assessment of early season soybean cultivars in organic and conventional production system for morphological and agronomic traits
Bibliographic record
Abstract
Abstract Organic production systems differ from the conventional system, especially because of the insect pest, weed, disease, and nutrient management. Therefore, there has been a focus on increasing performance stability in soybean [Glycine max (L.) Merr.] cultivars specifically adapted for organic farms. The objective of this study was to conduct a comparative assessment of Maturity Group 0 soybean genotypes grown in both organic and conventional conditions for several traits important in the organic soybean production system, such as early season canopy development, root morphology, nodule production, and nutrient use efficiency. A soybean panel consisting of 33 cultivars was grown in four environments (two locations × two years) on an organic farm and conventional production system farm in Southern Ontario, Canada. Significant differences among genotypes were observed for root morphology and canopy development in the organic environment only. Early season canopy development, root length, nodule mass, and nutrient use efficiency were related to yield in both environments. In addition, yield rank correlations between genotypes in two locations were significant in 2014 (r = .57) and 2015 (r = .31), and some large crossover effects were observed in both tested years. The principal components analysis for these and other agronomic traits showed that resource acquisition traits such as canopy development, root length, and nodule mass were more closely related to yield in the organic system than nutrient use efficiency. Overall, the results of this study may be useful for soybean breeders interested in developing cultivars adapted to the organic production system.
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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".