Economic optimum plant density of irrigated early-maturity soybean in southern Alberta
Bibliographic record
Abstract
With soybean [Glycine max (L.) Merr.] seed cost increasing in Alberta, understanding economic optimum plant density (EOPD) could help growers save on input expenses. A study was conducted at two irrigated locations in southern Alberta (Bow Island and Lethbridge), in three growing seasons (2014–2016), using two maturity group (MG) 00 soybean genotypes, two row spacings (RS; narrow, 17.5 cm; wide, 35 cm), and three seeding densities (SD; 30, 50 and 80 seeds·m −2 ). Exponential plant density–yield relationships were used to estimate EOPD. The earlier MG 00.4 genotype compensated yield at lower plant density (39 vs. 43 plants·m −2 ) and emergence (74% vs. 80%) than the later MG 00.8 genotype. The EOPD gaps between environments, genotypes, and RS were minimal (from 1–3 plants·m −2 ), resulting in only 1.3%–2.0% differences in grain yield (37–56 kg·ha −1 ), and gross revenue at EOPD ($16–24·ha −1 ). The overall EOPD estimate was 46 plants·m −2 , regardless of environment, genotype or RS. The study highlighted the difference between agronomic production and profit maximization in choosing an optimum plant density, and the need to establish a seeding density calculator for irrigated soybean in southern Alberta.
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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".