Analysis of Relationship between Soybean Relative Maturity Group, Crop Heat Units and ≥10 °C Active Accumulated Temperature
Bibliographic record
Abstract
Crop heat units (CHU) and ≥10 °C active accumulated temperature (≥10 °C AAT) are important indexes to quantify the effects of temperature on soybean development. The relative maturity group (RMG) is widely used in the classification of different soybean varieties. However, CHU and ≥10 °C AAT (AAT) were applied in Canada and northeastern China, respectively, and the relationships among CHU, AAT and RMG are poorly documented. The objective of this study is to analyze the conversion function among CHU, AAT and RMG based on two datasets. The first dataset was obtained to analyze the relationship between RMG and AAT in 395 varieties in Northeast China. The second dataset was obtained to calculate the relationship between CHU and AAT at 95 weather stations based on 30-year climatic data (1990–2019). The results showed that both relationships were significantly and positively correlated, and the R-square of these relationships were 0.90 and 0.98, respectively. The distribution of CHU or AAT in the Northeast is proposed. These results can be extensively used for predicting the CHU or AAT of soybean cultivars given the known RMG, thus determining the adaptation zone as well as the growth stage of agricultural practices and responses to heat accumulation. The conclusion of the current study is expected to be widely adopted by soybean regionalization and germplasm exchanges throughout the world.
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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 | 0.002 |
| 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) | 0.001 | 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".