Rapid in situ nondestructive evaluation of lodging risk in dryland agronomic wheat research
Bibliographic record
Abstract
Abstract The natural occurrence of lodging in wheat (Triticum aestivum L.) in small‐plot research aiming to record visual ratings is unpredictable highly dependent on environmental conditions, and does not differentiate between root and shoot lodging. Detailed plant characteristics can be used to indicate lodging risk; however, such measurements are destructive and time‐consuming for projects that are not focused solely on evaluating lodging. The Stalker, a push force meter, can be used nondestructively to rapidly indicate stem strength and elasticity, which may be useful for measuring lodging risk in small‐plot research to indicate both root and shoot lodging. The objective of this study was to evaluate the ability of the Stalker to detect agronomic management practices that are known to reduce lodging risk (reduced plant density, split nitrogen applications, and plant growth regulator applications). Stalk strength (resisting force) and elasticity (spike displacement, energy, and power) measurements were taken at anthesis and physiological maturity in a small‐plot agronomic research trial. The Stalker was able to identify practices with high and low lodging risk. Lower plant density led to increased stem strength (measured by resisting force) and stem flexibility (measured by spike displacement) compared with high plant densities, indicating a decreased risk of both stem and root lodging when low plant densities were used. Overall, the Stalker is a new tool for rapid and nondestructive measurements of lodging risk in small‐plot agronomic research trials and can indicate both stem and root lodging risk by measuring indicators of both stem strength and elasticity.
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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) | 0.001 | 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 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".