Modelling the effects of row configuration on sorghum yield reliability in north-eastern Australia
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Bibliographic record
Abstract
In recent years, many sorghum producers in the more marginal (<600 mm annual rainfall) cropping areas of Queensland and northern New South Wales have used skip row configurations in an attempt to improve yield reliability and reduce sorghum production risk. This paper describes modifications made to the APSIM sorghum module to account for the difference in water usage and light interception between alternative crop planting configurations, and then demonstrates how this new model can be used to quantify the long-term benefits of skip sorghum production. Detailed measurements of light interception and water extraction from sorghum crops grown in solid, single and double skip row configurations were collected from on-farm experiments in southern Qld and northern NSW. These measurements underpinned changes to the APSIM-Sorghum model so that it accounted for the elliptical water uptake pattern below the crop row and the reduced total light interception associated with skip row configurations. Long-term simulation runs using long-term weather files for locations near the experimental sites were used to determine the value of skip row sorghum production as a means of maintaining yield reliability. These simulations showed a trade-off between long-term average production (profitability) and annual yield reliability (risk of failure this year). Over the long term, the production of sorghum in a solid configuration produced a higher average yield compared with sorghum produced in a skip configuration. This difference in average yield is a result of the solid configuration having a higher yield potential compared with the skip configurations. Skip configurations limit the yield potential as a safeguard against crop failure. To achieve the higher average yield in the solid configuration the producer suffers some total failures. Skip configurations reduce the chance of total failure by capping the yield potential, which in turn reduces the long-term average yield. The decision on what row configuration to use should be made tactically and requires consideration of the starting soil water, the soil’s plant-available water capacity (PAWC), and the farm family’s current attitude to risk.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it