Enhancing the Profitability of Wheat
Bibliographic record
Abstract
Wheat is a staple in many prairie crop rotations, yet as years pass net profitability has declined, despite significant breeding improvements for yield. Unfortunately, updated agronomic research in wheat has been minimal; yet it may be the key to enhancing the profitability of this crop, if management practices are tailored to individual market classes and varieties. This project was designed to incorporate components of intensive wheat management in order to enhance wheat profitability. The first objective was to identify how wheat market classes and varieties are affected by enhanced management and the second objective was to identify how genetic characteristics of wheat interact with the varying soil and climate conditions across Saskatchewan. This small plot research project was conducted at Indian Head, Melfort, Scott, Swift Current and Yorkton, SK from 2017 to 2019. Six wheat varieties from three wheat cla sses were selected based on genetic differences in Fusarium Head Blight resistance, lodging resistance, maturity, yield and protein content. Each variety was grown under three progressively intensified management levels. Results indicate that CWRS varieties tended to be more responsive to Intensive management, on a count of the seed treatment applied, in order to increase plant populations than CPSR or CSWSW varieties. Enhanced management often led to hastened maturity across all varieties, while varietal selection is important in order to prevent delayed maturity with Conventional and Intensive management. Intensive management resulted in maximum yield for CWRS and CPSR varieties, while CWSWS were less responsive to management level. Conversely, CWRS and CPSR varieties were less responsive to management level, while CWSWS benefited the greatest from Intensive management for building protein. Test weight and seed size differences were largely attributed to genetic differences and an y responses to management were of little practical agronomic importance. FDK values were largely reflective of genetic differences, with Enhanced management providing increased control. In the end, CWRS varieties tended to be more profitable than CWSWS and CPSR varieties, with Conventional management providing the best net returns. Overall, CWRS varieties tended to be more responsive to changes in management intensity. Although intensive management resulted in the largest yields, Enhanced management hastened maturity and reduced FDK more consistently. However, Enhanced management did not always out preform Conventional. Therefore, the results of this experiment indicate that Conventional management of wheat in Saskatchewan continues to provide the best return on investment. In some circumstances, Enhanced management can be beneficial. Link to Video Presentation: https://youtu.be/y6kLG1phYUc
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".