Analyzing shifts in fertilizer use with crop rotation practices in Saskatchewan across distinct periods from 1991–94 to 2016–19
Bibliographic record
Abstract
Introduction Over the last three decades, Saskatchewan, home to over 40% of Canada's cropland, has seen transformative shifts in dryland crop production. Notably, the adoption of herbicide-tolerant canola in 1995 and the increase in nitrogen-fixing pulse crops like lentils and chickpeas have moved agricultural practices away from traditional fallow and tilled fields to more continuous crop rotations. Methods Our study, analyzing survey data from 1991–1994 and to 2016–2019, evaluates how these changes have influenced fertilizer usage, focusing on application rates, timing, and types. Results We anticipated that integrating nitrogen-fixing pulses and genetically modified herbicide-tolerant (GMHT) canola would promote more sustainable fertilization methods. Indeed, our results show significant reductions in nitrogen fertilizer use - by 49% to 73% in the earlier period and 3% to 19% more recently - due to the integration of these crops. Discussion GMHT canola, by reducing the dependency on synthetic nitrogen fertilizers, demonstrates a shift in fertility dynamics by enhancing nutrient uptake efficiency. This adaptation has not only reduced fertilizer costs but also contributed to more sustainable crop management. These findings highlight the environmental benefits of updated crop rotations, emphasizing the improved efficiency of fertilizer use. More broadly, they highlight the potential of expanded pulse cultivation to boost agricultural sustainability and reduce greenhouse gas emissions through better nitrogen management. While the transferability of these findings may be limited by the study's regional focus and sample size, they hold value for informing sustainable practices in similar agricultural settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 0.001 |
| 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".