Scientific evidence of sustainable plant disease protection strategies for oilseed rape (Brassica napus) in Sweden: a systematic map
Bibliographic record
Abstract
BACKGROUND: Oilseed rape (OSR; Brassica napus L.) is a highly valued crop for food, feed and industrial use. It is primarily grown in temperate climates, and over recent decades, its area of production and profitability have increased. Concurrently, several diseases negatively impact OSR production. Diseases caused by soil-borne pathogens, pose a risk of substantial yield loss since crop rotation schemes have become narrow as the time lapse between OSR crops in a field has been shortened. The aims of this paper were to provide an overview of plant protection measures available for OSR production and to identify knowledge gaps and areas where more research is needed. METHODS: This systematic map builds on a previously published protocol and follows the ROSES reporting standard. The search strategy was developed in collaboration with stakeholders and designed to cover available scientific evidence for OSR disease management in climate zones relevant for Scandinavian crop production (Dfc, Dfb, Cfb and Cfa in the Köppen-Geiger climate classification). Five scientific databases were used to identify peer-reviewed literature, complemented by additional searches performed in grey literature. Articles were screened at three stages: the title, abstract and full text. The eligible publications included studies of OSR crops, and all measures to control crop disease in agricultural fields were considered eligible interventions. The comparator was intervention and no intervention, and the yield per unit area, disease suppression or an increase in crop quality were determined to be outcomes of interventions. A basic assessment of the experimental design of each study was performed to assess its eligibility. All articles were coded based on the following categories: the location and climate zone, disease, pathogen, intervention and management method, outcome and study design. Articles not reporting original data but judged to be relevant (i.e., review papers, books and notes of registration of cultivars) were saved in a separate category called "books, reviews and reports". REVIEW FINDINGS: A total of 4633 articles were collected through systematic searches. After duplicates were removed, 3513 articles were included in the screening process. After screening at the title and abstract levels, 897 articles were evaluated at the full text level, and 118 articles comprised the studies that met the eligibility criteria of the systematic map. The country (Canada) and region (Europe) with the largest OSR crop production areas also contributed the highest number of articles. In total, 17 different diseases were reported, with black leg (syn. Phoma stem canker) being the most studied disease. Nineteen different intervention methods or management types were examined. Cultivar resistance and pesticide application were the most studied control measures. CONCLUSION: We report scientific studies on plant disease protection measures for OSR based on field trials where the results are intended to be directly implemented in crop production management. The map clearly provides an overview of research progress throughout the time period chosen, and it identifies knowledge gaps regarding important diseases where only a few studies have been published, for example, diseases caused by viruses.
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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 | 0.020 | 0.078 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.056 | 0.038 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".