Scientific evidence of sustainable plant disease protection strategies for oats in Sweden: a systematic map
Bibliographic record
Abstract
Abstract Background Oat (Avena sativa L.) is an important cereal crop for livestock feed and human consumption. The largest oat-producing countries are located in the Northern Hemisphere with Sweden as the tenth largest producer. Oat production is challenged by different diseases that can lead to significant yield reductions and impaired grain quality. The use of efficient and sustainable plant protection management is of great economic and ecological importance. The systematic map in this study aims to provide a knowledge base inventory and to identify areas that need to be researched in the future in terms of plant disease management for more sustainable oat production. Methods Literature searches were conducted in both academic bibliographic databases and relevant online sources of grey literature. A time-span restriction of 40 years (1978–2018) was applied to the searches. English was used in all searches, and Swedish, Norwegian and Danish languages were used in the grey literature searches. The screening process, which followed a protocol with eligibility criteria, was conducted at three levels: title, abstract and full text. Metadata incorporating bibliographic information, study location, climatic zone, disease name, the common and scientific names of the disease-causing organism, pathogen type, intervention and management methods, diseased plant part, plant stage, and outcome were extracted from the studies and included in the systematic map. The systematic map findings are visualized in figures and tables and described. All included studies can be found in a searchable database. Review findings A total of 58 eligible articles, most (n = 51) from scientific journals published in English, were included in the systematic map. A majority of the studies were conducted in the Northern Hemisphere in temperate climatic zones, where most of the world’s oats are produced. The earliest article was published in 1980, followed by an oscillating temporal distribution of articles over the following years. By country, Canada had the highest number of articles, and by region, Europe had the highest number. Fungi were the most studied pathogen type, and a total of 16 different diseases were reported. Fusarium head blight (Fusarium spp.) and crown rust (Puccinia coronata) were the most studied diseases. In total, 17 different intervention management approaches for controlling the diseases were analyzed in the articles, with cultivar resistance and pesticide application as the most studied methods. Conclusion The map highlights the low quantity of available relevant field research on oat disease management. To our knowledge, this is the first systematic map of crop protection. This map provides a database of scientific literature that can be used to develop sustainable disease management strategies. The method used in this study has great potential and can also be used to benefit other crops. Research is often based on the availability of funding, and this map could be a useful tool for researchers and funding organizations to identify relevant research topics that need to be further studied. In addition, this systematic map offers a useful tool for field-based advisors in providing scientifically relevant crop protection strategies for farmers.
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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 | 0.016 | 0.083 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.048 | 0.032 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".