Structure and Trends of Worldwide Research on Durum Wheat by Bibliographic Mapping
Bibliographic record
Abstract
The bibliometric mapping approach is a quantitative methodology to analyze the structure and evolution of research activities in a scientific area or a discipline. The objective of the current study was to perform a bibliometric analysis of the worldwide durum wheat literature published from 1961 to 2022 to identify topics and trends and their evolution over time. A total of 7512 documents were analyzed to generate bibliometric maps illustrating the main research topics. Most of the articles (91.6%) were published in indexed journals, with a low percentage (3.4%) in conference proceedings. The most active journals were the Journal of Cereal Science, Euphytica, Theoretical and Applied Genetics, Cereal Research Communications, and Cereal Chemistry. Italy, the USA, Canada, Spain, and France were the countries publishing the most documents. Research interests were focused on mutagenesis, interspecific hybridization, and technological quality in 1961–1980 and moved to conservation farming, molecular genetics, and nutritional quality in the last two decades. Future durum wheat production is facing challenges from climate change, water scarcity, and rising demand for sustainable food production. Advancements in molecular breeding techniques, genome editing, precision agriculture, and conservation farming can expedite wheat improvement and pave the way toward a healthier environment. The analysis of a large amount of bibliographic data provides useful information for researchers and policymakers and represents a starting point for a comprehensive discussion for future research.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.122 | 0.192 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".