Status and trends in world mushroom production-III-World Production of Different Mushroom Species in 21st Century
Bibliographic record
Abstract
Due to almost unimaginable growth in production of shiitake, oyster mushroom, wood ear mushroom and Flammulina and other new mushroom species, particularly in East Asian countries like Japan, South Korea, Taiwan, China, etc, the contribution of these mushrooms to total world mushroom production has increased tremendously as compared to button mushroom which is no more the number one mushroom in terms of share in global mushroom production. FAOSTAT represents consolidated data of mushroom production but does not cover all the species and countries and species-wise data is not available. Data were hence procured from major mushroom producing countries like Japan, Korea, China, European union, America, Canada, Australia and others or accessed from the research papers/databases available. Based on data from different sources, estimated world mushroom production in 2018-19 was 43 million tonne (MT) with Lentinula edodes (shiitake) contributing 26%, Auricularia spp 21% Pleurotus ostreatus 16%, Agaricus bisporus (button) 11%, Flammulina velutipes 7%, P. eryngii (king oyster) 5%, Volvariella volvacea (paddy straw mushroom) 1% and others 13%. Other important contributors were Agrocybe aegerita, Pholiota nameko, Tremella fuciformis, Hypsizygus marmoreus , etc. Production in developed countries is on decline or has reached plateau. Shiitake, Pleurotus species, etc which are mostly cultivated in Asian countries, have started making inroads in Europe, America, Canada and Australia where Agaricus bisporus is prime contributor. Global production is likely to surpass 50 MT by 2025.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| 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) | 0.005 | 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".