Optimization of cultivation techniques improves the agronomic behavior of Agaricus subrufescens
Bibliographic record
Abstract
Abstract New species of medicinal mushrooms have emerged over the past several decades, such as the Sun mushroom, Agaricus subrufescens. Horticultural improvements are required to shift its cultivation from small-scale local production to large-scale international production. The research reported here evaluated the agronomic behavior and the chemical characteristics of the Sun mushroom as a function of i) nutritional supplementation ii) ruffling of the casing layer and iii) the temperature management on the primordia induction and reduction of the crop cycle. Supplementation was beneficial for yield, unit mushroom weigh and decrease in time to first harvest. Supplementation improved biological efficiency with Champfood providing a yield increase of 15% over the non-supplemented compost. Among the supplements only Promycel increased the individual mushroom weight. Ruffling overall improved the yield in the 2nd and 4th flush. Already biological efficiency was greater by 21%. The highest yield harvested in any single day in the crop occurred in 3rd flush with the amount of 2.484 kg of mushrooms per m2 for the rapid induction method. Still the biological efficiency was not significantly affected by the mushroom induction temperature method. Only the fat content of the mushrooms was positively affected by the rapid induction of primordia. Champfood supplement promotes a reduction in the value of earliness and an increase of 1st flush yield. The ruffling technique provided an increase in biological efficiency due to the great number of mushrooms harvested. Rapid primordia induction allowed the crop cycle to end 3 days earlier than the slow primordia induction, providing a higher production rate.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".