Mycelial Growth, Biomass Production and Iron Uptake by Mushrooms of Pleurotus species Cultivated on Urochloa decumbens (Stapf) R. D. Webster
Bibliographic record
Abstract
Mushrooms absorb minerals and are able to accumulate them as functional organic compounds during growth. Iron is one of the elements required for various metabolic processes but low intake has resulted to some nutritional deficiencies. This study investigated the effect of different iron concentrations in the culture media on mycelial growth, biomass production, hyphae diameter and distance between septa of six species of Pleurotus, namely Pleurotus ostreatus; Pleurotus cornucopiae; Pleurotus djamor; Pleurotus pulmonarius, and Pleurotus djamor v. roseus. These macrofungi were further grown on substrate based Urochloa decumbens with addition of Fe (0, 500 and 1000 mg Kg-1). The mycelial growth rate and biomass produced by Pleurotus species decreased (P<0.05) as iron concentration increased from (0 - 100) mg L-1. This shows an inhibitory interaction between the fungi and iron at higher concentration. The hyphae diameter and distance between septa of the examined fungi were respectively ranged from 45 µm to 80 µm and 40 µm to 119 µm at iron concentration of (0 -100) mg L-1. The estimated iron uptake in cultivated Pleurotus species ranged from 37.8 µg g-1 to 96.6 µg g-1 when 500 mg Kg-1 and 1000 mg Kg-1 of Fe was added to the substrate. The cultivation of edible macrofungi enriched with iron could improve the socio economic status and play a nutritional role in decreasing anemia.
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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) | 0.000 | 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".