Pioppini mushrooms (Agrocybe aegerita), also called black poplar mushrooms, have a small brown cap, firm stem, and a distinctly nutty, earthy flavour. They provide selenium, copper, niacin, and riboflavin, and their firm texture means they hold their shape during cooking better than most mushrooms. They are traditional in Italian cooking, particularly in pasta and risotto.
Slice or leave whole for pasta dishes and risotto; their firmness means they can be added earlier in cooking than delicate varieties. Sauté with garlic, white wine, and parsley for a classic Italian preparation.
Where Mushroom, pioppini Stands Out
Macronutrients per 100g
Vitamins & Minerals
| Nutrient | Per 100g | % Daily Value* | Level |
|---|---|---|---|
| Potassium | 392 mg | 20% | |
| Phosphorus | 121 mg | 17% | |
| Magnesium | 16.0 mg | 4% | |
| Niacin (B3) | 6.22 mg | 39% | |
| Selenium | 4.12 µg | 7% | |
| Zinc | 0.857 mg | 9% | |
| Iron | 0.486 mg | 3% | |
| Riboflavin (B2) | 0.426 mg | 30% | |
| Copper | 0.276 mg | 28% | |
| Vitamin B6 | 0.102 mg | 7% | |
| Manganese | 0.098 mg | 5% | |
| Thiamin (B1) | 0.012 mg | 1% | |
| Calcium | 0.000 mg | 0% | |
| Vitamin D | 0.000 µg | 0% | |
| Stigmasterol | 0.000 mg | — | |
| Campesterol | 0.000 mg | — | |
| Biotin (Vitamin B7) | 15.3 µg | 31% |
* % Daily Value is the proportion of an adult
EU Nutrient Reference Value (NRV) supplied by 100g of this food.
NRVs are the labelling standard — the same basis as the “%RI” figures printed on
food packaging — so these percentages are directly comparable with a shop label.
They are a single adult figure and do not vary by age or sex, which is why they
sometimes differ from UK dietary reference values: the NRV for vitamin C is 80mg
where the UK RNI is 40mg. When Nutriofia assesses your own intake in the
reports and trackers, it uses the age- and sex-specific UK values instead.
Fibre is shown without a percentage. Our fibre values use the UK
Englyst NSP method, while the published 30g daily goal is an AOAC figure — the two
are measured differently and a single percentage would mislead.
How we source and normalise our data →